Saliency-Guided Change Detection of Remotely Sensed Images Using Random Forest

NASA Astrophysics Data System (ADS)

Feng, W.; Sui, H.; Chen, X.

2018-04-01

Studies based on object-based image analysis (OBIA) representing the paradigm shift in change detection (CD) have achieved remarkable progress in the last decade. Their aim has been developing more intelligent interpretation analysis methods in the future. The prediction effect and performance stability of random forest (RF), as a new kind of machine learning algorithm, are better than many single predictors and integrated forecasting method. In this paper, we present a novel CD approach for high-resolution remote sensing images, which incorporates visual saliency and RF. First, highly homogeneous and compact image super-pixels are generated using super-pixel segmentation, and the optimal segmentation result is obtained through image superimposition and principal component analysis (PCA). Second, saliency detection is used to guide the search of interest regions in the initial difference image obtained via the improved robust change vector analysis (RCVA) algorithm. The salient regions within the difference image that correspond to the binarized saliency map are extracted, and the regions are subject to the fuzzy c-means (FCM) clustering to obtain the pixel-level pre-classification result, which can be used as a prerequisite for superpixel-based analysis. Third, on the basis of the optimal segmentation and pixel-level pre-classification results, different super-pixel change possibilities are calculated. Furthermore, the changed and unchanged super-pixels that serve as the training samples are automatically selected. The spectral features and Gabor features of each super-pixel are extracted. Finally, superpixel-based CD is implemented by applying RF based on these samples. Experimental results on Ziyuan 3 (ZY3) multi-spectral images show that the proposed method outperforms the compared methods in the accuracy of CD, and also confirm the feasibility and effectiveness of the proposed approach.

A hyperspectral image projector for hyperspectral imagers

NASA Astrophysics Data System (ADS)

Rice, Joseph P.; Brown, Steven W.; Neira, Jorge E.; Bousquet, Robert R.

2007-04-01

We have developed and demonstrated a Hyperspectral Image Projector (HIP) intended for system-level validation testing of hyperspectral imagers, including the instrument and any associated spectral unmixing algorithms. HIP, based on the same digital micromirror arrays used in commercial digital light processing (DLP*) displays, is capable of projecting any combination of many different arbitrarily programmable basis spectra into each image pixel at up to video frame rates. We use a scheme whereby one micromirror array is used to produce light having the spectra of endmembers (i.e. vegetation, water, minerals, etc.), and a second micromirror array, optically in series with the first, projects any combination of these arbitrarily-programmable spectra into the pixels of a 1024 x 768 element spatial image, thereby producing temporally-integrated images having spectrally mixed pixels. HIP goes beyond conventional DLP projectors in that each spatial pixel can have an arbitrary spectrum, not just arbitrary color. As such, the resulting spectral and spatial content of the projected image can simulate realistic scenes that a hyperspectral imager will measure during its use. Also, the spectral radiance of the projected scenes can be measured with a calibrated spectroradiometer, such that the spectral radiance projected into each pixel of the hyperspectral imager can be accurately known. Use of such projected scenes in a controlled laboratory setting would alleviate expensive field testing of instruments, allow better separation of environmental effects from instrument effects, and enable system-level performance testing and validation of hyperspectral imagers as used with analysis algorithms. For example, known mixtures of relevant endmember spectra could be projected into arbitrary spatial pixels in a hyperspectral imager, enabling tests of how well a full system, consisting of the instrument + calibration + analysis algorithm, performs in unmixing (i.e. de-convolving) the spectra in all pixels. We discuss here the performance of a visible prototype HIP. The technology is readily extendable to the ultraviolet and infrared spectral ranges, and the scenes can be static or dynamic.

The effect of lossy image compression on image classification

NASA Technical Reports Server (NTRS)

Paola, Justin D.; Schowengerdt, Robert A.

1995-01-01

We have classified four different images, under various levels of JPEG compression, using the following classification algorithms: minimum-distance, maximum-likelihood, and neural network. The training site accuracy and percent difference from the original classification were tabulated for each image compression level, with maximum-likelihood showing the poorest results. In general, as compression ratio increased, the classification retained its overall appearance, but much of the pixel-to-pixel detail was eliminated. We also examined the effect of compression on spatial pattern detection using a neural network.

Linear dynamic range enhancement in a CMOS imager

NASA Technical Reports Server (NTRS)

Pain, Bedabrata (Inventor)

2008-01-01

A CMOS imager with increased linear dynamic range but without degradation in noise, responsivity, linearity, fixed-pattern noise, or photometric calibration comprises a linear calibrated dual gain pixel in which the gain is reduced after a pre-defined threshold level by switching in an additional capacitance. The pixel may include a novel on-pixel latch circuit that is used to switch in the additional capacitance.

Small target detection using bilateral filter and temporal cross product in infrared images

NASA Astrophysics Data System (ADS)

Bae, Tae-Wuk

2011-09-01

We introduce a spatial and temporal target detection method using spatial bilateral filter (BF) and temporal cross product (TCP) of temporal pixels in infrared (IR) image sequences. At first, the TCP is presented to extract the characteristics of temporal pixels by using temporal profile in respective spatial coordinates of pixels. The TCP represents the cross product values by the gray level distance vector of a current temporal pixel and the adjacent temporal pixel, as well as the horizontal distance vector of the current temporal pixel and a temporal pixel corresponding to potential target center. The summation of TCP values of temporal pixels in spatial coordinates makes the temporal target image (TTI), which represents the temporal target information of temporal pixels in spatial coordinates. And then the proposed BF filter is used to extract the spatial target information. In order to predict background without targets, the proposed BF filter uses standard deviations obtained by an exponential mapping of the TCP value corresponding to the coordinate of a pixel processed spatially. The spatial target image (STI) is made by subtracting the predicted image from the original image. Thus, the spatial and temporal target image (STTI) is achieved by multiplying the STI and the TTI, and then targets finally are detected in STTI. In experimental result, the receiver operating characteristics (ROC) curves were computed experimentally to compare the objective performance. From the results, the proposed algorithm shows better discrimination of target and clutters and lower false alarm rates than the existing target detection methods.

Quantitative evaluation of the accuracy and variance of individual pixels in a scientific CMOS (sCMOS) camera for computational imaging

NASA Astrophysics Data System (ADS)

Watanabe, Shigeo; Takahashi, Teruo; Bennett, Keith

2017-02-01

The"scientific" CMOS (sCMOS) camera architecture fundamentally differs from CCD and EMCCD cameras. In digital CCD and EMCCD cameras, conversion from charge to the digital output is generally through a single electronic chain, and the read noise and the conversion factor from photoelectrons to digital outputs are highly uniform for all pixels, although quantum efficiency may spatially vary. In CMOS cameras, the charge to voltage conversion is separate for each pixel and each column has independent amplifiers and analog-to-digital converters, in addition to possible pixel-to-pixel variation in quantum efficiency. The "raw" output from the CMOS image sensor includes pixel-to-pixel variability in the read noise, electronic gain, offset and dark current. Scientific camera manufacturers digitally compensate the raw signal from the CMOS image sensors to provide usable images. Statistical noise in images, unless properly modeled, can introduce errors in methods such as fluctuation correlation spectroscopy or computational imaging, for example, localization microscopy using maximum likelihood estimation. We measured the distributions and spatial maps of individual pixel offset, dark current, read noise, linearity, photoresponse non-uniformity and variance distributions of individual pixels for standard, off-the-shelf Hamamatsu ORCA-Flash4.0 V3 sCMOS cameras using highly uniform and controlled illumination conditions, from dark conditions to multiple low light levels between 20 to 1,000 photons / pixel per frame to higher light conditions. We further show that using pixel variance for flat field correction leads to errors in cameras with good factory calibration.

Wavelet imaging cleaning method for atmospheric Cherenkov telescopes

NASA Astrophysics Data System (ADS)

Lessard, R. W.; Cayón, L.; Sembroski, G. H.; Gaidos, J. A.

2002-07-01

We present a new method of image cleaning for imaging atmospheric Cherenkov telescopes. The method is based on the utilization of wavelets to identify noise pixels in images of gamma-ray and hadronic induced air showers. This method selects more signal pixels with Cherenkov photons than traditional image processing techniques. In addition, the method is equally efficient at rejecting pixels with noise alone. The inclusion of more signal pixels in an image of an air shower allows for a more accurate reconstruction, especially at lower gamma-ray energies that produce low levels of light. We present the results of Monte Carlo simulations of gamma-ray and hadronic air showers which show improved angular resolution using this cleaning procedure. Data from the Whipple Observatory's 10-m telescope are utilized to show the efficacy of the method for extracting a gamma-ray signal from the background of hadronic generated images.

Pixel-based meshfree modelling of skeletal muscles.

PubMed

Chen, Jiun-Shyan; Basava, Ramya Rao; Zhang, Yantao; Csapo, Robert; Malis, Vadim; Sinha, Usha; Hodgson, John; Sinha, Shantanu

2016-01-01

This paper introduces the meshfree Reproducing Kernel Particle Method (RKPM) for 3D image-based modeling of skeletal muscles. This approach allows for construction of simulation model based on pixel data obtained from medical images. The material properties and muscle fiber direction obtained from Diffusion Tensor Imaging (DTI) are input at each pixel point. The reproducing kernel (RK) approximation allows a representation of material heterogeneity with smooth transition. A multiphase multichannel level set based segmentation framework is adopted for individual muscle segmentation using Magnetic Resonance Images (MRI) and DTI. The application of the proposed methods for modeling the human lower leg is demonstrated.

Salt-and-pepper noise removal using modified mean filter and total variation minimization

NASA Astrophysics Data System (ADS)

Aghajarian, Mickael; McInroy, John E.; Wright, Cameron H. G.

2018-01-01

The search for effective noise removal algorithms is still a real challenge in the field of image processing. An efficient image denoising method is proposed for images that are corrupted by salt-and-pepper noise. Salt-and-pepper noise takes either the minimum or maximum intensity, so the proposed method restores the image by processing the pixels whose values are either 0 or 255 (assuming an 8-bit/pixel image). For low levels of noise corruption (less than or equal to 50% noise density), the method employs the modified mean filter (MMF), while for heavy noise corruption, noisy pixels values are replaced by the weighted average of the MMF and the total variation of corrupted pixels, which is minimized using convex optimization. Two fuzzy systems are used to determine the weights for taking average. To evaluate the performance of the algorithm, several test images with different noise levels are restored, and the results are quantitatively measured by peak signal-to-noise ratio and mean absolute error. The results show that the proposed scheme gives considerable noise suppression up to a noise density of 90%, while almost completely maintaining edges and fine details of the original image.

A design of optical modulation system with pixel-level modulation accuracy

NASA Astrophysics Data System (ADS)

Zheng, Shiwei; Qu, Xinghua; Feng, Wei; Liang, Baoqiu

2018-01-01

Vision measurement has been widely used in the field of dimensional measurement and surface metrology. However, traditional methods of vision measurement have many limits such as low dynamic range and poor reconfigurability. The optical modulation system before image formation has the advantage of high dynamic range, high accuracy and more flexibility, and the modulation accuracy is the key parameter which determines the accuracy and effectiveness of optical modulation system. In this paper, an optical modulation system with pixel level accuracy is designed and built based on multi-points reflective imaging theory and digital micromirror device (DMD). The system consisted of digital micromirror device, CCD camera and lens. Firstly we achieved accurate pixel-to-pixel correspondence between the DMD mirrors and the CCD pixels by moire fringe and an image processing of sampling and interpolation. Then we built three coordinate systems and calculated the mathematic relationship between the coordinate of digital micro-mirror and CCD pixels using a checkerboard pattern. A verification experiment proves that the correspondence error is less than 0.5 pixel. The results show that the modulation accuracy of system meets the requirements of modulation. Furthermore, the high reflecting edge of a metal circular piece can be detected using the system, which proves the effectiveness of the optical modulation system.

Self-amplified CMOS image sensor using a current-mode readout circuit

NASA Astrophysics Data System (ADS)

Santos, Patrick M.; de Lima Monteiro, Davies W.; Pittet, Patrick

2014-05-01

The feature size of the CMOS processes decreased during the past few years and problems such as reduced dynamic range have become more significant in voltage-mode pixels, even though the integration of more functionality inside the pixel has become easier. This work makes a contribution on both sides: the possibility of a high signal excursion range using current-mode circuits together with functionality addition by making signal amplification inside the pixel. The classic 3T pixel architecture was rebuild with small modifications to integrate a transconductance amplifier providing a current as an output. The matrix with these new pixels will operate as a whole large transistor outsourcing an amplified current that will be used for signal processing. This current is controlled by the intensity of the light received by the matrix, modulated pixel by pixel. The output current can be controlled by the biasing circuits to achieve a very large range of output signal levels. It can also be controlled with the matrix size and this permits a very high degree of freedom on the signal level, observing the current densities inside the integrated circuit. In addition, the matrix can operate at very small integration times. Its applications would be those in which fast imaging processing, high signal amplification are required and low resolution is not a major problem, such as UV image sensors. Simulation results will be presented to support: operation, control, design, signal excursion levels and linearity for a matrix of pixels that was conceived using this new concept of sensor.

Active-Pixel Image Sensor With Analog-To-Digital Converters

NASA Technical Reports Server (NTRS)

Fossum, Eric R.; Mendis, Sunetra K.; Pain, Bedabrata; Nixon, Robert H.

1995-01-01

Proposed single-chip integrated-circuit image sensor contains 128 x 128 array of active pixel sensors at 50-micrometer pitch. Output terminals of all pixels in each given column connected to analog-to-digital (A/D) converter located at bottom of column. Pixels scanned in semiparallel fashion, one row at time; during time allocated to scanning row, outputs of all active pixel sensors in row fed to respective A/D converters. Design of chip based on complementary metal oxide semiconductor (CMOS) technology, and individual circuit elements fabricated according to 2-micrometer CMOS design rules. Active pixel sensors designed to operate at video rate of 30 frames/second, even at low light levels. A/D scheme based on first-order Sigma-Delta modulation.

Fundamental performance differences of CMOS and CCD imagers: part V

NASA Astrophysics Data System (ADS)

Janesick, James R.; Elliott, Tom; Andrews, James; Tower, John; Pinter, Jeff

2013-02-01

Previous papers delivered over the last decade have documented developmental progress made on large pixel scientific CMOS imagers that match or surpass CCD performance. New data and discussions presented in this paper include: 1) a new buried channel CCD fabricated on a CMOS process line, 2) new data products generated by high performance custom scientific CMOS 4T/5T/6T PPD pixel imagers, 3) ultimate CTE and speed limits for large pixel CMOS imagers, 4) fabrication and test results of a flight 4k x 4k CMOS imager for NRL's SoloHi Solar Orbiter Mission, 5) a progress report on ultra large stitched Mk x Nk CMOS imager, 6) data generated by on-chip sub-electron CDS signal chain circuitry used in our imagers, 7) CMOS and CMOSCCD proton and electron radiation damage data for dose levels up to 10 Mrd, 8) discussions and data for a new class of PMOS pixel CMOS imagers and 9) future CMOS development work planned.

Musculoskeletal imaging with a prototype photon-counting detector.

PubMed

Gruber, M; Homolka, P; Chmeissani, M; Uffmann, M; Pretterklieber, M; Kainberger, F

2012-01-01

To test a digital imaging X-ray device based on the direct capture of X-ray photons with pixel detectors, which are coupled with photon-counting readout electronics. The chip consists of a matrix of 256 × 256 pixels with a pixel pitch of 55 μm. A monolithic image of 11.2 cm × 7 cm was obtained by the consecutive displacement approach. Images of embalmed anatomical specimens of eight human hands were obtained at four different dose levels (skin dose 2.4, 6, 12, 25 μGy) with the new detector, as well as with a flat-panel detector. The overall rating scores for the evaluated anatomical regions ranged from 5.23 at the lowest dose level, 6.32 at approximately 6 μGy, 6.70 at 12 μGy, to 6.99 at the highest dose level with the photon-counting system. The corresponding rating scores for the flat-panel detector were 3.84, 5.39, 6.64, and 7.34. When images obtained at the same dose were compared, the new system outperformed the conventional DR system at the two lowest dose levels. At the higher dose levels, there were no significant differences between the two systems. The photon-counting detector has great potential to obtain musculoskeletal images of excellent quality at very low dose levels.

Image encryption using a synchronous permutation-diffusion technique

NASA Astrophysics Data System (ADS)

Enayatifar, Rasul; Abdullah, Abdul Hanan; Isnin, Ismail Fauzi; Altameem, Ayman; Lee, Malrey

2017-03-01

In the past decade, the interest on digital images security has been increased among scientists. A synchronous permutation and diffusion technique is designed in order to protect gray-level image content while sending it through internet. To implement the proposed method, two-dimensional plain-image is converted to one dimension. Afterward, in order to reduce the sending process time, permutation and diffusion steps for any pixel are performed in the same time. The permutation step uses chaotic map and deoxyribonucleic acid (DNA) to permute a pixel, while diffusion employs DNA sequence and DNA operator to encrypt the pixel. Experimental results and extensive security analyses have been conducted to demonstrate the feasibility and validity of this proposed image encryption method.

Model Development and Testing for THEMIS Controlled Mars Mosaics

NASA Technical Reports Server (NTRS)

Archinal, B. A.; Sides, S.; Weller, L.; Cushing, G.; Titus, T.; Kirk, R. L.; Soderblom, L. A.; Duxbury, T. C.

2005-01-01

As part of our work [1] to develop techniques and procedures to create regional and eventually global THEMIS mosaics of Mars, we are developing algorithms and software to photogrammetrically control THEMIS IR line scanner camera images. We have found from comparison of a limited number of images to MOLA digital image models (DIMs) [2] that the a priori geometry information (i.e. SPICE [3]) for THEMIS images generally allows their relative positions to be specified at the several pixel level (e.g. approx.5 to 13 pixels). However a need for controlled solutions to improve this geometry to the sub-pixel level still exists. Only with such solutions can seamless mosaics be obtained and likely distortion from spacecraft motion during image collection removed at such levels. Past experience has shown clearly that such mosaics are in heavy demand by users for operational and scientific use, and that they are needed over large areas or globally (as opposed to being available only on a limited basis via labor intensive custom mapping projects). Uses include spacecraft navigation, landing site planning and mapping, registration of multiple data types and image sets, registration of multispectral images, registration of images with topographic information, recovery of thermal properties, change detection searches, etc.

Connecting Swath Satellite Data With Imagery in Mapping Applications

NASA Astrophysics Data System (ADS)

Thompson, C. K.; Hall, J. R.; Penteado, P. F.; Roberts, J. T.; Zhou, A. Y.

2016-12-01

Visualizations of gridded science data products (referred to as Level 3 or Level 4) typically provide a straightforward correlation between image pixels and the source science data. This direct relationship allows users to make initial inferences based on imagery values, facilitating additional operations on the underlying data values, such as data subsetting and analysis. However, that same pixel-to-data relationship for ungridded science data products (referred to as Level 2) is significantly more challenging. These products, also referred to as "swath products", are in orbital "instrument space" and raster visualization pixels do not directly correlate to science data values. Interpolation algorithms are often employed during the gridding or projection of a science dataset prior to image generation, introducing intermediary values that separate the image from the source data values. NASA's Global Imagery Browse Services (GIBS) is researching techniques for efficiently serving "image-ready" data allowing client-side dynamic visualization and analysis capabilities. This presentation will cover some GIBS prototyping work designed to maintain connectivity between Level 2 swath data and its corresponding raster visualizations. Specifically, we discuss the DAta-to-Image-SYstem (DAISY), an indexing approach for Level 2 swath data, and the mechanisms whereby a client may dynamically visualize the data in raster form.

Digital micromirror device camera with per-pixel coded exposure for high dynamic range imaging.

PubMed

Feng, Wei; Zhang, Fumin; Wang, Weijing; Xing, Wei; Qu, Xinghua

2017-05-01

In this paper, we overcome the limited dynamic range of the conventional digital camera, and propose a method of realizing high dynamic range imaging (HDRI) from a novel programmable imaging system called a digital micromirror device (DMD) camera. The unique feature of the proposed new method is that the spatial and temporal information of incident light in our DMD camera can be flexibly modulated, and it enables the camera pixels always to have reasonable exposure intensity by DMD pixel-level modulation. More importantly, it allows different light intensity control algorithms used in our programmable imaging system to achieve HDRI. We implement the optical system prototype, analyze the theory of per-pixel coded exposure for HDRI, and put forward an adaptive light intensity control algorithm to effectively modulate the different light intensity to recover high dynamic range images. Via experiments, we demonstrate the effectiveness of our method and implement the HDRI on different objects.

Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

NASA Astrophysics Data System (ADS)

Li, X. L.; Zhao, Q. H.; Li, Y.

2017-09-01

Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

A database system to support image algorithm evaluation

NASA Technical Reports Server (NTRS)

Lien, Y. E.

1977-01-01

The design is given of an interactive image database system IMDB, which allows the user to create, retrieve, store, display, and manipulate images through the facility of a high-level, interactive image query (IQ) language. The query language IQ permits the user to define false color functions, pixel value transformations, overlay functions, zoom functions, and windows. The user manipulates the images through generic functions. The user can direct images to display devices for visual and qualitative analysis. Image histograms and pixel value distributions can also be computed to obtain a quantitative analysis of images.

An investigation of signal performance enhancements achieved through innovative pixel design across several generations of indirect detection, active matrix, flat-panel arrays

PubMed Central

Antonuk, Larry E.; Zhao, Qihua; El-Mohri, Youcef; Du, Hong; Wang, Yi; Street, Robert A.; Ho, Jackson; Weisfield, Richard; Yao, William

2009-01-01

Active matrix flat-panel imager (AMFPI) technology is being employed for an increasing variety of imaging applications. An important element in the adoption of this technology has been significant ongoing improvements in optical signal collection achieved through innovations in indirect detection array pixel design. Such improvements have a particularly beneficial effect on performance in applications involving low exposures and∕or high spatial frequencies, where detective quantum efficiency is strongly reduced due to the relatively high level of additive electronic noise compared to signal levels of AMFPI devices. In this article, an examination of various signal properties, as determined through measurements and calculations related to novel array designs, is reported in the context of the evolution of AMFPI pixel design. For these studies, dark, optical, and radiation signal measurements were performed on prototype imagers incorporating a variety of increasingly sophisticated array designs, with pixel pitches ranging from 75 to 127 μm. For each design, detailed measurements of fundamental pixel-level properties conducted under radiographic and fluoroscopic operating conditions are reported and the results are compared. A series of 127 μm pitch arrays employing discrete photodiodes culminated in a novel design providing an optical fill factor of ∼80% (thereby assuring improved x-ray sensitivity), and demonstrating low dark current, very low charge trapping and charge release, and a large range of linear signal response. In two of the designs having 75 and 90 μm pitches, a novel continuous photodiode structure was found to provide fill factors that approach the theoretical maximum of 100%. Both sets of novel designs achieved large fill factors by employing architectures in which some, or all of the photodiode structure was elevated above the plane of the pixel addressing transistor. Generally, enhancement of the fill factor in either discrete or continuous photodiode arrays was observed to result in no degradation in MTF due to charge sharing between pixels. While the continuous designs exhibited relatively high levels of charge trapping and release, as well as shorter ranges of linearity, it is possible that these behaviors can be addressed through further refinements to pixel design. Both the continuous and the most recent discrete photodiode designs accommodate more sophisticated pixel circuitry than is present on conventional AMFPIs – such as a pixel clamp circuit, which is demonstrated to limit signal saturation under conditions corresponding to high exposures. It is anticipated that photodiode structures such as the ones reported in this study will enable the development of even more complex pixel circuitry, such as pixel-level amplifiers, that will lead to further significant improvements in imager performance. PMID:19673228

Video Image Tracking Engine

NASA Technical Reports Server (NTRS)

Howard, Richard T. (Inventor); Bryan, ThomasC. (Inventor); Book, Michael L. (Inventor)

2004-01-01

A method and system for processing an image including capturing an image and storing the image as image pixel data. Each image pixel datum is stored in a respective memory location having a corresponding address. Threshold pixel data is selected from the image pixel data and linear spot segments are identified from the threshold pixel data selected.. Ihe positions of only a first pixel and a last pixel for each linear segment are saved. Movement of one or more objects are tracked by comparing the positions of fust and last pixels of a linear segment present in the captured image with respective first and last pixel positions in subsequent captured images. Alternatively, additional data for each linear data segment is saved such as sum of pixels and the weighted sum of pixels i.e., each threshold pixel value is multiplied by that pixel's x-location).

An enhanced fast scanning algorithm for image segmentation

NASA Astrophysics Data System (ADS)

Ismael, Ahmed Naser; Yusof, Yuhanis binti

2015-12-01

Segmentation is an essential and important process that separates an image into regions that have similar characteristics or features. This will transform the image for a better image analysis and evaluation. An important benefit of segmentation is the identification of region of interest in a particular image. Various algorithms have been proposed for image segmentation and this includes the Fast Scanning algorithm which has been employed on food, sport and medical images. It scans all pixels in the image and cluster each pixel according to the upper and left neighbor pixels. The clustering process in Fast Scanning algorithm is performed by merging pixels with similar neighbor based on an identified threshold. Such an approach will lead to a weak reliability and shape matching of the produced segments. This paper proposes an adaptive threshold function to be used in the clustering process of the Fast Scanning algorithm. This function used the gray'value in the image's pixels and variance Also, the level of the image that is more the threshold are converted into intensity values between 0 and 1, and other values are converted into intensity values zero. The proposed enhanced Fast Scanning algorithm is realized on images of the public and private transportation in Iraq. Evaluation is later made by comparing the produced images of proposed algorithm and the standard Fast Scanning algorithm. The results showed that proposed algorithm is faster in terms the time from standard fast scanning.

Video image stabilization and registration--plus

NASA Technical Reports Server (NTRS)

Hathaway, David H. (Inventor)

2009-01-01

A method of stabilizing a video image displayed in multiple video fields of a video sequence includes the steps of: subdividing a selected area of a first video field into nested pixel blocks; determining horizontal and vertical translation of each of the pixel blocks in each of the pixel block subdivision levels from the first video field to a second video field; and determining translation of the image from the first video field to the second video field by determining a change in magnification of the image from the first video field to the second video field in each of horizontal and vertical directions, and determining shear of the image from the first video field to the second video field in each of the horizontal and vertical directions.

Analysis and Enhancement of Low-Light-Level Performance of Photodiode-Type CMOS Active Pixel Images Operated with Sub-Threshold Reset

NASA Technical Reports Server (NTRS)

Pain, Bedabrata; Yang, Guang; Ortiz, Monico; Wrigley, Christopher; Hancock, Bruce; Cunningham, Thomas

2000-01-01

Noise in photodiode-type CMOS active pixel sensors (APS) is primarily due to the reset (kTC) noise at the sense node, since it is difficult to implement in-pixel correlated double sampling for a 2-D array. Signal integrated on the photodiode sense node (SENSE) is calculated by measuring difference between the voltage on the column bus (COL) - before and after the reset (RST) is pulsed. Lower than kTC noise can be achieved with photodiode-type pixels by employing "softreset" technique. Soft-reset refers to resetting with both drain and gate of the n-channel reset transistor kept at the same potential, causing the sense node to be reset using sub-threshold MOSFET current. However, lowering of noise is achieved only at the expense higher image lag and low-light-level non-linearity. In this paper, we present an analysis to explain the noise behavior, show evidence of degraded performance under low-light levels, and describe new pixels that eliminate non-linearity and lag without compromising noise.

A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

NASA Astrophysics Data System (ADS)

Tatar, Nurollah; Saadatseresht, Mohammad; Arefi, Hossein; Hadavand, Ahmad

2018-06-01

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C4 index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.

High dynamic range pixel architecture for advanced diagnostic medical x-ray imaging applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Izadi, Mohammad Hadi; Karim, Karim S.

2006-05-15

The most widely used architecture in large-area amorphous silicon (a-Si) flat panel imagers is a passive pixel sensor (PPS), which consists of a detector and a readout switch. While the PPS has the advantage of being compact and amenable toward high-resolution imaging, small PPS output signals are swamped by external column charge amplifier and data line thermal noise, which reduce the minimum readable sensor input signal. In contrast to PPS circuits, on-pixel amplifiers in a-Si technology reduce readout noise to levels that can meet even the stringent requirements for low noise digital x-ray fluoroscopy (<1000 noise electrons). However, larger voltagesmore » at the pixel input cause the output of the amplified pixel to become nonlinear thus reducing the dynamic range. We reported a hybrid amplified pixel architecture based on a combination of PPS and amplified pixel designs that, in addition to low noise performance, also resulted in large-signal linearity and consequently higher dynamic range [K. S. Karim et al., Proc. SPIE 5368, 657 (2004)]. The additional benefit in large-signal linearity, however, came at the cost of an additional pixel transistor. We present an amplified pixel design that achieves the goals of low noise performance and large-signal linearity without the need for an additional pixel transistor. Theoretical calculations and simulation results for noise indicate the applicability of the amplified a-Si pixel architecture for high dynamic range, medical x-ray imaging applications that require switching between low exposure, real-time fluoroscopy and high-exposure radiography.« less

Rule-driven defect detection in CT images of hardwood logs

Treesearch

Erol Sarigul; A. Lynn Abbott; Daniel L. Schmoldt

2000-01-01

This paper deals with automated detection and identification of internal defects in hardwood logs using computed tomography (CT) images. We have developed a system that employs artificial neural networks to perform tentative classification of logs on a pixel-by-pixel basis. This approach achieves a high level of classification accuracy for several hardwood species (...

Preliminary investigations of active pixel sensors in Nuclear Medicine imaging

NASA Astrophysics Data System (ADS)

Ott, Robert; Evans, Noel; Evans, Phil; Osmond, J.; Clark, A.; Turchetta, R.

2009-06-01

Three CMOS active pixel sensors have been investigated for their application to Nuclear Medicine imaging. Startracker with 525×525 25 μm square pixels has been coupled via a fibre optic stud to a 2 mm thick segmented CsI(Tl) crystal. Imaging tests were performed using 99mTc sources, which emit 140 keV gamma rays. The system was interfaced to a PC via FPGA-based DAQ and optical link enabling imaging rates of 10 f/s. System noise was measured to be >100e and it was shown that the majority of this noise was fixed pattern in nature. The intrinsic spatial resolution was measured to be ˜80 μm and the system spatial resolution measured with a slit was ˜450 μm. The second sensor, On Pixel Intelligent CMOS (OPIC), had 64×72 40 μm pixels and was used to evaluate noise characteristics and to develop a method of differentiation between fixed pattern and statistical noise. The third sensor, Vanilla, had 520×520 25 μm pixels and a measured system noise of ˜25e. This sensor was coupled directly to the segmented phosphor. Imaging results show that even at this lower level of noise the signal from 140 keV gamma rays is small as the light from the phosphor is spread over a large number of pixels. Suggestions for the 'ideal' sensor are made.

Digital identification of cartographic control points

NASA Technical Reports Server (NTRS)

Gaskell, R. W.

1988-01-01

Techniques have been developed for the sub-pixel location of control points in satellite images returned by the Voyager spacecraft. The procedure uses digital imaging data in the neighborhood of the point to form a multipicture model of a piece of the surface. Comparison of this model with the digital image in each picture determines the control point locations to about a tenth of a pixel. At this level of precision, previously insignificant effects must be considered, including chromatic aberration, high level imaging distortions, and systematic errors due to navigation uncertainties. Use of these methods in the study of Jupiter's satellite Io has proven very fruitful.

CMOS Active Pixel Sensors for Low Power, Highly Miniaturized Imaging Systems

NASA Technical Reports Server (NTRS)

Fossum, Eric R.

1996-01-01

The complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) technology has been developed over the past three years by NASA at the Jet Propulsion Laboratory, and has reached a level of performance comparable to CCDs with greatly increased functionality but at a very reduced power level.

Image processing on the image with pixel noise bits removed

NASA Astrophysics Data System (ADS)

Chuang, Keh-Shih; Wu, Christine

1992-06-01

Our previous studies used statistical methods to assess the noise level in digital images of various radiological modalities. We separated the pixel data into signal bits and noise bits and demonstrated visually that the removal of the noise bits does not affect the image quality. In this paper we apply image enhancement techniques on noise-bits-removed images and demonstrate that the removal of noise bits has no effect on the image property. The image processing techniques used are gray-level look up table transformation, Sobel edge detector, and 3-D surface display. Preliminary results show no noticeable difference between original image and noise bits removed image using look up table operation and Sobel edge enhancement. There is a slight enhancement of the slicing artifact in the 3-D surface display of the noise bits removed image.

G-Channel Restoration for RWB CFA with Double-Exposed W Channel

PubMed Central

Park, Chulhee; Song, Ki Sun; Kang, Moon Gi

2017-01-01

In this paper, we propose a green (G)-channel restoration for a red–white–blue (RWB) color filter array (CFA) image sensor using the dual sampling technique. By using white (W) pixels instead of G pixels, the RWB CFA provides high-sensitivity imaging and an improved signal-to-noise ratio compared to the Bayer CFA. However, owing to this high sensitivity, the W pixel values become rapidly over-saturated before the red–blue (RB) pixel values reach the appropriate levels. Because the missing G color information included in the W channel cannot be restored with a saturated W, multiple captures with dual sampling are necessary to solve this early W-pixel saturation problem. Each W pixel has a different exposure time when compared to those of the R and B pixels, because the W pixels are double-exposed. Therefore, a RWB-to-RGB color conversion method is required in order to restore the G color information, using a double-exposed W channel. The proposed G-channel restoration algorithm restores G color information from the W channel by considering the energy difference caused by the different exposure times. Using the proposed method, the RGB full-color image can be obtained while maintaining the high-sensitivity characteristic of the W pixels. PMID:28165425

G-Channel Restoration for RWB CFA with Double-Exposed W Channel.

PubMed

Park, Chulhee; Song, Ki Sun; Kang, Moon Gi

2017-02-05

In this paper, we propose a green (G)-channel restoration for a red-white-blue (RWB) color filter array (CFA) image sensor using the dual sampling technique. By using white (W) pixels instead of G pixels, the RWB CFA provides high-sensitivity imaging and an improved signal-to-noise ratio compared to the Bayer CFA. However, owing to this high sensitivity, the W pixel values become rapidly over-saturated before the red-blue (RB) pixel values reach the appropriate levels. Because the missing G color information included in the W channel cannot be restored with a saturated W, multiple captures with dual sampling are necessary to solve this early W-pixel saturation problem. Each W pixel has a different exposure time when compared to those of the R and B pixels, because the W pixels are double-exposed. Therefore, a RWB-to-RGB color conversion method is required in order to restore the G color information, using a double-exposed W channel. The proposed G-channel restoration algorithm restores G color information from the W channel by considering the energy difference caused by the different exposure times. Using the proposed method, the RGB full-color image can be obtained while maintaining the high-sensitivity characteristic of the W pixels.

Estimation bias from using nonlinear Fourier plane correlators for sub-pixel image shift measurement and implications for the binary joint transform correlator

NASA Astrophysics Data System (ADS)

Grycewicz, Thomas J.; Florio, Christopher J.; Franz, Geoffrey A.; Robinson, Ross E.

2007-09-01

When using Fourier plane digital algorithms or an optical correlator to measure the correlation between digital images, interpolation by center-of-mass or quadratic estimation techniques can be used to estimate image displacement to the sub-pixel level. However, this can lead to a bias in the correlation measurement. This bias shifts the sub-pixel output measurement to be closer to the nearest pixel center than the actual location. The paper investigates the bias in the outputs of both digital and optical correlators, and proposes methods to minimize this effect. We use digital studies and optical implementations of the joint transform correlator to demonstrate optical registration with accuracies better than 0.1 pixels. We use both simulations of image shift and movies of a moving target as inputs. We demonstrate bias error for both center-of-mass and quadratic interpolation, and discuss the reasons that this bias is present. Finally, we suggest measures to reduce or eliminate the bias effects. We show that when sub-pixel bias is present, it can be eliminated by modifying the interpolation method. By removing the bias error, we improve registration accuracy by thirty percent.

Method and system for non-linear motion estimation

NASA Technical Reports Server (NTRS)

Lu, Ligang (Inventor)

2011-01-01

A method and system for extrapolating and interpolating a visual signal including determining a first motion vector between a first pixel position in a first image to a second pixel position in a second image, determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image, determining a third motion vector between one of the first pixel position in the first image and the second pixel position in the second image, and the second pixel position in the second image and the third pixel position in the third image using a non-linear model, determining a position of the fourth pixel in a fourth image based upon the third motion vector.

Digital shaded relief image of a carbonate platform (northern Great Bahama Bank): Scenery seen and unseen

NASA Astrophysics Data System (ADS)

Boss, Stephen K.

1996-11-01

A mosaic image of the northern Great Bahama Bank was created from separate gray-scale Landsat images using photo-editing and image analysis software that is commercially available for desktop computers. Measurements of pixel gray levels (relative scale from 0 to 255 referred to as digital number, DN) on the mosaic image were compared to bank-top bathymetry (determined from a network of single-channel, high-resolution seismic profiles), bottom type (coarse sand, sandy mud, barren rock, or reef determined from seismic profiles and diver observations), and vegetative cover (presence and/or absence and relative density of the marine angiosperm Thalassia testudinum determined from diver observations). Results of these analyses indicate that bank-top bathymetry is a primary control on observed pixel DN, bottom type is a secondary control on pixel DN, and vegetative cover is a tertiary influence on pixel DN. Consequently, processing of the gray-scale Landsat mosaic with a directional gradient edge-detection filter generated a physiographic shaded relief image resembling bank-top bathymetric patterns related to submerged physiographic features across the platform. The visibility of submerged karst landforms, Pleistocene eolianite ridges, islands, and possible paleo-drainage patterns created during sea-level lowstands is significantly enhanced on processed images relative to the original mosaic. Bank-margin ooid shoals, platform interior sand bodies, reef edifices, and bidirectional sand waves are features resulting from Holocene carbonate deposition that are also more clearly visible on the new physiographic images. Combined with observational data (single-channel, high-resolution seismic profiles, bottom observations by SCUBA divers, sediment and rock cores) across the northern Great Bahama Bank, these physiographic images facilitate comprehension of areal relations among antecedent platform topography, physical processes, and ensuing depositional patterns during sea-level rise.

Shape and Albedo from Shading (SAfS) for Pixel-Level dem Generation from Monocular Images Constrained by Low-Resolution dem

NASA Astrophysics Data System (ADS)

Wu, Bo; Chung Liu, Wai; Grumpe, Arne; Wöhler, Christian

2016-06-01

Lunar topographic information, e.g., lunar DEM (Digital Elevation Model), is very important for lunar exploration missions and scientific research. Lunar DEMs are typically generated from photogrammetric image processing or laser altimetry, of which photogrammetric methods require multiple stereo images of an area. DEMs generated from these methods are usually achieved by various interpolation techniques, leading to interpolation artifacts in the resulting DEM. On the other hand, photometric shape reconstruction, e.g., SfS (Shape from Shading), extensively studied in the field of Computer Vision has been introduced to pixel-level resolution DEM refinement. SfS methods have the ability to reconstruct pixel-wise terrain details that explain a given image of the terrain. If the terrain and its corresponding pixel-wise albedo were to be estimated simultaneously, this is a SAfS (Shape and Albedo from Shading) problem and it will be under-determined without additional information. Previous works show strong statistical regularities in albedo of natural objects, and this is even more logically valid in the case of lunar surface due to its lower surface albedo complexity than the Earth. In this paper we suggest a method that refines a lower-resolution DEM to pixel-level resolution given a monocular image of the coverage with known light source, at the same time we also estimate the corresponding pixel-wise albedo map. We regulate the behaviour of albedo and shape such that the optimized terrain and albedo are the likely solutions that explain the corresponding image. The parameters in the approach are optimized through a kernel-based relaxation framework to gain computational advantages. In this research we experimentally employ the Lunar-Lambertian model for reflectance modelling; the framework of the algorithm is expected to be independent of a specific reflectance model. Experiments are carried out using the monocular images from Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) (0.5 m spatial resolution), constrained by the SELENE and LRO Elevation Model (SLDEM 2015) of 60 m spatial resolution. The results indicate that local details are largely recovered by the algorithm while low frequency topographic consistency is affected by the low-resolution DEM.

Radiometric calibration and SNR calculation of a SWIR imaging telescope

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yilmaz, Ozgur; Turk, Fethi; Selimoglu, Ozgur

2012-09-06

Radiometric calibration of an imaging telescope is usually made using a uniform illumination sphere in a laboratory. In this study, we used the open-sky images taken during bright day conditions to calibrate our telescope. We found a dark signal offset value and a linear response coefficient value for each pixel by using three different algorithms. Then we applied these coefficients to the taken images, and considerably lowered the image non-uniformity. Calibration can be repeated during the operation of telescope with an object that has better uniformity than open-sky. Also SNR (Signal to Noise Ratio) of each pixel was calculated frommore » the open-sky images using the temporal mean and standard deviations. It is found that SNR is greater than 80 for all pixels even at low light levels.« less

a New Object-Based Framework to Detect Shodows in High-Resolution Satellite Imagery Over Urban Areas

NASA Astrophysics Data System (ADS)

Tatar, N.; Saadatseresht, M.; Arefi, H.; Hadavand, A.

2015-12-01

In this paper a new object-based framework to detect shadow areas in high resolution satellite images is proposed. To produce shadow map in pixel level state of the art supervised machine learning algorithms are employed. Automatic ground truth generation based on Otsu thresholding on shadow and non-shadow indices is used to train the classifiers. It is followed by segmenting the image scene and create image objects. To detect shadow objects, a majority voting on pixel-based shadow detection result is designed. GeoEye-1 multi-spectral image over an urban area in Qom city of Iran is used in the experiments. Results shows the superiority of our proposed method over traditional pixel-based, visually and quantitatively.

Characterization and correction of charge-induced pixel shifts in DECam

DOE PAGES

Gruen, D.; Bernstein, G. M.; Jarvis, M.; ...

2015-05-28

Interaction of charges in CCDs with the already accumulated charge distribution causes both a flux dependence of the point-spread function (an increase of observed size with flux, also known as the brighter/fatter effect) and pixel-to-pixel correlations of the Poissonian noise in flat fields. We describe these effects in the Dark Energy Camera (DECam) with charge dependent shifts of effective pixel borders, i.e. the Antilogus et al. (2014) model, which we fit to measurements of flat-field Poissonian noise correlations. The latter fall off approximately as a power-law r -2.5 with pixel separation r, are isotropic except for an asymmetry in themore » direct neighbors along rows and columns, are stable in time, and are weakly dependent on wavelength. They show variations from chip to chip at the 20% level that correlate with the silicon resistivity. The charge shifts predicted by the model cause biased shape measurements, primarily due to their effect on bright stars, at levels exceeding weak lensing science requirements. We measure the flux dependence of star images and show that the effect can be mitigated by applying the reverse charge shifts at the pixel level during image processing. Differences in stellar size, however, remain significant due to residuals at larger distance from the centroid.« less

Design and implementation of non-linear image processing functions for CMOS image sensor

NASA Astrophysics Data System (ADS)

Musa, Purnawarman; Sudiro, Sunny A.; Wibowo, Eri P.; Harmanto, Suryadi; Paindavoine, Michel

2012-11-01

Today, solid state image sensors are used in many applications like in mobile phones, video surveillance systems, embedded medical imaging and industrial vision systems. These image sensors require the integration in the focal plane (or near the focal plane) of complex image processing algorithms. Such devices must meet the constraints related to the quality of acquired images, speed and performance of embedded processing, as well as low power consumption. To achieve these objectives, low-level analog processing allows extracting the useful information in the scene directly. For example, edge detection step followed by a local maxima extraction will facilitate the high-level processing like objects pattern recognition in a visual scene. Our goal was to design an intelligent image sensor prototype achieving high-speed image acquisition and non-linear image processing (like local minima and maxima calculations). For this purpose, we present in this article the design and test of a 64×64 pixels image sensor built in a standard CMOS Technology 0.35 μm including non-linear image processing. The architecture of our sensor, named nLiRIC (non-Linear Rapid Image Capture), is based on the implementation of an analog Minima/Maxima Unit. This MMU calculates the minimum and maximum values (non-linear functions), in real time, in a 2×2 pixels neighbourhood. Each MMU needs 52 transistors and the pitch of one pixel is 40×40 mu m. The total area of the 64×64 pixels is 12.5mm2. Our tests have shown the validity of the main functions of our new image sensor like fast image acquisition (10K frames per second), minima/maxima calculations in less then one ms.

Event-driven charge-coupled device design and applications therefor

NASA Technical Reports Server (NTRS)

Doty, John P. (Inventor); Ricker, Jr., George R. (Inventor); Burke, Barry E. (Inventor); Prigozhin, Gregory Y. (Inventor)

2005-01-01

An event-driven X-ray CCD imager device uses a floating-gate amplifier or other non-destructive readout device to non-destructively sense a charge level in a charge packet associated with a pixel. The output of the floating-gate amplifier is used to identify each pixel that has a charge level above a predetermined threshold. If the charge level is above a predetermined threshold the charge in the triggering charge packet and in the charge packets from neighboring pixels need to be measured accurately. A charge delay register is included in the event-driven X-ray CCD imager device to enable recovery of the charge packets from neighboring pixels for accurate measurement. When a charge packet reaches the end of the charge delay register, control logic either dumps the charge packet, or steers the charge packet to a charge FIFO to preserve it if the charge packet is determined to be a packet that needs accurate measurement. A floating-diffusion amplifier or other low-noise output stage device, which converts charge level to a voltage level with high precision, provides final measurement of the charge packets. The voltage level is eventually digitized by a high linearity ADC.

A Nipkow disk integrated with Fresnel lenses for terahertz single pixel imaging.

PubMed

Li, Chong; Grant, James; Wang, Jue; Cumming, David R S

2013-10-21

We present a novel Nipkow disk design for terahertz (THz) single pixel imaging applications. A 100 mm high resistivity (ρ≈3k-10k Ω·cm) silicon wafer was used for the disk on which a spiral array of twelve 16-level binary Fresnel lenses were fabricated using photolithography and a dry-etch process. The implementation of Fresnel lenses on the Nipkow disk increases the THz signal transmission compared to the conventional pinhole-based Nipkow disk by more than 12 times thus a THz source with lower power or a THz detector with lower detectivity can be used. Due to the focusing capability of the lenses, a pixel resolution better than 0.5 mm is in principle achievable. To demonstrate the concept, a single pixel imaging system operating at 2.52 THz is described.

A unified tensor level set for image segmentation.

PubMed

Wang, Bin; Gao, Xinbo; Tao, Dacheng; Li, Xuelong

2010-06-01

This paper presents a new region-based unified tensor level set model for image segmentation. This model introduces a three-order tensor to comprehensively depict features of pixels, e.g., gray value and the local geometrical features, such as orientation and gradient, and then, by defining a weighted distance, we generalized the representative region-based level set method from scalar to tensor. The proposed model has four main advantages compared with the traditional representative method as follows. First, involving the Gaussian filter bank, the model is robust against noise, particularly the salt- and pepper-type noise. Second, considering the local geometrical features, e.g., orientation and gradient, the model pays more attention to boundaries and makes the evolving curve stop more easily at the boundary location. Third, due to the unified tensor pixel representation representing the pixels, the model segments images more accurately and naturally. Fourth, based on a weighted distance definition, the model possesses the capacity to cope with data varying from scalar to vector, then to high-order tensor. We apply the proposed method to synthetic, medical, and natural images, and the result suggests that the proposed method is superior to the available representative region-based level set method.

Foreign object detection and removal to improve automated analysis of chest radiographs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogeweg, Laurens; Sanchez, Clara I.; Melendez, Jaime

2013-07-15

Purpose: Chest radiographs commonly contain projections of foreign objects, such as buttons, brassier clips, jewellery, or pacemakers and wires. The presence of these structures can substantially affect the output of computer analysis of these images. An automated method is presented to detect, segment, and remove foreign objects from chest radiographs.Methods: Detection is performed using supervised pixel classification with a kNN classifier, resulting in a probability estimate per pixel to belong to a projected foreign object. Segmentation is performed by grouping and post-processing pixels with a probability above a certain threshold. Next, the objects are replaced by texture inpainting.Results: The methodmore » is evaluated in experiments on 257 chest radiographs. The detection at pixel level is evaluated with receiver operating characteristic analysis on pixels within the unobscured lung fields and an A{sub z} value of 0.949 is achieved. Free response operator characteristic analysis is performed at the object level, and 95.6% of objects are detected with on average 0.25 false positive detections per image. To investigate the effect of removing the detected objects through inpainting, a texture analysis system for tuberculosis detection is applied to images with and without pathology and with and without foreign object removal. Unprocessed, the texture analysis abnormality score of normal images with foreign objects is comparable to those with pathology. After removing foreign objects, the texture score of normal images with and without foreign objects is similar, while abnormal images, whether they contain foreign objects or not, achieve on average higher scores.Conclusions: The authors conclude that removal of foreign objects from chest radiographs is feasible and beneficial for automated image analysis.« less

Ghost detection and removal based on super-pixel grouping in exposure fusion

NASA Astrophysics Data System (ADS)

Jiang, Shenyu; Xu, Zhihai; Li, Qi; Chen, Yueting; Feng, Huajun

2014-09-01

A novel multi-exposure images fusion method for dynamic scenes is proposed. The commonly used techniques for high dynamic range (HDR) imaging are based on the combination of multiple differently exposed images of the same scene. The drawback of these methods is that ghosting artifacts will be introduced into the final HDR image if the scene is not static. In this paper, a super-pixel grouping based method is proposed to detect the ghost in the image sequences. We introduce the zero mean normalized cross correlation (ZNCC) as a measure of similarity between a given exposure image and the reference. The calculation of ZNCC is implemented in super-pixel level, and the super-pixels which have low correlation with the reference are excluded by adjusting the weight maps for fusion. Without any prior information on camera response function or exposure settings, the proposed method generates low dynamic range (LDR) images which can be shown on conventional display devices directly with details preserving and ghost effects reduced. Experimental results show that the proposed method generates high quality images which have less ghost artifacts and provide a better visual quality than previous approaches.

Decoding brain responses to pixelized images in the primary visual cortex: implications for visual cortical prostheses

PubMed Central

Guo, Bing-bing; Zheng, Xiao-lin; Lu, Zhen-gang; Wang, Xing; Yin, Zheng-qin; Hou, Wen-sheng; Meng, Ming

2015-01-01

Visual cortical prostheses have the potential to restore partial vision. Still limited by the low-resolution visual percepts provided by visual cortical prostheses, implant wearers can currently only “see” pixelized images, and how to obtain the specific brain responses to different pixelized images in the primary visual cortex (the implant area) is still unknown. We conducted a functional magnetic resonance imaging experiment on normal human participants to investigate the brain activation patterns in response to 18 different pixelized images. There were 100 voxels in the brain activation pattern that were selected from the primary visual cortex, and voxel size was 4 mm × 4 mm × 4 mm. Multi-voxel pattern analysis was used to test if these 18 different brain activation patterns were specific. We chose a Linear Support Vector Machine (LSVM) as the classifier in this study. The results showed that the classification accuracies of different brain activation patterns were significantly above chance level, which suggests that the classifier can successfully distinguish the brain activation patterns. Our results suggest that the specific brain activation patterns to different pixelized images can be obtained in the primary visual cortex using a 4 mm × 4 mm × 4 mm voxel size and a 100-voxel pattern. PMID:26692860

Reflectance Prediction Modelling for Residual-Based Hyperspectral Image Coding

PubMed Central

Xiao, Rui; Gao, Junbin; Bossomaier, Terry

2016-01-01

A Hyperspectral (HS) image provides observational powers beyond human vision capability but represents more than 100 times the data compared to a traditional image. To transmit and store the huge volume of an HS image, we argue that a fundamental shift is required from the existing “original pixel intensity”-based coding approaches using traditional image coders (e.g., JPEG2000) to the “residual”-based approaches using a video coder for better compression performance. A modified video coder is required to exploit spatial-spectral redundancy using pixel-level reflectance modelling due to the different characteristics of HS images in their spectral and shape domain of panchromatic imagery compared to traditional videos. In this paper a novel coding framework using Reflectance Prediction Modelling (RPM) in the latest video coding standard High Efficiency Video Coding (HEVC) for HS images is proposed. An HS image presents a wealth of data where every pixel is considered a vector for different spectral bands. By quantitative comparison and analysis of pixel vector distribution along spectral bands, we conclude that modelling can predict the distribution and correlation of the pixel vectors for different bands. To exploit distribution of the known pixel vector, we estimate a predicted current spectral band from the previous bands using Gaussian mixture-based modelling. The predicted band is used as the additional reference band together with the immediate previous band when we apply the HEVC. Every spectral band of an HS image is treated like it is an individual frame of a video. In this paper, we compare the proposed method with mainstream encoders. The experimental results are fully justified by three types of HS dataset with different wavelength ranges. The proposed method outperforms the existing mainstream HS encoders in terms of rate-distortion performance of HS image compression. PMID:27695102

Varying ultrasound power level to distinguish surgical instruments and tissue.

PubMed

Ren, Hongliang; Anuraj, Banani; Dupont, Pierre E

2018-03-01

We investigate a new framework of surgical instrument detection based on power-varying ultrasound images with simple and efficient pixel-wise intensity processing. Without using complicated feature extraction methods, we identified the instrument with an estimated optimal power level and by comparing pixel values of varying transducer power level images. The proposed framework exploits the physics of ultrasound imaging system by varying the transducer power level to effectively distinguish metallic surgical instruments from tissue. This power-varying image-guidance is motivated from our observations that ultrasound imaging at different power levels exhibit different contrast enhancement capabilities between tissue and instruments in ultrasound-guided robotic beating-heart surgery. Using lower transducer power levels (ranging from 40 to 75% of the rated lowest ultrasound power levels of the two tested ultrasound scanners) can effectively suppress the strong imaging artifacts from metallic instruments and thus, can be utilized together with the images from normal transducer power levels to enhance the separability between instrument and tissue, improving intraoperative instrument tracking accuracy from the acquired noisy ultrasound volumetric images. We performed experiments in phantoms and ex vivo hearts in water tank environments. The proposed multi-level power-varying ultrasound imaging approach can identify robotic instruments of high acoustic impedance from low-signal-to-noise-ratio ultrasound images by power adjustments.

PixelLearn

NASA Technical Reports Server (NTRS)

Mazzoni, Dominic; Wagstaff, Kiri; Bornstein, Benjamin; Tang, Nghia; Roden, Joseph

2006-01-01

PixelLearn is an integrated user-interface computer program for classifying pixels in scientific images. Heretofore, training a machine-learning algorithm to classify pixels in images has been tedious and difficult. PixelLearn provides a graphical user interface that makes it faster and more intuitive, leading to more interactive exploration of image data sets. PixelLearn also provides image-enhancement controls to make it easier to see subtle details in images. PixelLearn opens images or sets of images in a variety of common scientific file formats and enables the user to interact with several supervised or unsupervised machine-learning pixel-classifying algorithms while the user continues to browse through the images. The machinelearning algorithms in PixelLearn use advanced clustering and classification methods that enable accuracy much higher than is achievable by most other software previously available for this purpose. PixelLearn is written in portable C++ and runs natively on computers running Linux, Windows, or Mac OS X.

An RBF-based compression method for image-based relighting.

PubMed

Leung, Chi-Sing; Wong, Tien-Tsin; Lam, Ping-Man; Choy, Kwok-Hung

2006-04-01

In image-based relighting, a pixel is associated with a number of sampled radiance values. This paper presents a two-level compression method. In the first level, the plenoptic property of a pixel is approximated by a spherical radial basis function (SRBF) network. That means that the spherical plenoptic function of each pixel is represented by a number of SRBF weights. In the second level, we apply a wavelet-based method to compress these SRBF weights. To reduce the visual artifact due to quantization noise, we develop a constrained method for estimating the SRBF weights. Our proposed approach is superior to JPEG, JPEG2000, and MPEG. Compared with the spherical harmonics approach, our approach has a lower complexity, while the visual quality is comparable. The real-time rendering method for our SRBF representation is also discussed.

Design of a Low-Light-Level Image Sensor with On-Chip Sigma-Delta Analog-to- Digital Conversion

NASA Technical Reports Server (NTRS)

Mendis, Sunetra K.; Pain, Bedabrata; Nixon, Robert H.; Fossum, Eric R.

1993-01-01

The design and projected performance of a low-light-level active-pixel-sensor (APS) chip with semi-parallel analog-to-digital (A/D) conversion is presented. The individual elements have been fabricated and tested using MOSIS* 2 micrometer CMOS technology, although the integrated system has not yet been fabricated. The imager consists of a 128 x 128 array of active pixels at a 50 micrometer pitch. Each column of pixels shares a 10-bit A/D converter based on first-order oversampled sigma-delta (Sigma-Delta) modulation. The 10-bit outputs of each converter are multiplexed and read out through a single set of outputs. A semi-parallel architecture is chosen to achieve 30 frames/second operation even at low light levels. The sensor is designed for less than 12 e^- rms noise performance.

Superpixel-Augmented Endmember Detection for Hyperspectral Images

NASA Technical Reports Server (NTRS)

Thompson, David R.; Castano, Rebecca; Gilmore, Martha

2011-01-01

Superpixels are homogeneous image regions comprised of several contiguous pixels. They are produced by shattering the image into contiguous, homogeneous regions that each cover between 20 and 100 image pixels. The segmentation aims for a many-to-one mapping from superpixels to image features; each image feature could contain several superpixels, but each superpixel occupies no more than one image feature. This conservative segmentation is relatively easy to automate in a robust fashion. Superpixel processing is related to the more general idea of improving hyperspectral analysis through spatial constraints, which can recognize subtle features at or below the level of noise by exploiting the fact that their spectral signatures are found in neighboring pixels. Recent work has explored spatial constraints for endmember extraction, showing significant advantages over techniques that ignore pixels relative positions. Methods such as AMEE (automated morphological endmember extraction) express spatial influence using fixed isometric relationships a local square window or Euclidean distance in pixel coordinates. In other words, two pixels covariances are based on their spatial proximity, but are independent of their absolute location in the scene. These isometric spatial constraints are most appropriate when spectral variation is smooth and constant over the image. Superpixels are simple to implement, efficient to compute, and are empirically effective. They can be used as a preprocessing step with any desired endmember extraction technique. Superpixels also have a solid theoretical basis in the hyperspectral linear mixing model, making them a principled approach for improving endmember extraction. Unlike existing approaches, superpixels can accommodate non-isometric covariance between image pixels (characteristic of discrete image features separated by step discontinuities). These kinds of image features are common in natural scenes. Analysts can substitute superpixels for image pixels during endmember analysis that leverages the spatial contiguity of scene features to enhance subtle spectral features. Superpixels define populations of image pixels that are independent samples from each image feature, permitting robust estimation of spectral properties, and reducing measurement noise in proportion to the area of the superpixel. This permits improved endmember extraction, and enables automated search for novel and constituent minerals in very noisy, hyperspatial images. This innovation begins with a graph-based segmentation based on the work of Felzenszwalb et al., but then expands their approach to the hyperspectral image domain with a Euclidean distance metric. Then, the mean spectrum of each segment is computed, and the resulting data cloud is used as input into sequential maximum angle convex cone (SMACC) endmember extraction.

Photon Counting Imaging with an Electron-Bombarded Pixel Image Sensor

PubMed Central

Hirvonen, Liisa M.; Suhling, Klaus

2016-01-01

Electron-bombarded pixel image sensors, where a single photoelectron is accelerated directly into a CCD or CMOS sensor, allow wide-field imaging at extremely low light levels as they are sensitive enough to detect single photons. This technology allows the detection of up to hundreds or thousands of photon events per frame, depending on the sensor size, and photon event centroiding can be employed to recover resolution lost in the detection process. Unlike photon events from electron-multiplying sensors, the photon events from electron-bombarded sensors have a narrow, acceleration-voltage-dependent pulse height distribution. Thus a gain voltage sweep during exposure in an electron-bombarded sensor could allow photon arrival time determination from the pulse height with sub-frame exposure time resolution. We give a brief overview of our work with electron-bombarded pixel image sensor technology and recent developments in this field for single photon counting imaging, and examples of some applications. PMID:27136556

Advances in Spectral-Spatial Classification of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2012-01-01

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

Modulated CMOS camera for fluorescence lifetime microscopy.

PubMed

Chen, Hongtao; Holst, Gerhard; Gratton, Enrico

2015-12-01

Widefield frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) is a fast and accurate method to measure the fluorescence lifetime of entire images. However, the complexity and high costs involved in construction of such a system limit the extensive use of this technique. PCO AG recently released the first luminescence lifetime imaging camera based on a high frequency modulated CMOS image sensor, QMFLIM2. Here we tested and provide operational procedures to calibrate the camera and to improve the accuracy using corrections necessary for image analysis. With its flexible input/output options, we are able to use a modulated laser diode or a 20 MHz pulsed white supercontinuum laser as the light source. The output of the camera consists of a stack of modulated images that can be analyzed by the SimFCS software using the phasor approach. The nonuniform system response across the image sensor must be calibrated at the pixel level. This pixel calibration is crucial and needed for every camera settings, e.g. modulation frequency and exposure time. A significant dependency of the modulation signal on the intensity was also observed and hence an additional calibration is needed for each pixel depending on the pixel intensity level. These corrections are important not only for the fundamental frequency, but also for the higher harmonics when using the pulsed supercontinuum laser. With these post data acquisition corrections, the PCO CMOS-FLIM camera can be used for various biomedical applications requiring a large frame and high speed acquisition. © 2015 Wiley Periodicals, Inc.

Adaptive pseudo-color enhancement method of weld radiographic images based on HSI color space and self-transformation of pixels.

PubMed

Jiang, Hongquan; Zhao, Yalin; Gao, Jianmin; Gao, Zhiyong

2017-06-01

The radiographic testing (RT) image of a steam turbine manufacturing enterprise has the characteristics of low gray level, low contrast, and blurriness, which lead to a substandard image quality. Moreover, it is not conducive for human eyes to detect and evaluate defects. This study proposes an adaptive pseudo-color enhancement method for weld radiographic images based on the hue, saturation, and intensity (HSI) color space and the self-transformation of pixels to solve these problems. First, the pixel's self-transformation is performed to the pixel value of the original RT image. The function value after the pixel's self-transformation is assigned to the HSI components in the HSI color space. Thereafter, the average intensity of the enhanced image is adaptively adjusted to 0.5 according to the intensity of the original image. Moreover, the hue range and interval can be adjusted according to personal habits. Finally, the HSI components after the adaptive adjustment can be transformed to display in the red, green, and blue color space. Numerous weld radiographic images from a steam turbine manufacturing enterprise are used to validate the proposed method. The experimental results show that the proposed pseudo-color enhancement method can improve image definition and make the target and background areas distinct in weld radiographic images. The enhanced images will be more conducive for defect recognition. Moreover, the image enhanced using the proposed method conforms to the human eye visual properties, and the effectiveness of defect recognition and evaluation can be ensured.

Adaptive pseudo-color enhancement method of weld radiographic images based on HSI color space and self-transformation of pixels

NASA Astrophysics Data System (ADS)

Jiang, Hongquan; Zhao, Yalin; Gao, Jianmin; Gao, Zhiyong

2017-06-01

The radiographic testing (RT) image of a steam turbine manufacturing enterprise has the characteristics of low gray level, low contrast, and blurriness, which lead to a substandard image quality. Moreover, it is not conducive for human eyes to detect and evaluate defects. This study proposes an adaptive pseudo-color enhancement method for weld radiographic images based on the hue, saturation, and intensity (HSI) color space and the self-transformation of pixels to solve these problems. First, the pixel's self-transformation is performed to the pixel value of the original RT image. The function value after the pixel's self-transformation is assigned to the HSI components in the HSI color space. Thereafter, the average intensity of the enhanced image is adaptively adjusted to 0.5 according to the intensity of the original image. Moreover, the hue range and interval can be adjusted according to personal habits. Finally, the HSI components after the adaptive adjustment can be transformed to display in the red, green, and blue color space. Numerous weld radiographic images from a steam turbine manufacturing enterprise are used to validate the proposed method. The experimental results show that the proposed pseudo-color enhancement method can improve image definition and make the target and background areas distinct in weld radiographic images. The enhanced images will be more conducive for defect recognition. Moreover, the image enhanced using the proposed method conforms to the human eye visual properties, and the effectiveness of defect recognition and evaluation can be ensured.

Night Vision Camera

NASA Technical Reports Server (NTRS)

1996-01-01

PixelVision, Inc. developed the Night Video NV652 Back-illuminated CCD Camera, based on the expertise of a former Jet Propulsion Laboratory employee and a former employee of Scientific Imaging Technologies, Inc. The camera operates without an image intensifier, using back-illuminated and thinned CCD technology to achieve extremely low light level imaging performance. The advantages of PixelVision's system over conventional cameras include greater resolution and better target identification under low light conditions, lower cost and a longer lifetime. It is used commercially for research and aviation.

A novel snapshot polarimetric imager

NASA Astrophysics Data System (ADS)

Wong, Gerald; McMaster, Ciaran; Struthers, Robert; Gorman, Alistair; Sinclair, Peter; Lamb, Robert; Harvey, Andrew R.

2012-10-01

Polarimetric imaging (PI) is of increasing importance in determining additional scene information beyond that of conventional images. For very long-range surveillance, image quality is degraded due to turbulence. Furthermore, the high magnification required to create images with sufficient spatial resolution suitable for object recognition and identification require long focal length optical systems. These are incompatible with the size and weight restrictions for aircraft. Techniques which allow detection and recognition of an object at the single pixel level are therefore likely to provide advance warning of approaching threats or long-range object cueing. PI is a technique that has the potential to detect object signatures at the pixel level. Early attempts to develop PI used rotating polarisers (and spectral filters) which recorded sequential polarized images from which the complete Stokes matrix could be derived. This approach has built-in latency between frames and requires accurate registration of consecutive frames to analyze real-time video of moving objects. Alternatively, multiple optical systems and cameras have been demonstrated to remove latency, but this approach increases cost and bulk of the imaging system. In our investigation we present a simplified imaging system that divides an image into two orthogonal polarimetric components which are then simultaneously projected onto a single detector array. Thus polarimetric data is recorded without latency on a single snapshot. We further show that, for pixel-level objects, the data derived from only two orthogonal states (H and V) is sufficient to increase the probability of detection whilst reducing false alarms compared to conventional unpolarised imaging.

Estimation of saturated pixel values in digital color imaging

PubMed Central

Zhang, Xuemei; Brainard, David H.

2007-01-01

Pixel saturation, where the incident light at a pixel causes one of the color channels of the camera sensor to respond at its maximum value, can produce undesirable artifacts in digital color images. We present a Bayesian algorithm that estimates what the saturated channel's value would have been in the absence of saturation. The algorithm uses the non-saturated responses from the other color channels, together with a multivariate Normal prior that captures the correlation in response across color channels. The appropriate parameters for the prior may be estimated directly from the image data, since most image pixels are not saturated. Given the prior, the responses of the non-saturated channels, and the fact that the true response of the saturated channel is known to be greater than the saturation level, the algorithm returns the optimal expected mean square estimate for the true response. Extensions of the algorithm to the case where more than one channel is saturated are also discussed. Both simulations and examples with real images are presented to show that the algorithm is effective. PMID:15603065

A programmable computational image sensor for high-speed vision

NASA Astrophysics Data System (ADS)

Yang, Jie; Shi, Cong; Long, Xitian; Wu, Nanjian

2013-08-01

In this paper we present a programmable computational image sensor for high-speed vision. This computational image sensor contains four main blocks: an image pixel array, a massively parallel processing element (PE) array, a row processor (RP) array and a RISC core. The pixel-parallel PE is responsible for transferring, storing and processing image raw data in a SIMD fashion with its own programming language. The RPs are one dimensional array of simplified RISC cores, it can carry out complex arithmetic and logic operations. The PE array and RP array can finish great amount of computation with few instruction cycles and therefore satisfy the low- and middle-level high-speed image processing requirement. The RISC core controls the whole system operation and finishes some high-level image processing algorithms. We utilize a simplified AHB bus as the system bus to connect our major components. Programming language and corresponding tool chain for this computational image sensor are also developed.

Increasing Linear Dynamic Range of a CMOS Image Sensor

NASA Technical Reports Server (NTRS)

Pain, Bedabrata

2007-01-01

A generic design and a corresponding operating sequence have been developed for increasing the linear-response dynamic range of a complementary metal oxide/semiconductor (CMOS) image sensor. The design provides for linear calibrated dual-gain pixels that operate at high gain at a low signal level and at low gain at a signal level above a preset threshold. Unlike most prior designs for increasing dynamic range of an image sensor, this design does not entail any increase in noise (including fixed-pattern noise), decrease in responsivity or linearity, or degradation of photometric calibration. The figure is a simplified schematic diagram showing the circuit of one pixel and pertinent parts of its column readout circuitry. The conventional part of the pixel circuit includes a photodiode having a small capacitance, CD. The unconventional part includes an additional larger capacitance, CL, that can be connected to the photodiode via a transfer gate controlled in part by a latch. In the high-gain mode, the signal labeled TSR in the figure is held low through the latch, which also helps to adapt the gain on a pixel-by-pixel basis. Light must be coupled to the pixel through a microlens or by back illumination in order to obtain a high effective fill factor; this is necessary to ensure high quantum efficiency, a loss of which would minimize the efficacy of the dynamic- range-enhancement scheme. Once the level of illumination of the pixel exceeds the threshold, TSR is turned on, causing the transfer gate to conduct, thereby adding CL to the pixel capacitance. The added capacitance reduces the conversion gain, and increases the pixel electron-handling capacity, thereby providing an extension of the dynamic range. By use of an array of comparators also at the bottom of the column, photocharge voltages on sampling capacitors in each column are compared with a reference voltage to determine whether it is necessary to switch from the high-gain to the low-gain mode. Depending upon the built-in offset in each pixel and in each comparator, the point at which the gain change occurs will be different, adding gain-dependent fixed pattern noise in each pixel. The offset, and hence the fixed pattern noise, is eliminated by sampling the pixel readout charge four times by use of four capacitors (instead of two such capacitors as in conventional design) connected to the bottom of the column via electronic switches SHS1, SHR1, SHS2, and SHR2, respectively, corresponding to high and low values of the signals TSR and RST. The samples are combined in an appropriate fashion to cancel offset-induced errors, and provide spurious-free imaging with extended dynamic range.

X-ray imaging using amorphous selenium: a photoinduced discharge readout method for digital mammography.

PubMed

Rowlands, J A; Hunter, D M; Araj, N

1991-01-01

A new digital image readout method for electrostatic charge images on photoconductive plates is described. The method can be used to read out images on selenium plates similar to those used in xeromammography. The readout method, called the air-gap photoinduced discharge method (PID), discharges the latent image pixel by pixel and measures the charge. The PID readout method, like electrometer methods, is linear. However, the PID method permits much better resolution than scanning electrometers while maintaining quantum limited performance at high radiation exposure levels. Thus the air-gap PID method appears to be uniquely superior for high-resolution digital imaging tasks such as mammography.

Sub-pixel mineral mapping using EO-1 Hyperion hyperspectral data

NASA Astrophysics Data System (ADS)

Kumar, C.; Shetty, A.; Raval, S.; Champatiray, P. K.; Sharma, R.

2014-11-01

This study describes the utility of Earth Observation (EO)-1 Hyperion data for sub-pixel mineral investigation using Mixture Tuned Target Constrained Interference Minimized Filter (MTTCIMF) algorithm in hostile mountainous terrain of Rajsamand district of Rajasthan, which hosts economic mineralization such as lead, zinc, and copper etc. The study encompasses pre-processing, data reduction, Pixel Purity Index (PPI) and endmember extraction from reflectance image of surface minerals such as illite, montmorillonite, phlogopite, dolomite and chlorite. These endmembers were then assessed with USGS mineral spectral library and lab spectra of rock samples collected from field for spectral inspection. Subsequently, MTTCIMF algorithm was implemented on processed image to obtain mineral distribution map of each detected mineral. A virtual verification method has been adopted to evaluate the classified image, which uses directly image information to evaluate the result and confirm the overall accuracy and kappa coefficient of 68 % and 0.6 respectively. The sub-pixel level mineral information with reasonable accuracy could be a valuable guide to geological and exploration community for expensive ground and/or lab experiments to discover economic deposits. Thus, the study demonstrates the feasibility of Hyperion data for sub-pixel mineral mapping using MTTCIMF algorithm with cost and time effective approach.

Vectorized image segmentation via trixel agglomeration

DOEpatents

Prasad, Lakshman [Los Alamos, NM; Skourikhine, Alexei N [Los Alamos, NM

2006-10-24

A computer implemented method transforms an image comprised of pixels into a vectorized image specified by a plurality of polygons that can be subsequently used to aid in image processing and understanding. The pixelated image is processed to extract edge pixels that separate different colors and a constrained Delaunay triangulation of the edge pixels forms a plurality of triangles having edges that cover the pixelated image. A color for each one of the plurality of triangles is determined from the color pixels within each triangle. A filter is formed with a set of grouping rules related to features of the pixelated image and applied to the plurality of triangle edges to merge adjacent triangles consistent with the filter into polygons having a plurality of vertices. The pixelated image may be then reformed into an array of the polygons, that can be represented collectively and efficiently by standard vector image.

Scanning microarray slides.

PubMed

Ares, Manuel

2014-02-01

Here we describe some practical concerns surrounding the scanning of microarray slides that have been hybridized with fluorescent dyes. We use a laser scanner that has two lasers, each set to excite a different fluor, and separate detectors to capture emission from each fluor. The laser passes over an address (position on the scanned surface) and the detectors capture photons emitted from each address. Two superimposed image files are written that carry intensities for each channel for each pixel of the image scan. These are the raw data. Image analysis software is used to identify and summarize the intensities of the pixels that make up each spot. After comparison to background pixels, the processed intensity levels representing the gene expression measurements are associated with the identity of each spot.

Selective document image data compression technique

DOEpatents

Fu, C.Y.; Petrich, L.I.

1998-05-19

A method of storing information from filled-in form-documents comprises extracting the unique user information in the foreground from the document form information in the background. The contrast of the pixels is enhanced by a gamma correction on an image array, and then the color value of each of pixel is enhanced. The color pixels lying on edges of an image are converted to black and an adjacent pixel is converted to white. The distance between black pixels and other pixels in the array is determined, and a filled-edge array of pixels is created. User information is then converted to a two-color format by creating a first two-color image of the scanned image by converting all pixels darker than a threshold color value to black. All the pixels that are lighter than the threshold color value to white. Then a second two-color image of the filled-edge file is generated by converting all pixels darker than a second threshold value to black and all pixels lighter than the second threshold color value to white. The first two-color image and the second two-color image are then combined and filtered to smooth the edges of the image. The image may be compressed with a unique Huffman coding table for that image. The image file is also decimated to create a decimated-image file which can later be interpolated back to produce a reconstructed image file using a bilinear interpolation kernel. 10 figs.

Selective document image data compression technique

DOEpatents

Fu, Chi-Yung; Petrich, Loren I.

1998-01-01

A method of storing information from filled-in form-documents comprises extracting the unique user information in the foreground from the document form information in the background. The contrast of the pixels is enhanced by a gamma correction on an image array, and then the color value of each of pixel is enhanced. The color pixels lying on edges of an image are converted to black and an adjacent pixel is converted to white. The distance between black pixels and other pixels in the array is determined, and a filled-edge array of pixels is created. User information is then converted to a two-color format by creating a first two-color image of the scanned image by converting all pixels darker than a threshold color value to black. All the pixels that are lighter than the threshold color value to white. Then a second two-color image of the filled-edge file is generated by converting all pixels darker than a second threshold value to black and all pixels lighter than the second threshold color value to white. The first two-color image and the second two-color image are then combined and filtered to smooth the edges of the image. The image may be compressed with a unique Huffman coding table for that image. The image file is also decimated to create a decimated-image file which can later be interpolated back to produce a reconstructed image file using a bilinear interpolation kernel.--(235 words)

Image Processing for Binarization Enhancement via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A. (Inventor)

2009-01-01

A technique for enhancing a gray-scale image to improve conversions of the image to binary employs fuzzy reasoning. In the technique, pixels in the image are analyzed by comparing the pixel's gray scale value, which is indicative of its relative brightness, to the values of pixels immediately surrounding the selected pixel. The degree to which each pixel in the image differs in value from the values of surrounding pixels is employed as the variable in a fuzzy reasoning-based analysis that determines an appropriate amount by which the selected pixel's value should be adjusted to reduce vagueness and ambiguity in the image and improve retention of information during binarization of the enhanced gray-scale image.

Noise Reduction Techniques and Scaling Effects towards Photon Counting CMOS Image Sensors

PubMed Central

Boukhayma, Assim; Peizerat, Arnaud; Enz, Christian

2016-01-01

This paper presents an overview of the read noise in CMOS image sensors (CISs) based on four-transistors (4T) pixels, column-level amplification and correlated multiple sampling. Starting from the input-referred noise analytical formula, process level optimizations, device choices and circuit techniques at the pixel and column level of the readout chain are derived and discussed. The noise reduction techniques that can be implemented at the column and pixel level are verified by transient noise simulations, measurement and results from recently-published low noise CIS. We show how recently-reported process refinement, leading to the reduction of the sense node capacitance, can be combined with an optimal in-pixel source follower design to reach a sub-0.3erms- read noise at room temperature. This paper also discusses the impact of technology scaling on the CIS read noise. It shows how designers can take advantage of scaling and how the Metal-Oxide-Semiconductor (MOS) transistor gate leakage tunneling current appears as a challenging limitation. For this purpose, both simulation results of the gate leakage current and 1/f noise data reported from different foundries and technology nodes are used.

Fundamental performance differences between CMOS and CCD imagers, part IV

NASA Astrophysics Data System (ADS)

Janesick, James; Pinter, Jeff; Potter, Robert; Elliott, Tom; Andrews, James; Tower, John; Grygon, Mark; Keller, Dave

2010-07-01

This paper is a continuation of past papers written on fundamental performance differences of scientific CMOS and CCD imagers. New characterization results presented below include: 1). a new 1536 × 1536 × 8μm 5TPPD pixel CMOS imager, 2). buried channel MOSFETs for random telegraph noise (RTN) and threshold reduction, 3) sub-electron noise pixels, 4) 'MIM pixel' for pixel sensitivity (V/e-) control, 5) '5TPPD RING pixel' for large pixel, high-speed charge transfer applications, 6) pixel-to-pixel blooming control, 7) buried channel photo gate pixels and CMOSCCDs, 8) substrate bias for deep depletion CMOS imagers, 9) CMOS dark spikes and dark current issues and 10) high energy radiation damage test data. Discussions are also given to a 1024 × 1024 × 16 um 5TPPD pixel imager currently in fabrication and new stitched CMOS imagers that are in the design phase including 4k × 4k × 10 μm and 10k × 10k × 10 um imager formats.

Acquisition of STEM Images by Adaptive Compressive Sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Weiyi; Feng, Qianli; Srinivasan, Ramprakash

Compressive Sensing (CS) allows a signal to be sparsely measured first and accurately recovered later in software [1]. In scanning transmission electron microscopy (STEM), it is possible to compress an image spatially by reducing the number of measured pixels, which decreases electron dose and increases sensing speed [2,3,4]. The two requirements for CS to work are: (1) sparsity of basis coefficients and (2) incoherence of the sensing system and the representation system. However, when pixels are missing from the image, it is difficult to have an incoherent sensing matrix. Nevertheless, dictionary learning techniques such as Beta-Process Factor Analysis (BPFA) [5]more » are able to simultaneously discover a basis and the sparse coefficients in the case of missing pixels. On top of CS, we would like to apply active learning [6,7] to further reduce the proportion of pixels being measured, while maintaining image reconstruction quality. Suppose we initially sample 10% of random pixels. We wish to select the next 1% of pixels that are most useful in recovering the image. Now, we have 11% of pixels, and we want to decide the next 1% of “most informative” pixels. Active learning methods are online and sequential in nature. Our goal is to adaptively discover the best sensing mask during acquisition using feedback about the structures in the image. In the end, we hope to recover a high quality reconstruction with a dose reduction relative to the non-adaptive (random) sensing scheme. In doing this, we try three metrics applied to the partial reconstructions for selecting the new set of pixels: (1) variance, (2) Kullback-Leibler (KL) divergence using a Radial Basis Function (RBF) kernel, and (3) entropy. Figs. 1 and 2 display the comparison of Peak Signal-to-Noise (PSNR) using these three different active learning methods at different percentages of sampled pixels. At 20% level, all the three active learning methods underperform the original CS without active learning. However, they all beat the original CS as more of the “most informative” pixels are sampled. One can also argue that CS equipped with active learning requires less sampled pixels to achieve the same value of PSNR than CS with pixels randomly sampled, since all the three PSNR curves with active learning grow at a faster pace than that without active learning. For this particular STEM image, by observing the reconstructed images and the sensing masks, we find that while the method based on RBF kernel acquires samples more uniformly, the one on entropy samples more areas of significant change, thus less uniformly. The KL-divergence method performs the best in terms of reconstruction error (PSNR) for this example [8].« less

Efficient Solar Scene Wavefront Estimation with Reduced Systematic and RMS Errors: Summary

NASA Astrophysics Data System (ADS)

Anugu, N.; Garcia, P.

2016-04-01

Wave front sensing for solar telescopes is commonly implemented with the Shack-Hartmann sensors. Correlation algorithms are usually used to estimate the extended scene Shack-Hartmann sub-aperture image shifts or slopes. The image shift is computed by correlating a reference sub-aperture image with the target distorted sub-aperture image. The pixel position where the maximum correlation is located gives the image shift in integer pixel coordinates. Sub-pixel precision image shifts are computed by applying a peak-finding algorithm to the correlation peak Poyneer (2003); Löfdahl (2010). However, the peak-finding algorithm results are usually biased towards the integer pixels, these errors are called as systematic bias errors Sjödahl (1994). These errors are caused due to the low pixel sampling of the images. The amplitude of these errors depends on the type of correlation algorithm and the type of peak-finding algorithm being used. To study the systematic errors in detail, solar sub-aperture synthetic images are constructed by using a Swedish Solar Telescope solar granulation image1. The performance of cross-correlation algorithm in combination with different peak-finding algorithms is investigated. The studied peak-finding algorithms are: parabola Poyneer (2003); quadratic polynomial Löfdahl (2010); threshold center of gravity Bailey (2003); Gaussian Nobach & Honkanen (2005) and Pyramid Bailey (2003). The systematic error study reveals that that the pyramid fit is the most robust to pixel locking effects. The RMS error analysis study reveals that the threshold centre of gravity behaves better in low SNR, although the systematic errors in the measurement are large. It is found that no algorithm is best for both the systematic and the RMS error reduction. To overcome the above problem, a new solution is proposed. In this solution, the image sampling is increased prior to the actual correlation matching. The method is realized in two steps to improve its computational efficiency. In the first step, the cross-correlation is implemented at the original image spatial resolution grid (1 pixel). In the second step, the cross-correlation is performed using a sub-pixel level grid by limiting the field of search to 4 × 4 pixels centered at the first step delivered initial position. The generation of these sub-pixel grid based region of interest images is achieved with the bi-cubic interpolation. The correlation matching with sub-pixel grid technique was previously reported in electronic speckle photography Sjö'dahl (1994). This technique is applied here for the solar wavefront sensing. A large dynamic range and a better accuracy in the measurements are achieved with the combination of the original pixel grid based correlation matching in a large field of view and a sub-pixel interpolated image grid based correlation matching within a small field of view. The results revealed that the proposed method outperforms all the different peak-finding algorithms studied in the first approach. It reduces both the systematic error and the RMS error by a factor of 5 (i.e., 75% systematic error reduction), when 5 times improved image sampling was used. This measurement is achieved at the expense of twice the computational cost. With the 5 times improved image sampling, the wave front accuracy is increased by a factor of 5. The proposed solution is strongly recommended for wave front sensing in the solar telescopes, particularly, for measuring large dynamic image shifts involved open loop adaptive optics. Also, by choosing an appropriate increment of image sampling in trade-off between the computational speed limitation and the aimed sub-pixel image shift accuracy, it can be employed in closed loop adaptive optics. The study is extended to three other class of sub-aperture images (a point source; a laser guide star; a Galactic Center extended scene). The results are planned to submit for the Optical Express journal.

Penrose high-dynamic-range imaging

NASA Astrophysics Data System (ADS)

Li, Jia; Bai, Chenyan; Lin, Zhouchen; Yu, Jian

2016-05-01

High-dynamic-range (HDR) imaging is becoming increasingly popular and widespread. The most common multishot HDR approach, based on multiple low-dynamic-range images captured with different exposures, has difficulties in handling camera and object movements. The spatially varying exposures (SVE) technology provides a solution to overcome this limitation by obtaining multiple exposures of the scene in only one shot but suffers from a loss in spatial resolution of the captured image. While aperiodic assignment of exposures has been shown to be advantageous during reconstruction in alleviating resolution loss, almost all the existing imaging sensors use the square pixel layout, which is a periodic tiling of square pixels. We propose the Penrose pixel layout, using pixels in aperiodic rhombus Penrose tiling, for HDR imaging. With the SVE technology, Penrose pixel layout has both exposure and pixel aperiodicities. To investigate its performance, we have to reconstruct HDR images in square pixel layout from Penrose raw images with SVE. Since the two pixel layouts are different, the traditional HDR reconstruction methods are not applicable. We develop a reconstruction method for Penrose pixel layout using a Gaussian mixture model for regularization. Both quantitative and qualitative results show the superiority of Penrose pixel layout over square pixel layout.

Measurements with MÖNCH, a 25 μm pixel pitch hybrid pixel detector

NASA Astrophysics Data System (ADS)

Ramilli, M.; Bergamaschi, A.; Andrae, M.; Brückner, M.; Cartier, S.; Dinapoli, R.; Fröjdh, E.; Greiffenberg, D.; Hutwelker, T.; Lopez-Cuenca, C.; Mezza, D.; Mozzanica, A.; Ruat, M.; Redford, S.; Schmitt, B.; Shi, X.; Tinti, G.; Zhang, J.

2017-01-01

MÖNCH is a hybrid silicon pixel detector based on charge integration and with analog readout, featuring a pixel size of 25×25 μm2. The latest working prototype consists of an array of 400×400 identical pixels for a total active area of 1×1 cm2. Its design is optimized for the single photon regime. An exhaustive characterization of this large area prototype has been carried out in the past months, and it confirms an ENC in the order of 35 electrons RMS and a dynamic range of ~4×12 keV photons in high gain mode, which increases to ~100×12 keV photons with the lowest gain setting. The low noise levels of MÖNCH make it a suitable candidate for X-ray detection at energies around 1 keV and below. Imaging applications in particular can benefit significantly from the use of MÖNCH: due to its extremely small pixel pitch, the detector intrinsically offers excellent position resolution. Moreover, in low flux conditions, charge sharing between neighboring pixels allows the use of position interpolation algorithms which grant a resolution at the micrometer-level. Its energy reconstruction and imaging capabilities have been tested for the first time at a low energy beamline at PSI, with photon energies between 1.75 keV and 3.5 keV, and results will be shown.

Hexagonal Pixels and Indexing Scheme for Binary Images

NASA Technical Reports Server (NTRS)

Johnson, Gordon G.

2004-01-01

A scheme for resampling binaryimage data from a rectangular grid to a regular hexagonal grid and an associated tree-structured pixel-indexing scheme keyed to the level of resolution have been devised. This scheme could be utilized in conjunction with appropriate image-data-processing algorithms to enable automated retrieval and/or recognition of images. For some purposes, this scheme is superior to a prior scheme that relies on rectangular pixels: one example of such a purpose is recognition of fingerprints, which can be approximated more closely by use of line segments along hexagonal axes than by line segments along rectangular axes. This scheme could also be combined with algorithms for query-image-based retrieval of images via the Internet. A binary image on a rectangular grid is generated by raster scanning or by sampling on a stationary grid of rectangular pixels. In either case, each pixel (each cell in the rectangular grid) is denoted as either bright or dark, depending on whether the light level in the pixel is above or below a prescribed threshold. The binary data on such an image are stored in a matrix form that lends itself readily to searches of line segments aligned with either or both of the perpendicular coordinate axes. The first step in resampling onto a regular hexagonal grid is to make the resolution of the hexagonal grid fine enough to capture all the binaryimage detail from the rectangular grid. In practice, this amounts to choosing a hexagonal-cell width equal to or less than a third of the rectangular- cell width. Once the data have been resampled onto the hexagonal grid, the image can readily be checked for line segments aligned with the hexagonal coordinate axes, which typically lie at angles of 30deg, 90deg, and 150deg with respect to say, the horizontal rectangular coordinate axis. Optionally, one can then rotate the rectangular image by 90deg, then again sample onto the hexagonal grid and check for line segments at angles of 0deg, 60deg, and 120deg to the original horizontal coordinate axis. The net result is that one has checked for line segments at angular intervals of 30deg. For even finer angular resolution, one could, for example, then rotate the rectangular-grid image +/-45deg before sampling to perform checking for line segments at angular intervals of 15deg.

Threshold selection for classification of MR brain images by clustering method

NASA Astrophysics Data System (ADS)

Moldovanu, Simona; Obreja, Cristian; Moraru, Luminita

2015-12-01

Given a grey-intensity image, our method detects the optimal threshold for a suitable binarization of MR brain images. In MR brain image processing, the grey levels of pixels belonging to the object are not substantially different from the grey levels belonging to the background. Threshold optimization is an effective tool to separate objects from the background and further, in classification applications. This paper gives a detailed investigation on the selection of thresholds. Our method does not use the well-known method for binarization. Instead, we perform a simple threshold optimization which, in turn, will allow the best classification of the analyzed images into healthy and multiple sclerosis disease. The dissimilarity (or the distance between classes) has been established using the clustering method based on dendrograms. We tested our method using two classes of images: the first consists of 20 T2-weighted and 20 proton density PD-weighted scans from two healthy subjects and from two patients with multiple sclerosis. For each image and for each threshold, the number of the white pixels (or the area of white objects in binary image) has been determined. These pixel numbers represent the objects in clustering operation. The following optimum threshold values are obtained, T = 80 for PD images and T = 30 for T2w images. Each mentioned threshold separate clearly the clusters that belonging of the studied groups, healthy patient and multiple sclerosis disease.

A comparative study of 2 computer-assisted methods of quantifying brightfield microscopy images.

PubMed

Tse, George H; Marson, Lorna P

2013-10-01

Immunohistochemistry continues to be a powerful tool for the detection of antigens. There are several commercially available software packages that allow image analysis; however, these can be complex, require relatively high level of computer skills, and can be expensive. We compared 2 commonly available software packages, Adobe Photoshop CS6 and ImageJ, in their ability to quantify percentage positive area after picrosirius red (PSR) staining and 3,3'-diaminobenzidine (DAB) staining. On analysis of DAB-stained B cells in the mouse spleen, with a biotinylated primary rat anti-mouse-B220 antibody, there was no significant difference on converting images from brightfield microscopy to binary images to measure black and white pixels using ImageJ compared with measuring a range of brown pixels with Photoshop (Student t test, P=0.243, correlation r=0.985). When analyzing mouse kidney allografts stained with PSR, Photoshop achieved a greater interquartile range while maintaining a lower 10th percentile value compared with analysis with ImageJ. A lower 10% percentile reflects that Photoshop analysis is better at analyzing tissues with low levels of positive pixels; particularly relevant for control tissues or negative controls, whereas after ImageJ analysis the same images would result in spuriously high levels of positivity. Furthermore comparing the 2 methods by Bland-Altman plot revealed that these 2 methodologies did not agree when measuring images with a higher percentage of positive staining and correlation was poor (r=0.804). We conclude that for computer-assisted analysis of images of DAB-stained tissue there is no difference between using Photoshop or ImageJ. However, for analysis of color images where differentiation into a binary pattern is not easy, such as with PSR, Photoshop is superior at identifying higher levels of positivity while maintaining differentiation of low levels of positive staining.

Advances in Spectral-Spatial Classification of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2012-01-01

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation, and contrast of the spatial structures present in the image. Then, the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines (SVMs) using the available spectral information and the extracted spatial information. Spatial postprocessing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple-classifier (MC) system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral–spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

Development and characterization of high-resolution neutron pixel detectors based on Timepix read-out chips

NASA Astrophysics Data System (ADS)

Krejci, F.; Zemlicka, J.; Jakubek, J.; Dudak, J.; Vavrik, D.; Köster, U.; Atkins, D.; Kaestner, A.; Soltes, J.; Viererbl, L.; Vacik, J.; Tomandl, I.

2016-12-01

Using a suitable isotope such as 6Li and 10B semiconductor hybrid pixel detectors can be successfully adapted for position sensitive detection of thermal and cold neutrons via conversion into energetic light ions. The adapted devices then typically provides spatial resolution at the level comparable to the pixel pitch (55 μm) and sensitive area of about few cm2. In this contribution, we describe further progress in neutron imaging performance based on the development of a large-area hybrid pixel detector providing practically continuous neutron sensitive area of 71 × 57 mm2. The measurements characterising the detector performance at the cold neutron imaging instrument ICON at PSI and high-flux imaging beam-line Neutrograph at ILL are presented. At both facilities, high-resolution high-contrast neutron radiography with the newly developed detector has been successfully applied for objects which imaging were previously difficult with hybrid pixel technology (such as various composite materials, objects of cultural heritage etc.). Further, a significant improvement in the spatial resolution of neutron radiography with hybrid semiconductor pixel detector based on the fast read-out Timepix-based detector is presented. The system is equipped with a thin planar 6LiF convertor operated effectively in the event-by-event mode enabling position sensitive detection with spatial resolution better than 10 μm.

Surface composition of Mars: A Viking multispectral view

NASA Technical Reports Server (NTRS)

Adams, John B.; Smith, Milton O.; Arvidson, Raymond E.; Dale-Bannister, Mary; Guinness, Edward A.; Singer, Robert; Adams, John B.

1987-01-01

A new method of analyzing multispectral images takes advantage of the spectral variation from pixel to pixel that is typical for natural planetary surfaces, and treats all pixels as potential mixtures of spectrally distinct materials. For Viking Lander images, mixtures of only three spectral end members (rock, soil, and shade) are sufficient to explain the observed spectral variation to the level of instrumental noise. It was concluded that a large portion of the Martian surface consists of only two spectrally distinct materials, basalt and palgonitic soil. It is emphasized, however, that as viewed through the three broad bandpasses of Viking Orbiter, other materials cannot be distinguished from the mixtures.

Hierarchical tone mapping for high dynamic range image visualization

NASA Astrophysics Data System (ADS)

Qiu, Guoping; Duan, Jiang

2005-07-01

In this paper, we present a computationally efficient, practically easy to use tone mapping techniques for the visualization of high dynamic range (HDR) images in low dynamic range (LDR) reproduction devices. The new method, termed hierarchical nonlinear linear (HNL) tone-mapping operator maps the pixels in two hierarchical steps. The first step allocates appropriate numbers of LDR display levels to different HDR intensity intervals according to the pixel densities of the intervals. The second step linearly maps the HDR intensity intervals to theirs allocated LDR display levels. In the developed HNL scheme, the assignment of LDR display levels to HDR intensity intervals is controlled by a very simple and flexible formula with a single adjustable parameter. We also show that our new operators can be used for the effective enhancement of ordinary images.

Image acquisition system using on sensor compressed sampling technique

NASA Astrophysics Data System (ADS)

Gupta, Pravir Singh; Choi, Gwan Seong

2018-01-01

Advances in CMOS technology have made high-resolution image sensors possible. These image sensors pose significant challenges in terms of the amount of raw data generated, energy efficiency, and frame rate. This paper presents a design methodology for an imaging system and a simplified image sensor pixel design to be used in the system so that the compressed sensing (CS) technique can be implemented easily at the sensor level. This results in significant energy savings as it not only cuts the raw data rate but also reduces transistor count per pixel; decreases pixel size; increases fill factor; simplifies analog-to-digital converter, JPEG encoder, and JPEG decoder design; decreases wiring; and reduces the decoder size by half. Thus, CS has the potential to increase the resolution of image sensors for a given technology and die size while significantly decreasing the power consumption and design complexity. We show that it has potential to reduce power consumption by about 23% to 65%.

The fragmented nature of tundra landscape

NASA Astrophysics Data System (ADS)

Virtanen, Tarmo; Ek, Malin

2014-04-01

The vegetation and land cover structure of tundra areas is fragmented when compared to other biomes. Thus, satellite images of high resolution are required for producing land cover classifications, in order to reveal the actual distribution of land cover types across these large and remote areas. We produced and compared different land cover classifications using three satellite images (QuickBird, Aster and Landsat TM5) with different pixel sizes (2.4 m, 15 m and 30 m pixel size, respectively). The study area, in north-eastern European Russia, was visited in July 2007 to obtain ground reference data. The QuickBird image was classified using supervised segmentation techniques, while the Aster and Landsat TM5 images were classified using a pixel-based supervised classification method. The QuickBird classification showed the highest accuracy when tested against field data, while the Aster image was generally more problematic to classify than the Landsat TM5 image. Use of smaller pixel sized images distinguished much greater levels of landscape fragmentation. The overall mean patch sizes in the QuickBird, Aster, and Landsat TM5-classifications were 871 m2, 2141 m2 and 7433 m2, respectively. In the QuickBird classification, the mean patch size of all the tundra and peatland vegetation classes was smaller than one pixel of the Landsat TM5 image. Water bodies and fens in particular occur in the landscape in small or elongated patches, and thus cannot be realistically classified from larger pixel sized images. Land cover patterns vary considerably at such a fine-scale, so that a lot of information is lost if only medium resolution satellite images are used. It is crucial to know the amount and spatial distribution of different vegetation types in arctic landscapes, as carbon dynamics and other climate related physical, geological and biological processes are known to vary greatly between vegetation types.

Automatic optimal filament segmentation with sub-pixel accuracy using generalized linear models and B-spline level-sets

PubMed Central

Xiao, Xun; Geyer, Veikko F.; Bowne-Anderson, Hugo; Howard, Jonathon; Sbalzarini, Ivo F.

2016-01-01

Biological filaments, such as actin filaments, microtubules, and cilia, are often imaged using different light-microscopy techniques. Reconstructing the filament curve from the acquired images constitutes the filament segmentation problem. Since filaments have lower dimensionality than the image itself, there is an inherent trade-off between tracing the filament with sub-pixel accuracy and avoiding noise artifacts. Here, we present a globally optimal filament segmentation method based on B-spline vector level-sets and a generalized linear model for the pixel intensity statistics. We show that the resulting optimization problem is convex and can hence be solved with global optimality. We introduce a simple and efficient algorithm to compute such optimal filament segmentations, and provide an open-source implementation as an ImageJ/Fiji plugin. We further derive an information-theoretic lower bound on the filament segmentation error, quantifying how well an algorithm could possibly do given the information in the image. We show that our algorithm asymptotically reaches this bound in the spline coefficients. We validate our method in comprehensive benchmarks, compare with other methods, and show applications from fluorescence, phase-contrast, and dark-field microscopy. PMID:27104582

Super-pixel extraction based on multi-channel pulse coupled neural network

NASA Astrophysics Data System (ADS)

Xu, GuangZhu; Hu, Song; Zhang, Liu; Zhao, JingJing; Fu, YunXia; Lei, BangJun

2018-04-01

Super-pixel extraction techniques group pixels to form over-segmented image blocks according to the similarity among pixels. Compared with the traditional pixel-based methods, the image descripting method based on super-pixel has advantages of less calculation, being easy to perceive, and has been widely used in image processing and computer vision applications. Pulse coupled neural network (PCNN) is a biologically inspired model, which stems from the phenomenon of synchronous pulse release in the visual cortex of cats. Each PCNN neuron can correspond to a pixel of an input image, and the dynamic firing pattern of each neuron contains both the pixel feature information and its context spatial structural information. In this paper, a new color super-pixel extraction algorithm based on multi-channel pulse coupled neural network (MPCNN) was proposed. The algorithm adopted the block dividing idea of SLIC algorithm, and the image was divided into blocks with same size first. Then, for each image block, the adjacent pixels of each seed with similar color were classified as a group, named a super-pixel. At last, post-processing was adopted for those pixels or pixel blocks which had not been grouped. Experiments show that the proposed method can adjust the number of superpixel and segmentation precision by setting parameters, and has good potential for super-pixel extraction.

Image compression technique

DOEpatents

Fu, Chi-Yung; Petrich, Loren I.

1997-01-01

An image is compressed by identifying edge pixels of the image; creating a filled edge array of pixels each of the pixels in the filled edge array which corresponds to an edge pixel having a value equal to the value of a pixel of the image array selected in response to the edge pixel, and each of the pixels in the filled edge array which does not correspond to an edge pixel having a value which is a weighted average of the values of surrounding pixels in the filled edge array which do correspond to edge pixels; and subtracting the filled edge array from the image array to create a difference array. The edge file and the difference array are then separately compressed and transmitted or stored. The original image is later reconstructed by creating a preliminary array in response to the received edge file, and adding the preliminary array to the received difference array. Filling is accomplished by solving Laplace's equation using a multi-grid technique. Contour and difference file coding techniques also are described. The techniques can be used in a method for processing a plurality of images by selecting a respective compression approach for each image, compressing each of the images according to the compression approach selected, and transmitting each of the images as compressed, in correspondence with an indication of the approach selected for the image.

Image compression technique

DOEpatents

Fu, C.Y.; Petrich, L.I.

1997-03-25

An image is compressed by identifying edge pixels of the image; creating a filled edge array of pixels each of the pixels in the filled edge array which corresponds to an edge pixel having a value equal to the value of a pixel of the image array selected in response to the edge pixel, and each of the pixels in the filled edge array which does not correspond to an edge pixel having a value which is a weighted average of the values of surrounding pixels in the filled edge array which do correspond to edge pixels; and subtracting the filled edge array from the image array to create a difference array. The edge file and the difference array are then separately compressed and transmitted or stored. The original image is later reconstructed by creating a preliminary array in response to the received edge file, and adding the preliminary array to the received difference array. Filling is accomplished by solving Laplace`s equation using a multi-grid technique. Contour and difference file coding techniques also are described. The techniques can be used in a method for processing a plurality of images by selecting a respective compression approach for each image, compressing each of the images according to the compression approach selected, and transmitting each of the images as compressed, in correspondence with an indication of the approach selected for the image. 16 figs.

Application of low-noise CID imagers in scientific instrumentation cameras

NASA Astrophysics Data System (ADS)

Carbone, Joseph; Hutton, J.; Arnold, Frank S.; Zarnowski, Jeffrey J.; Vangorden, Steven; Pilon, Michael J.; Wadsworth, Mark V.

1991-07-01

CIDTEC has developed a PC-based instrumentation camera incorporating a preamplifier per row CID imager and a microprocessor/LCA camera controller. The camera takes advantage of CID X-Y addressability to randomly read individual pixels and potentially overlapping pixel subsets in true nondestructive (NDRO) as well as destructive readout modes. Using an oxy- nitride fabricated CID and the NDRO readout technique, pixel full well and noise levels of approximately 1*10(superscript 6) and 40 electrons, respectively, were measured. Data taken from test structures indicates noise levels (which appear to be 1/f limited) can be reduced by a factor of two by eliminating the nitride under the preamplifier gate. Due to software programmability, versatile readout capabilities, wide dynamic range, and extended UV/IR capability, this camera appears to be ideally suited for use in spectroscopy and other scientific applications.

Simulating urban land cover changes at sub-pixel level in a coastal city

NASA Astrophysics Data System (ADS)

Zhao, Xiaofeng; Deng, Lei; Feng, Huihui; Zhao, Yanchuang

2014-10-01

The simulation of urban expansion or land cover changes is a major theme in both geographic information science and landscape ecology. Yet till now, almost all of previous studies were based on grid computations at pixel level. With the prevalence of spectral mixture analysis in urban land cover research, the simulation of urban land cover at sub-pixel level is being put into agenda. This study provided a new approach of land cover simulation at sub-pixel level. Landsat TM/ETM+ images of Xiamen city, China on both the January of 2002 and 2007 were used to acquire land cover data through supervised classification. Then the two classified land cover data were utilized to extract the transformation rule between 2002 and 2007 using logistic regression. The transformation possibility of each land cover type in a certain pixel was taken as its percent in the same pixel after normalization. And cellular automata (CA) based grid computation was carried out to acquire simulated land cover on 2007. The simulated 2007 sub-pixel land cover was testified with a validated sub-pixel land cover achieved by spectral mixture analysis in our previous studies on the same date. And finally the sub-pixel land cover of 2017 was simulated for urban planning and management. The results showed that our method is useful in land cover simulation at sub-pixel level. Although the simulation accuracy is not quite satisfactory for all the land cover types, it provides an important idea and a good start in the CA-based urban land cover simulation.

Pixel-based image fusion with false color mapping

NASA Astrophysics Data System (ADS)

Zhao, Wei; Mao, Shiyi

2003-06-01

In this paper, we propose a pixel-based image fusion algorithm that combines the gray-level image fusion method with the false color mapping. This algorithm integrates two gray-level images presenting different sensor modalities or at different frequencies and produces a fused false-color image. The resulting image has higher information content than each of the original images. The objects in the fused color image are easy to be recognized. This algorithm has three steps: first, obtaining the fused gray-level image of two original images; second, giving the generalized high-boost filtering images between fused gray-level image and two source images respectively; third, generating the fused false-color image. We use the hybrid averaging and selection fusion method to obtain the fused gray-level image. The fused gray-level image will provide better details than two original images and reduce noise at the same time. But the fused gray-level image can't contain all detail information in two source images. At the same time, the details in gray-level image cannot be discerned as easy as in a color image. So a color fused image is necessary. In order to create color variation and enhance details in the final fusion image, we produce three generalized high-boost filtering images. These three images are displayed through red, green and blue channel respectively. A fused color image is produced finally. This method is used to fuse two SAR images acquired on the San Francisco area (California, USA). The result shows that fused false-color image enhances the visibility of certain details. The resolution of the final false-color image is the same as the resolution of the input images.

A New Pixels Flipping Method for Huge Watermarking Capacity of the Invoice Font Image

PubMed Central

Li, Li; Hou, Qingzheng; Lu, Jianfeng; Dai, Junping; Mao, Xiaoyang; Chang, Chin-Chen

2014-01-01

Invoice printing just has two-color printing, so invoice font image can be seen as binary image. To embed watermarks into invoice image, the pixels need to be flipped. The more huge the watermark is, the more the pixels need to be flipped. We proposed a new pixels flipping method in invoice image for huge watermarking capacity. The pixels flipping method includes one novel interpolation method for binary image, one flippable pixels evaluation mechanism, and one denoising method based on gravity center and chaos degree. The proposed interpolation method ensures that the invoice image keeps features well after scaling. The flippable pixels evaluation mechanism ensures that the pixels keep better connectivity and smoothness and the pattern has highest structural similarity after flipping. The proposed denoising method makes invoice font image smoother and fiter for human vision. Experiments show that the proposed flipping method not only keeps the invoice font structure well but also improves watermarking capacity. PMID:25489606

Pneumothorax detection in chest radiographs using convolutional neural networks

NASA Astrophysics Data System (ADS)

Blumenfeld, Aviel; Konen, Eli; Greenspan, Hayit

2018-02-01

This study presents a computer assisted diagnosis system for the detection of pneumothorax (PTX) in chest radiographs based on a convolutional neural network (CNN) for pixel classification. Using a pixel classification approach allows utilization of the texture information in the local environment of each pixel while training a CNN model on millions of training patches extracted from a relatively small dataset. The proposed system uses a pre-processing step of lung field segmentation to overcome the large variability in the input images coming from a variety of imaging sources and protocols. Using a CNN classification, suspected pixel candidates are extracted within each lung segment. A postprocessing step follows to remove non-physiological suspected regions and noisy connected components. The overall percentage of suspected PTX area was used as a robust global decision for the presence of PTX in each lung. The system was trained on a set of 117 chest x-ray images with ground truth segmentations of the PTX regions. The system was tested on a set of 86 images and reached diagnosis accuracy of AUC=0.95. Overall preliminary results are promising and indicate the growing ability of CAD based systems to detect findings in medical imaging on a clinical level accuracy.

ImgLib2--generic image processing in Java.

PubMed

Pietzsch, Tobias; Preibisch, Stephan; Tomancák, Pavel; Saalfeld, Stephan

2012-11-15

ImgLib2 is an open-source Java library for n-dimensional data representation and manipulation with focus on image processing. It aims at minimizing code duplication by cleanly separating pixel-algebra, data access and data representation in memory. Algorithms can be implemented for classes of pixel types and generic access patterns by which they become independent of the specific dimensionality, pixel type and data representation. ImgLib2 illustrates that an elegant high-level programming interface can be achieved without sacrificing performance. It provides efficient implementations of common data types, storage layouts and algorithms. It is the data model underlying ImageJ2, the KNIME Image Processing toolbox and an increasing number of Fiji-Plugins. ImgLib2 is licensed under BSD. Documentation and source code are available at http://imglib2.net and in a public repository at https://github.com/imagej/imglib. Supplementary data are available at Bioinformatics Online. saalfeld@mpi-cbg.de

Subpixel target detection and enhancement in hyperspectral images

NASA Astrophysics Data System (ADS)

Tiwari, K. C.; Arora, M.; Singh, D.

2011-06-01

Hyperspectral data due to its higher information content afforded by higher spectral resolution is increasingly being used for various remote sensing applications including information extraction at subpixel level. There is however usually a lack of matching fine spatial resolution data particularly for target detection applications. Thus, there always exists a tradeoff between the spectral and spatial resolutions due to considerations of type of application, its cost and other associated analytical and computational complexities. Typically whenever an object, either manmade, natural or any ground cover class (called target, endmembers, components or class) gets spectrally resolved but not spatially, mixed pixels in the image result. Thus, numerous manmade and/or natural disparate substances may occur inside such mixed pixels giving rise to mixed pixel classification or subpixel target detection problems. Various spectral unmixing models such as Linear Mixture Modeling (LMM) are in vogue to recover components of a mixed pixel. Spectral unmixing outputs both the endmember spectrum and their corresponding abundance fractions inside the pixel. It, however, does not provide spatial distribution of these abundance fractions within a pixel. This limits the applicability of hyperspectral data for subpixel target detection. In this paper, a new inverse Euclidean distance based super-resolution mapping method has been presented that achieves subpixel target detection in hyperspectral images by adjusting spatial distribution of abundance fraction within a pixel. Results obtained at different resolutions indicate that super-resolution mapping may effectively aid subpixel target detection.

Microlens performance limits in sub-2mum pixel CMOS image sensors.

PubMed

Huo, Yijie; Fesenmaier, Christian C; Catrysse, Peter B

2010-03-15

CMOS image sensors with smaller pixels are expected to enable digital imaging systems with better resolution. When pixel size scales below 2 mum, however, diffraction affects the optical performance of the pixel and its microlens, in particular. We present a first-principles electromagnetic analysis of microlens behavior during the lateral scaling of CMOS image sensor pixels. We establish for a three-metal-layer pixel that diffraction prevents the microlens from acting as a focusing element when pixels become smaller than 1.4 microm. This severely degrades performance for on and off-axis pixels in red, green and blue color channels. We predict that one-metal-layer or backside-illuminated pixels are required to extend the functionality of microlenses beyond the 1.4 microm pixel node.

Cellular image segmentation using n-agent cooperative game theory

NASA Astrophysics Data System (ADS)

Dimock, Ian B.; Wan, Justin W. L.

2016-03-01

Image segmentation is an important problem in computer vision and has significant applications in the segmentation of cellular images. Many different imaging techniques exist and produce a variety of image properties which pose difficulties to image segmentation routines. Bright-field images are particularly challenging because of the non-uniform shape of the cells, the low contrast between cells and background, and imaging artifacts such as halos and broken edges. Classical segmentation techniques often produce poor results on these challenging images. Previous attempts at bright-field imaging are often limited in scope to the images that they segment. In this paper, we introduce a new algorithm for automatically segmenting cellular images. The algorithm incorporates two game theoretic models which allow each pixel to act as an independent agent with the goal of selecting their best labelling strategy. In the non-cooperative model, the pixels choose strategies greedily based only on local information. In the cooperative model, the pixels can form coalitions, which select labelling strategies that benefit the entire group. Combining these two models produces a method which allows the pixels to balance both local and global information when selecting their label. With the addition of k-means and active contour techniques for initialization and post-processing purposes, we achieve a robust segmentation routine. The algorithm is applied to several cell image datasets including bright-field images, fluorescent images and simulated images. Experiments show that the algorithm produces good segmentation results across the variety of datasets which differ in cell density, cell shape, contrast, and noise levels.

Theory and applications of structured light single pixel imaging

NASA Astrophysics Data System (ADS)

Stokoe, Robert J.; Stockton, Patrick A.; Pezeshki, Ali; Bartels, Randy A.

2018-02-01

Many single-pixel imaging techniques have been developed in recent years. Though the methods of image acquisition vary considerably, the methods share unifying features that make general analysis possible. Furthermore, the methods developed thus far are based on intuitive processes that enable simple and physically-motivated reconstruction algorithms, however, this approach may not leverage the full potential of single-pixel imaging. We present a general theoretical framework of single-pixel imaging based on frame theory, which enables general, mathematically rigorous analysis. We apply our theoretical framework to existing single-pixel imaging techniques, as well as provide a foundation for developing more-advanced methods of image acquisition and reconstruction. The proposed frame theoretic framework for single-pixel imaging results in improved noise robustness, decrease in acquisition time, and can take advantage of special properties of the specimen under study. By building on this framework, new methods of imaging with a single element detector can be developed to realize the full potential associated with single-pixel imaging.

Impact of defective pixels in AMLCDs on the perception of medical images

NASA Astrophysics Data System (ADS)

Kimpe, Tom; Sneyders, Yuri

2006-03-01

With LCD displays, each pixel has its own individual transistor that controls the transmittance of that pixel. Occasionally, these individual transistors will short or alternatively malfunction, resulting in a defective pixel that always shows the same brightness. With ever increasing resolution of displays the number of defect pixels per display increases accordingly. State of the art processes are capable of producing displays with no more than one faulty transistor out of 3 million. A five Mega Pixel medical LCD panel contains 15 million individual sub pixels (3 sub pixels per pixel), each having an individual transistor. This means that a five Mega Pixel display on average will have 5 failing pixels. This paper investigates the visibility of defective pixels and analyzes the possible impact of defective pixels on the perception of medical images. JND simulations were done to study the effect of defective pixels on medical images. Our results indicate that defective LCD pixels can mask subtle features in medical images in an unexpectedly broad area around the defect and therefore may reduce the quality of diagnosis for specific high-demanding areas such as mammography. As a second contribution an innovative solution is proposed. A specialized image processing algorithm can make defective pixels completely invisible and moreover can also recover the information of the defect so that the radiologist perceives the medical image correctly. This correction algorithm has been validated with both JND simulations and psycho visual tests.

iPixel: a visual content-based and semantic search engine for retrieving digitized mammograms by using collective intelligence.

PubMed

Alor-Hernández, Giner; Pérez-Gallardo, Yuliana; Posada-Gómez, Rubén; Cortes-Robles, Guillermo; Rodríguez-González, Alejandro; Aguilar-Laserre, Alberto A

2012-09-01

Nowadays, traditional search engines such as Google, Yahoo and Bing facilitate the retrieval of information in the format of images, but the results are not always useful for the users. This is mainly due to two problems: (1) the semantic keywords are not taken into consideration and (2) it is not always possible to establish a query using the image features. This issue has been covered in different domains in order to develop content-based image retrieval (CBIR) systems. The expert community has focussed their attention on the healthcare domain, where a lot of visual information for medical analysis is available. This paper provides a solution called iPixel Visual Search Engine, which involves semantics and content issues in order to search for digitized mammograms. iPixel offers the possibility of retrieving mammogram features using collective intelligence and implementing a CBIR algorithm. Our proposal compares not only features with similar semantic meaning, but also visual features. In this sense, the comparisons are made in different ways: by the number of regions per image, by maximum and minimum size of regions per image and by average intensity level of each region. iPixel Visual Search Engine supports the medical community in differential diagnoses related to the diseases of the breast. The iPixel Visual Search Engine has been validated by experts in the healthcare domain, such as radiologists, in addition to experts in digital image analysis.

A research on radiation calibration of high dynamic range based on the dual channel CMOS

NASA Astrophysics Data System (ADS)

Ma, Kai; Shi, Zhan; Pan, Xiaodong; Wang, Yongsheng; Wang, Jianghua

2017-10-01

The dual channel complementary metal-oxide semiconductor (CMOS) can get high dynamic range (HDR) image through extending the gray level of the image by using image fusion with high gain channel image and low gain channel image in a same frame. In the process of image fusion with dual channel, it adopts the coefficients of radiation response of a pixel from dual channel in a same frame, and then calculates the gray level of the pixel in the HDR image. For the coefficients of radiation response play a crucial role in image fusion, it has to find an effective method to acquire these parameters. In this article, it makes a research on radiation calibration of high dynamic range based on the dual channel CMOS, and designs an experiment to calibrate the coefficients of radiation response for the sensor it used. In the end, it applies these response parameters in the dual channel CMOS which calibrates, and verifies the correctness and feasibility of the method mentioned in this paper.

Method and System for Temporal Filtering in Video Compression Systems

NASA Technical Reports Server (NTRS)

Lu, Ligang; He, Drake; Jagmohan, Ashish; Sheinin, Vadim

2011-01-01

Three related innovations combine improved non-linear motion estimation, video coding, and video compression. The first system comprises a method in which side information is generated using an adaptive, non-linear motion model. This method enables extrapolating and interpolating a visual signal, including determining the first motion vector between the first pixel position in a first image to a second pixel position in a second image; determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image; determining a third motion vector between the first pixel position in the first image and the second pixel position in the second image, the second pixel position in the second image, and the third pixel position in the third image using a non-linear model; and determining a position of the fourth pixel in a fourth image based upon the third motion vector. For the video compression element, the video encoder has low computational complexity and high compression efficiency. The disclosed system comprises a video encoder and a decoder. The encoder converts the source frame into a space-frequency representation, estimates the conditional statistics of at least one vector of space-frequency coefficients with similar frequencies, and is conditioned on previously encoded data. It estimates an encoding rate based on the conditional statistics and applies a Slepian-Wolf code with the computed encoding rate. The method for decoding includes generating a side-information vector of frequency coefficients based on previously decoded source data and encoder statistics and previous reconstructions of the source frequency vector. It also performs Slepian-Wolf decoding of a source frequency vector based on the generated side-information and the Slepian-Wolf code bits. The video coding element includes receiving a first reference frame having a first pixel value at a first pixel position, a second reference frame having a second pixel value at a second pixel position, and a third reference frame having a third pixel value at a third pixel position. It determines a first motion vector between the first pixel position and the second pixel position, a second motion vector between the second pixel position and the third pixel position, and a fourth pixel value for a fourth frame based upon a linear or nonlinear combination of the first pixel value, the second pixel value, and the third pixel value. A stationary filtering process determines the estimated pixel values. The parameters of the filter may be predetermined constants.

On-Orbit Solar Dynamics Observatory (SDO) Star Tracker Warm Pixel Analysis

NASA Technical Reports Server (NTRS)

Felikson, Denis; Ekinci, Matthew; Hashmall, Joseph A.; Vess, Melissa

2011-01-01

This paper describes the process of identification and analysis of warm pixels in two autonomous star trackers on the Solar Dynamics Observatory (SDO) mission. A brief description of the mission orbit and attitude regimes is discussed and pertinent star tracker hardware specifications are given. Warm pixels are defined and the Quality Index parameter is introduced, which can be explained qualitatively as a manifestation of a possible warm pixel event. A description of the algorithm used to identify warm pixel candidates is given. Finally, analysis of dumps of on-orbit star tracker charge coupled devices (CCD) images is presented and an operational plan going forward is discussed. SDO, launched on February 11, 2010, is operated from the NASA Goddard Space Flight Center (GSFC). SDO is in a geosynchronous orbit with a 28.5 inclination. The nominal mission attitude points the spacecraft X-axis at the Sun, with the spacecraft Z-axis roughly aligned with the Solar North Pole. The spacecraft Y-axis completes the triad. In attitude, SDO moves approximately 0.04 per hour, mostly about the spacecraft Z-axis. The SDO star trackers, manufactured by Galileo Avionica, project the images of stars in their 16.4deg x 16.4deg fields-of-view onto CCD detectors consisting of 512 x 512 pixels. The trackers autonomously identify the star patterns and provide an attitude estimate. Each unit is able to track up to 9 stars. Additionally, each tracker calculates a parameter called the Quality Index, which is a measure of the quality of the attitude solution. Each pixel in the CCD measures the intensity of light and a warns pixel is defined as having a measurement consistently and significantly higher than the mean background intensity level. A warns pixel should also have lower intensity than a pixel containing a star image and will not move across the field of view as the attitude changes (as would a dim star image). It should be noted that the maximum error introduced in the star tracker attitude solution during suspected warm pixel corruptions is within the specified 36 attitude error budget requirement of [35, 70, 70] arcseconds. Thus, the star trackers provided attitude accuracy within the specification for SDO. The star tracker images are intentionally defocused so each star image is detected in more than one CCD pixel. The position of each star is calculated as an intensity-weighted average of the illuminated pixels. The exact method of finding the positions is proprietary to the tracker manufacturer. When a warm pixel happens to be in the vicinity of a star, it can corrupt the calculation of the position of that particular star, thereby corrupting the estimate of the attitude.

MRO's High Resolution Imaging Science Experiment (HiRISE): Polar Science Expectations

NASA Technical Reports Server (NTRS)

McEwen, A.; Herkenhoff, K.; Hansen, C.; Bridges, N.; Delamere, W. A.; Eliason, E.; Grant, J.; Gulick, V.; Keszthelyi, L.; Kirk, R.

2003-01-01

The Mars Reconnaissance Orbiter (MRO) is expected to launch in August 2005, arrive at Mars in March 2006, and begin the primary science phase in November 2006. MRO will carry a suite of remote-sensing instruments and is designed to routinely point off-nadir to precisely target locations on Mars for high-resolution observations. The mission will have a much higher data return than any previous planetary mission, with 34 Tbits of returned data expected in the first Mars year in the mapping orbit (255 x 320 km). The HiRISE camera features a 0.5 m telescope, 12 m focal length, and 14 CCDs. We expect to acquire approximately 10,000 observations in the primary science phase (approximately 1 Mars year), including approximately 2,000 images for 1,000 stereo targets. Each observation will be accompanied by a approximately 6 m/pixel image over a 30 x 45 km region acquired by MRO s context imager. Many HiRISE images will be full resolution in the center portion of the swath width and binned (typically 4x4) on the sides. This provides two levels of context, so we step out from 0.3 m/pixel to 1.2 m/pixel to 6 m/pixel (at 300 km altitude). We expect to cover approximately 1% of Mars at better than 1.2 m/pixel, approximately 0.1% at 0.3 m/pixel, approximately 0.1% in 3 colors, and approximately 0.05% in stereo. Our major challenge is to find the dey contacts, exposures and type morphologies to observe.

Weak-lensing shear estimates with general adaptive moments, and studies of bias by pixellation, PSF distortions, and noise

NASA Astrophysics Data System (ADS)

Simon, Patrick; Schneider, Peter

2017-08-01

In weak gravitational lensing, weighted quadrupole moments of the brightness profile in galaxy images are a common way to estimate gravitational shear. We have employed general adaptive moments (GLAM ) to study causes of shear bias on a fundamental level and for a practical definition of an image ellipticity. The GLAM ellipticity has useful properties for any chosen weight profile: the weighted ellipticity is identical to that of isophotes of elliptical images, and in absence of noise and pixellation it is always an unbiased estimator of reduced shear. We show that moment-based techniques, adaptive or unweighted, are similar to a model-based approach in the sense that they can be seen as imperfect fit of an elliptical profile to the image. Due to residuals in the fit, moment-based estimates of ellipticities are prone to underfitting bias when inferred from observed images. The estimation is fundamentally limited mainly by pixellation which destroys information on the original, pre-seeing image. We give an optimised estimator for the pre-seeing GLAM ellipticity and quantify its bias for noise-free images. To deal with images where pixel noise is prominent, we consider a Bayesian approach to infer GLAM ellipticity where, similar to the noise-free case, the ellipticity posterior can be inconsistent with the true ellipticity if we do not properly account for our ignorance about fit residuals. This underfitting bias, quantified in the paper, does not vary with the overall noise level but changes with the pre-seeing brightness profile and the correlation or heterogeneity of pixel noise over the image. Furthermore, when inferring a constant ellipticity or, more relevantly, constant shear from a source sample with a distribution of intrinsic properties (sizes, centroid positions, intrinsic shapes), an additional, now noise-dependent bias arises towards low signal-to-noise if incorrect prior densities for the intrinsic properties are used. We discuss the origin of this prior bias. With regard to a fully-Bayesian lensing analysis, we point out that passing tests with source samples subject to constant shear may not be sufficient for an analysis of sources with varying shear.

Signal-Conditioning Block of a 1 × 200 CMOS Detector Array for a Terahertz Real-Time Imaging System

PubMed Central

Yang, Jong-Ryul; Lee, Woo-Jae; Han, Seong-Tae

2016-01-01

A signal conditioning block of a 1 × 200 Complementary Metal-Oxide-Semiconductor (CMOS) detector array is proposed to be employed with a real-time 0.2 THz imaging system for inspecting large areas. The plasmonic CMOS detector array whose pixel size including an integrated antenna is comparable to the wavelength of the THz wave for the imaging system, inevitably carries wide pixel-to-pixel variation. To make the variant outputs from the array uniform, the proposed signal conditioning block calibrates the responsivity of each pixel by controlling the gate bias of each detector and the voltage gain of the lock-in amplifiers in the block. The gate bias of each detector is modulated to 1 MHz to improve the signal-to-noise ratio of the imaging system via the electrical modulation by the conditioning block. In addition, direct current (DC) offsets of the detectors in the array are cancelled by initializing the output voltage level from the block. Real-time imaging using the proposed signal conditioning block is demonstrated by obtaining images at the rate of 19.2 frame-per-sec of an object moving on the conveyor belt with a scan width of 20 cm and a scan speed of 25 cm/s. PMID:26950128

Signal-Conditioning Block of a 1 × 200 CMOS Detector Array for a Terahertz Real-Time Imaging System.

PubMed

Yang, Jong-Ryul; Lee, Woo-Jae; Han, Seong-Tae

2016-03-02

A signal conditioning block of a 1 × 200 Complementary Metal-Oxide-Semiconductor (CMOS) detector array is proposed to be employed with a real-time 0.2 THz imaging system for inspecting large areas. The plasmonic CMOS detector array whose pixel size including an integrated antenna is comparable to the wavelength of the THz wave for the imaging system, inevitably carries wide pixel-to-pixel variation. To make the variant outputs from the array uniform, the proposed signal conditioning block calibrates the responsivity of each pixel by controlling the gate bias of each detector and the voltage gain of the lock-in amplifiers in the block. The gate bias of each detector is modulated to 1 MHz to improve the signal-to-noise ratio of the imaging system via the electrical modulation by the conditioning block. In addition, direct current (DC) offsets of the detectors in the array are cancelled by initializing the output voltage level from the block. Real-time imaging using the proposed signal conditioning block is demonstrated by obtaining images at the rate of 19.2 frame-per-sec of an object moving on the conveyor belt with a scan width of 20 cm and a scan speed of 25 cm/s.

Automated segmentation of geographic atrophy in fundus autofluorescence images using supervised pixel classification.

PubMed

Hu, Zhihong; Medioni, Gerard G; Hernandez, Matthias; Sadda, Srinivas R

2015-01-01

Geographic atrophy (GA) is a manifestation of the advanced or late stage of age-related macular degeneration (AMD). AMD is the leading cause of blindness in people over the age of 65 in the western world. The purpose of this study is to develop a fully automated supervised pixel classification approach for segmenting GA, including uni- and multifocal patches in fundus autofluorescene (FAF) images. The image features include region-wise intensity measures, gray-level co-occurrence matrix measures, and Gaussian filter banks. A [Formula: see text]-nearest-neighbor pixel classifier is applied to obtain a GA probability map, representing the likelihood that the image pixel belongs to GA. Sixteen randomly chosen FAF images were obtained from 16 subjects with GA. The algorithm-defined GA regions are compared with manual delineation performed by a certified image reading center grader. Eight-fold cross-validation is applied to evaluate the algorithm performance. The mean overlap ratio (OR), area correlation (Pearson's [Formula: see text]), accuracy (ACC), true positive rate (TPR), specificity (SPC), positive predictive value (PPV), and false discovery rate (FDR) between the algorithm- and manually defined GA regions are [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text], respectively.

Computational imaging with a single-pixel detector and a consumer video projector

NASA Astrophysics Data System (ADS)

Sych, D.; Aksenov, M.

2018-02-01

Single-pixel imaging is a novel rapidly developing imaging technique that employs spatially structured illumination and a single-pixel detector. In this work, we experimentally demonstrate a fully operating modular single-pixel imaging system. Light patterns in our setup are created with help of a computer-controlled digital micromirror device from a consumer video projector. We investigate how different working modes and settings of the projector affect the quality of reconstructed images. We develop several image reconstruction algorithms and compare their performance for real imaging. Also, we discuss the potential use of the single-pixel imaging system for quantum applications.

Obstacle Detection Algorithms for Rotorcraft Navigation

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar; Camps, Octavia I.; Huang, Ying; Narasimhamurthy, Anand; Pande, Nitin; Ahumada, Albert (Technical Monitor)

2001-01-01

In this research we addressed the problem of obstacle detection for low altitude rotorcraft flight. In particular, the problem of detecting thin wires in the presence of image clutter and noise was studied. Wires present a serious hazard to rotorcrafts. Since they are very thin, their detection early enough so that the pilot has enough time to take evasive action is difficult, as their images can be less than one or two pixels wide. After reviewing the line detection literature, an algorithm for sub-pixel edge detection proposed by Steger was identified as having good potential to solve the considered task. The algorithm was tested using a set of images synthetically generated by combining real outdoor images with computer generated wire images. The performance of the algorithm was evaluated both, at the pixel and the wire levels. It was observed that the algorithm performs well, provided that the wires are not too thin (or distant) and that some post processing is performed to remove false alarms due to clutter.

Fluorescence imaging to quantify crop residue cover

NASA Technical Reports Server (NTRS)

Daughtry, C. S. T.; Mcmurtrey, J. E., III; Chappelle, E. W.

1994-01-01

Crop residues, the portion of the crop left in the field after harvest, can be an important management factor in controlling soil erosion. Methods to quantify residue cover are needed that are rapid, accurate, and objective. Scenes with known amounts of crop residue were illuminated with long wave ultraviolet (UV) radiation and fluorescence images were recorded with an intensified video camera fitted with a 453 to 488 nm band pass filter. A light colored soil and a dark colored soil were used as background for the weathered soybean stems. Residue cover was determined by counting the proportion of the pixels in the image with fluorescence values greater than a threshold. Soil pixels had the lowest gray levels in the images. The values of the soybean residue pixels spanned nearly the full range of the 8-bit video data. Classification accuracies typically were within 3(absolute units) of measured cover values. Video imaging can provide an intuitive understanding of the fraction of the soil covered by residue.

Enhancement of low light level images using color-plus-mono dual camera.

PubMed

Jung, Yong Ju

2017-05-15

In digital photography, the improvement of imaging quality in low light shooting is one of the users' needs. Unfortunately, conventional smartphone cameras that use a single, small image sensor cannot provide satisfactory quality in low light level images. A color-plus-mono dual camera that consists of two horizontally separate image sensors, which simultaneously captures both a color and mono image pair of the same scene, could be useful for improving the quality of low light level images. However, an incorrect image fusion between the color and mono image pair could also have negative effects, such as the introduction of severe visual artifacts in the fused images. This paper proposes a selective image fusion technique that applies an adaptive guided filter-based denoising and selective detail transfer to only those pixels deemed reliable with respect to binocular image fusion. We employ a dissimilarity measure and binocular just-noticeable-difference (BJND) analysis to identify unreliable pixels that are likely to cause visual artifacts during image fusion via joint color image denoising and detail transfer from the mono image. By constructing an experimental system of color-plus-mono camera, we demonstrate that the BJND-aware denoising and selective detail transfer is helpful in improving the image quality during low light shooting.

Threshold selection for classification of MR brain images by clustering method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moldovanu, Simona; Dumitru Moţoc High School, 15 Milcov St., 800509, Galaţi; Obreja, Cristian

Given a grey-intensity image, our method detects the optimal threshold for a suitable binarization of MR brain images. In MR brain image processing, the grey levels of pixels belonging to the object are not substantially different from the grey levels belonging to the background. Threshold optimization is an effective tool to separate objects from the background and further, in classification applications. This paper gives a detailed investigation on the selection of thresholds. Our method does not use the well-known method for binarization. Instead, we perform a simple threshold optimization which, in turn, will allow the best classification of the analyzedmore » images into healthy and multiple sclerosis disease. The dissimilarity (or the distance between classes) has been established using the clustering method based on dendrograms. We tested our method using two classes of images: the first consists of 20 T2-weighted and 20 proton density PD-weighted scans from two healthy subjects and from two patients with multiple sclerosis. For each image and for each threshold, the number of the white pixels (or the area of white objects in binary image) has been determined. These pixel numbers represent the objects in clustering operation. The following optimum threshold values are obtained, T = 80 for PD images and T = 30 for T2w images. Each mentioned threshold separate clearly the clusters that belonging of the studied groups, healthy patient and multiple sclerosis disease.« less

Sub-pixel image classification for forest types in East Texas

NASA Astrophysics Data System (ADS)

Westbrook, Joey

Sub-pixel classification is the extraction of information about the proportion of individual materials of interest within a pixel. Landcover classification at the sub-pixel scale provides more discrimination than traditional per-pixel multispectral classifiers for pixels where the material of interest is mixed with other materials. It allows for the un-mixing of pixels to show the proportion of each material of interest. The materials of interest for this study are pine, hardwood, mixed forest and non-forest. The goal of this project was to perform a sub-pixel classification, which allows a pixel to have multiple labels, and compare the result to a traditional supervised classification, which allows a pixel to have only one label. The satellite image used was a Landsat 5 Thematic Mapper (TM) scene of the Stephen F. Austin Experimental Forest in Nacogdoches County, Texas and the four cover type classes are pine, hardwood, mixed forest and non-forest. Once classified, a multi-layer raster datasets was created that comprised four raster layers where each layer showed the percentage of that cover type within the pixel area. Percentage cover type maps were then produced and the accuracy of each was assessed using a fuzzy error matrix for the sub-pixel classifications, and the results were compared to the supervised classification in which a traditional error matrix was used. The overall accuracy of the sub-pixel classification using the aerial photo for both training and reference data had the highest (65% overall) out of the three sub-pixel classifications. This was understandable because the analyst can visually observe the cover types actually on the ground for training data and reference data, whereas using the FIA (Forest Inventory and Analysis) plot data, the analyst must assume that an entire pixel contains the exact percentage of a cover type found in a plot. An increase in accuracy was found after reclassifying each sub-pixel classification from nine classes with 10 percent interval each to five classes with 20 percent interval each. When compared to the supervised classification which has a satisfactory overall accuracy of 90%, none of the sub-pixel classification achieved the same level. However, since traditional per-pixel classifiers assign only one label to pixels throughout the landscape while sub-pixel classifications assign multiple labels to each pixel, the traditional 85% accuracy of acceptance for pixel-based classifications should not apply to sub-pixel classifications. More research is needed in order to define the level of accuracy that is deemed acceptable for sub-pixel classifications.

A time-resolved image sensor for tubeless streak cameras

NASA Astrophysics Data System (ADS)

Yasutomi, Keita; Han, SangMan; Seo, Min-Woong; Takasawa, Taishi; Kagawa, Keiichiro; Kawahito, Shoji

2014-03-01

This paper presents a time-resolved CMOS image sensor with draining-only modulation (DOM) pixels for tube-less streak cameras. Although the conventional streak camera has high time resolution, the device requires high voltage and bulky system due to the structure with a vacuum tube. The proposed time-resolved imager with a simple optics realize a streak camera without any vacuum tubes. The proposed image sensor has DOM pixels, a delay-based pulse generator, and a readout circuitry. The delay-based pulse generator in combination with an in-pixel logic allows us to create and to provide a short gating clock to the pixel array. A prototype time-resolved CMOS image sensor with the proposed pixel is designed and implemented using 0.11um CMOS image sensor technology. The image array has 30(Vertical) x 128(Memory length) pixels with the pixel pitch of 22.4um. .

Alignment by Maximization of Mutual Information

DTIC Science & Technology

1995-06-01

Davi Geiger, David Chapman, Jose Robles, Tao Alter, Misha Bolotski, Jonathan Connel, Karen Sarachik, Maja Mataric , Ian Horswill, Colin Angle...the same pose. These images are very different and are in fact anti-correlated: bright pixels in the left image correspond to dark pixels in the right...image; dark pixels in the left image correspond to bright pixels in the right image. No variant of correlation could match these images together

Technique for ship/wake detection

DOEpatents

Roskovensky, John K [Albuquerque, NM

2012-05-01

An automated ship detection technique includes accessing data associated with an image of a portion of Earth. The data includes reflectance values. A first portion of pixels within the image are masked with a cloud and land mask based on spectral flatness of the reflectance values associated with the pixels. A given pixel selected from the first portion of pixels is unmasked when a threshold number of localized pixels surrounding the given pixel are not masked by the cloud and land mask. A spatial variability image is generated based on spatial derivatives of the reflectance values of the pixels which remain unmasked by the cloud and land mask. The spatial variability image is thresholded to identify one or more regions within the image as possible ship detection regions.

Integrated sensor with frame memory and programmable resolution for light adaptive imaging

NASA Technical Reports Server (NTRS)

Zhou, Zhimin (Inventor); Fossum, Eric R. (Inventor); Pain, Bedabrata (Inventor)

2004-01-01

An image sensor operable to vary the output spatial resolution according to a received light level while maintaining a desired signal-to-noise ratio. Signals from neighboring pixels in a pixel patch with an adjustable size are added to increase both the image brightness and signal-to-noise ratio. One embodiment comprises a sensor array for receiving input signals, a frame memory array for temporarily storing a full frame, and an array of self-calibration column integrators for uniform column-parallel signal summation. The column integrators are capable of substantially canceling fixed pattern noise.

Active pixel imagers incorporating pixel-level amplifiers based on polycrystalline-silicon thin-film transistors

PubMed Central

El-Mohri, Youcef; Antonuk, Larry E.; Koniczek, Martin; Zhao, Qihua; Li, Yixin; Street, Robert A.; Lu, Jeng-Ping

2009-01-01

Active matrix, flat-panel imagers (AMFPIs) employing a 2D matrix of a-Si addressing TFTs have become ubiquitous in many x-ray imaging applications due to their numerous advantages. However, under conditions of low exposures and∕or high spatial resolution, their signal-to-noise performance is constrained by the modest system gain relative to the electronic additive noise. In this article, a strategy for overcoming this limitation through the incorporation of in-pixel amplification circuits, referred to as active pixel (AP) architectures, using polycrystalline-silicon (poly-Si) TFTs is reported. Compared to a-Si, poly-Si offers substantially higher mobilities, enabling higher TFT currents and the possibility of sophisticated AP designs based on both n- and p-channel TFTs. Three prototype indirect detection arrays employing poly-Si TFTs and a continuous a-Si photodiode structure were characterized. The prototypes consist of an array (PSI-1) that employs a pixel architecture with a single TFT, as well as two arrays (PSI-2 and PSI-3) that employ AP architectures based on three and five TFTs, respectively. While PSI-1 serves as a reference with a design similar to that of conventional AMFPI arrays, PSI-2 and PSI-3 incorporate additional in-pixel amplification circuitry. Compared to PSI-1, results of x-ray sensitivity demonstrate signal gains of ∼10.7 and 20.9 for PSI-2 and PSI-3, respectively. These values are in reasonable agreement with design expectations, demonstrating that poly-Si AP circuits can be tailored to provide a desired level of signal gain. PSI-2 exhibits the same high levels of charge trapping as those observed for PSI-1 and other conventional arrays employing a continuous photodiode structure. For PSI-3, charge trapping was found to be significantly lower and largely independent of the bias voltage applied across the photodiode. MTF results indicate that the use of a continuous photodiode structure in PSI-1, PSI-2, and PSI-3 results in optical fill factors that are close to unity. In addition, the greater complexity of PSI-2 and PSI-3 pixel circuits, compared to that of PSI-1, has no observable effect on spatial resolution. Both PSI-2 and PSI-3 exhibit high levels of additive noise, resulting in no net improvement in the signal-to-noise performance of these early prototypes compared to conventional AMFPIs. However, faster readout rates, coupled with implementation of multiple sampling protocols allowed by the nondestructive nature of pixel readout, resulted in a significantly lower noise level of ∼560 e (rms) for PSI-3. PMID:19673229

Active pixel imagers incorporating pixel-level amplifiers based on polycrystalline-silicon thin-film transistors.

PubMed

El-Mohri, Youcef; Antonuk, Larry E; Koniczek, Martin; Zhao, Qihua; Li, Yixin; Street, Robert A; Lu, Jeng-Ping

2009-07-01

Active matrix, flat-panel imagers (AMFPIs) employing a 2D matrix of a-Si addressing TFTs have become ubiquitous in many x-ray imaging applications due to their numerous advantages. However, under conditions of low exposures and/or high spatial resolution, their signal-to-noise performance is constrained by the modest system gain relative to the electronic additive noise. In this article, a strategy for overcoming this limitation through the incorporation of in-pixel amplification circuits, referred to as active pixel (AP) architectures, using polycrystalline-silicon (poly-Si) TFTs is reported. Compared to a-Si, poly-Si offers substantially higher mobilities, enabling higher TFT currents and the possibility of sophisticated AP designs based on both n- and p-channel TFTs. Three prototype indirect detection arrays employing poly-Si TFTs and a continuous a-Si photodiode structure were characterized. The prototypes consist of an array (PSI-1) that employs a pixel architecture with a single TFT, as well as two arrays (PSI-2 and PSI-3) that employ AP architectures based on three and five TFTs, respectively. While PSI-1 serves as a reference with a design similar to that of conventional AMFPI arrays, PSI-2 and PSI-3 incorporate additional in-pixel amplification circuitry. Compared to PSI-1, results of x-ray sensitivity demonstrate signal gains of approximately 10.7 and 20.9 for PSI-2 and PSI-3, respectively. These values are in reasonable agreement with design expectations, demonstrating that poly-Si AP circuits can be tailored to provide a desired level of signal gain. PSI-2 exhibits the same high levels of charge trapping as those observed for PSI-1 and other conventional arrays employing a continuous photodiode structure. For PSI-3, charge trapping was found to be significantly lower and largely independent of the bias voltage applied across the photodiode. MTF results indicate that the use of a continuous photodiode structure in PSI-1, PSI-2, and PSI-3 results in optical fill factors that are close to unity. In addition, the greater complexity of PSI-2 and PSI-3 pixel circuits, compared to that of PSI-1, has no observable effect on spatial resolution. Both PSI-2 and PSI-3 exhibit high levels of additive noise, resulting in no net improvement in the signal-to-noise performance of these early prototypes compared to conventional AMFPIs. However, faster readout rates, coupled with implementation of multiple sampling protocols allowed by the nondestructive nature of pixel readout, resulted in a significantly lower noise level of approximately 560 e (rms) for PSI-3.

Fast single image dehazing based on image fusion

NASA Astrophysics Data System (ADS)

Liu, Haibo; Yang, Jie; Wu, Zhengping; Zhang, Qingnian

2015-01-01

Images captured in foggy weather conditions often fade the colors and reduce the contrast of the observed objects. An efficient image fusion method is proposed to remove haze from a single input image. First, the initial medium transmission is estimated based on the dark channel prior. Second, the method adopts an assumption that the degradation level affected by haze of each region is the same, which is similar to the Retinex theory, and uses a simple Gaussian filter to get the coarse medium transmission. Then, pixel-level fusion is achieved between the initial medium transmission and coarse medium transmission. The proposed method can recover a high-quality haze-free image based on the physical model, and the complexity of the proposed method is only a linear function of the number of input image pixels. Experimental results demonstrate that the proposed method can allow a very fast implementation and achieve better restoration for visibility and color fidelity compared to some state-of-the-art methods.

Steganography on quantum pixel images using Shannon entropy

NASA Astrophysics Data System (ADS)

Laurel, Carlos Ortega; Dong, Shi-Hai; Cruz-Irisson, M.

2016-07-01

This paper presents a steganographical algorithm based on least significant bit (LSB) from the most significant bit information (MSBI) and the equivalence of a bit pixel image to a quantum pixel image, which permits to make the information communicate secretly onto quantum pixel images for its secure transmission through insecure channels. This algorithm offers higher security since it exploits the Shannon entropy for an image.

Thermal wake/vessel detection technique

DOEpatents

Roskovensky, John K [Albuquerque, NM; Nandy, Prabal [Albuquerque, NM; Post, Brian N [Albuquerque, NM

2012-01-10

A computer-automated method for detecting a vessel in water based on an image of a portion of Earth includes generating a thermal anomaly mask. The thermal anomaly mask flags each pixel of the image initially deemed to be a wake pixel based on a comparison of a thermal value of each pixel against other thermal values of other pixels localized about each pixel. Contiguous pixels flagged by the thermal anomaly mask are grouped into pixel clusters. A shape of each of the pixel clusters is analyzed to determine whether each of the pixel clusters represents a possible vessel detection event. The possible vessel detection events are represented visually within the image.

Crown-level tree species classification from AISA hyperspectral imagery using an innovative pixel-weighting approach

NASA Astrophysics Data System (ADS)

Liu, Haijian; Wu, Changshan

2018-06-01

Crown-level tree species classification is a challenging task due to the spectral similarity among different tree species. Shadow, underlying objects, and other materials within a crown may decrease the purity of extracted crown spectra and further reduce classification accuracy. To address this problem, an innovative pixel-weighting approach was developed for tree species classification at the crown level. The method utilized high density discrete LiDAR data for individual tree delineation and Airborne Imaging Spectrometer for Applications (AISA) hyperspectral imagery for pure crown-scale spectra extraction. Specifically, three steps were included: 1) individual tree identification using LiDAR data, 2) pixel-weighted representative crown spectra calculation using hyperspectral imagery, with which pixel-based illuminated-leaf fractions estimated using a linear spectral mixture analysis (LSMA) were employed as weighted factors, and 3) representative spectra based tree species classification was performed through applying a support vector machine (SVM) approach. Analysis of results suggests that the developed pixel-weighting approach (OA = 82.12%, Kc = 0.74) performed better than treetop-based (OA = 70.86%, Kc = 0.58) and pixel-majority methods (OA = 72.26, Kc = 0.62) in terms of classification accuracy. McNemar tests indicated the differences in accuracy between pixel-weighting and treetop-based approaches as well as that between pixel-weighting and pixel-majority approaches were statistically significant.

Fast Fiber-Coupled Imaging Devices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brockington, Samuel; Case, Andrew; Witherspoon, Franklin Douglas

HyperV Technologies Corp. has successfully designed, built and experimentally demonstrated a full scale 1024 pixel 100 MegaFrames/s fiber coupled camera with 12 or 14 bits, and record lengths of 32K frames, exceeding our original performance objectives. This high-pixel-count, fiber optically-coupled, imaging diagnostic can be used for investigating fast, bright plasma events. In Phase 1 of this effort, a 100 pixel fiber-coupled fast streak camera for imaging plasma jet profiles was constructed and successfully demonstrated. The resulting response from outside plasma physics researchers emphasized development of increased pixel performance as a higher priority over increasing pixel count. In this Phase 2more » effort, HyperV therefore focused on increasing the sample rate and bit-depth of the photodiode pixel designed in Phase 1, while still maintaining a long record length and holding the cost per channel to levels which allowed up to 1024 pixels to be constructed. Cost per channel was 53.31 dollars, very close to our original target of $50 per channel. The system consists of an imaging "camera head" coupled to a photodiode bank with an array of optical fibers. The output of these fast photodiodes is then digitized at 100 Megaframes per second and stored in record lengths of 32,768 samples with bit depths of 12 to 14 bits per pixel. Longer record lengths are possible with additional memory. A prototype imaging system with up to 1024 pixels was designed and constructed and used to successfully take movies of very fast moving plasma jets as a demonstration of the camera performance capabilities. Some faulty electrical components on the 64 circuit boards resulted in only 1008 functional channels out of 1024 on this first generation prototype system. We experimentally observed backlit high speed fan blades in initial camera testing and then followed that with full movies and streak images of free flowing high speed plasma jets (at 30-50 km/s). Jet structure and jet collisions onto metal pillars in the path of the plasma jets were recorded in a single shot. This new fast imaging system is an attractive alternative to conventional fast framing cameras for applications and experiments where imaging events using existing techniques are inefficient or impossible. The development of HyperV's new diagnostic was split into two tracks: a next generation camera track, in which HyperV built, tested, and demonstrated a prototype 1024 channel camera at its own facility, and a second plasma community beta test track, where selected plasma physics programs received small systems of a few test pixels to evaluate the expected performance of a full scale camera on their experiments. These evaluations were performed as part of an unfunded collaboration with researchers at Los Alamos National Laboratory and the University of California at Davis. Results from the prototype 1024-pixel camera are discussed, as well as results from the collaborations with test pixel system deployment sites.« less

Vision Sensors and Cameras

NASA Astrophysics Data System (ADS)

Hoefflinger, Bernd

Silicon charge-coupled-device (CCD) imagers have been and are a specialty market ruled by a few companies for decades. Based on CMOS technologies, active-pixel sensors (APS) began to appear in 1990 at the 1 μm technology node. These pixels allow random access, global shutters, and they are compatible with focal-plane imaging systems combining sensing and first-level image processing. The progress towards smaller features and towards ultra-low leakage currents has provided reduced dark currents and μm-size pixels. All chips offer Mega-pixel resolution, and many have very high sensitivities equivalent to ASA 12.800. As a result, HDTV video cameras will become a commodity. Because charge-integration sensors suffer from a limited dynamic range, significant processing effort is spent on multiple exposure and piece-wise analog-digital conversion to reach ranges >10,000:1. The fundamental alternative is log-converting pixels with an eye-like response. This offers a range of almost a million to 1, constant contrast sensitivity and constant colors, important features in professional, technical and medical applications. 3D retino-morphic stacking of sensing and processing on top of each other is being revisited with sub-100 nm CMOS circuits and with TSV technology. With sensor outputs directly on top of neurons, neural focal-plane processing will regain momentum, and new levels of intelligent vision will be achieved. The industry push towards thinned wafers and TSV enables backside-illuminated and other pixels with a 100% fill-factor. 3D vision, which relies on stereo or on time-of-flight, high-speed circuitry, will also benefit from scaled-down CMOS technologies both because of their size as well as their higher speed.

Terahertz imaging with compressive sensing

NASA Astrophysics Data System (ADS)

Chan, Wai Lam

Most existing terahertz imaging systems are generally limited by slow image acquisition due to mechanical raster scanning. Other systems using focal plane detector arrays can acquire images in real time, but are either too costly or limited by low sensitivity in the terahertz frequency range. To design faster and more cost-effective terahertz imaging systems, the first part of this thesis proposes two new terahertz imaging schemes based on compressive sensing (CS). Both schemes can acquire amplitude and phase-contrast images efficiently with a single-pixel detector, thanks to the powerful CS algorithms which enable the reconstruction of N-by- N pixel images with much fewer than N2 measurements. The first CS Fourier imaging approach successfully reconstructs a 64x64 image of an object with pixel size 1.4 mm using a randomly chosen subset of the 4096 pixels which defines the image in the Fourier plane. Only about 12% of the pixels are required for reassembling the image of a selected object, equivalent to a 2/3 reduction in acquisition time. The second approach is single-pixel CS imaging, which uses a series of random masks for acquisition. Besides speeding up acquisition with a reduced number of measurements, the single-pixel system can further cut down acquisition time by electrical or optical spatial modulation of random patterns. In order to switch between random patterns at high speed in the single-pixel imaging system, the second part of this thesis implements a multi-pixel electrical spatial modulator for terahertz beams using active terahertz metamaterials. The first generation of this device consists of a 4x4 pixel array, where each pixel is an array of sub-wavelength-sized split-ring resonator elements fabricated on a semiconductor substrate, and is independently controlled by applying an external voltage. The spatial modulator has a uniform modulation depth of around 40 percent across all pixels, and negligible crosstalk, at the resonant frequency. The second-generation spatial terahertz modulator, also based on metamaterials with a higher resolution (32x32), is under development. A FPGA-based circuit is designed to control the large number of modulator pixels. Once fully implemented, this second-generation device will enable fast terahertz imaging with both pulsed and continuous-wave terahertz sources.

Twofold processing for denoising ultrasound medical images.

PubMed

Kishore, P V V; Kumar, K V V; Kumar, D Anil; Prasad, M V D; Goutham, E N D; Rahul, R; Krishna, C B S Vamsi; Sandeep, Y

2015-01-01

Ultrasound medical (US) imaging non-invasively pictures inside of a human body for disease diagnostics. Speckle noise attacks ultrasound images degrading their visual quality. A twofold processing algorithm is proposed in this work to reduce this multiplicative speckle noise. First fold used block based thresholding, both hard (BHT) and soft (BST), on pixels in wavelet domain with 8, 16, 32 and 64 non-overlapping block sizes. This first fold process is a better denoising method for reducing speckle and also inducing object of interest blurring. The second fold process initiates to restore object boundaries and texture with adaptive wavelet fusion. The degraded object restoration in block thresholded US image is carried through wavelet coefficient fusion of object in original US mage and block thresholded US image. Fusion rules and wavelet decomposition levels are made adaptive for each block using gradient histograms with normalized differential mean (NDF) to introduce highest level of contrast between the denoised pixels and the object pixels in the resultant image. Thus the proposed twofold methods are named as adaptive NDF block fusion with hard and soft thresholding (ANBF-HT and ANBF-ST). The results indicate visual quality improvement to an interesting level with the proposed twofold processing, where the first fold removes noise and second fold restores object properties. Peak signal to noise ratio (PSNR), normalized cross correlation coefficient (NCC), edge strength (ES), image quality Index (IQI) and structural similarity index (SSIM), measure the quantitative quality of the twofold processing technique. Validation of the proposed method is done by comparing with anisotropic diffusion (AD), total variational filtering (TVF) and empirical mode decomposition (EMD) for enhancement of US images. The US images are provided by AMMA hospital radiology labs at Vijayawada, India.

Automatic Feature Detection, Description and Matching from Mobile Laser Scanning Data and Aerial Imagery

NASA Astrophysics Data System (ADS)

Hussnain, Zille; Oude Elberink, Sander; Vosselman, George

2016-06-01

In mobile laser scanning systems, the platform's position is measured by GNSS and IMU, which is often not reliable in urban areas. Consequently, derived Mobile Laser Scanning Point Cloud (MLSPC) lacks expected positioning reliability and accuracy. Many of the current solutions are either semi-automatic or unable to achieve pixel level accuracy. We propose an automatic feature extraction method which involves utilizing corresponding aerial images as a reference data set. The proposed method comprise three steps; image feature detection, description and matching between corresponding patches of nadir aerial and MLSPC ortho images. In the data pre-processing step the MLSPC is patch-wise cropped and converted to ortho images. Furthermore, each aerial image patch covering the area of the corresponding MLSPC patch is also cropped from the aerial image. For feature detection, we implemented an adaptive variant of Harris-operator to automatically detect corner feature points on the vertices of road markings. In feature description phase, we used the LATCH binary descriptor, which is robust to data from different sensors. For descriptor matching, we developed an outlier filtering technique, which exploits the arrangements of relative Euclidean-distances and angles between corresponding sets of feature points. We found that the positioning accuracy of the computed correspondence has achieved the pixel level accuracy, where the image resolution is 12cm. Furthermore, the developed approach is reliable when enough road markings are available in the data sets. We conclude that, in urban areas, the developed approach can reliably extract features necessary to improve the MLSPC accuracy to pixel level.

Automatic optimal filament segmentation with sub-pixel accuracy using generalized linear models and B-spline level-sets.

PubMed

Xiao, Xun; Geyer, Veikko F; Bowne-Anderson, Hugo; Howard, Jonathon; Sbalzarini, Ivo F

2016-08-01

Biological filaments, such as actin filaments, microtubules, and cilia, are often imaged using different light-microscopy techniques. Reconstructing the filament curve from the acquired images constitutes the filament segmentation problem. Since filaments have lower dimensionality than the image itself, there is an inherent trade-off between tracing the filament with sub-pixel accuracy and avoiding noise artifacts. Here, we present a globally optimal filament segmentation method based on B-spline vector level-sets and a generalized linear model for the pixel intensity statistics. We show that the resulting optimization problem is convex and can hence be solved with global optimality. We introduce a simple and efficient algorithm to compute such optimal filament segmentations, and provide an open-source implementation as an ImageJ/Fiji plugin. We further derive an information-theoretic lower bound on the filament segmentation error, quantifying how well an algorithm could possibly do given the information in the image. We show that our algorithm asymptotically reaches this bound in the spline coefficients. We validate our method in comprehensive benchmarks, compare with other methods, and show applications from fluorescence, phase-contrast, and dark-field microscopy. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

A digital pixel cell for address event representation image convolution processing

NASA Astrophysics Data System (ADS)

Camunas-Mesa, Luis; Acosta-Jimenez, Antonio; Serrano-Gotarredona, Teresa; Linares-Barranco, Bernabe

2005-06-01

Address Event Representation (AER) is an emergent neuromorphic interchip communication protocol that allows for real-time virtual massive connectivity between huge number of neurons located on different chips. By exploiting high speed digital communication circuits (with nano-seconds timings), synaptic neural connections can be time multiplexed, while neural activity signals (with mili-seconds timings) are sampled at low frequencies. Also, neurons generate events according to their information levels. Neurons with more information (activity, derivative of activities, contrast, motion, edges,...) generate more events per unit time, and access the interchip communication channel more frequently, while neurons with low activity consume less communication bandwidth. AER technology has been used and reported for the implementation of various type of image sensors or retinae: luminance with local agc, contrast retinae, motion retinae,... Also, there has been a proposal for realizing programmable kernel image convolution chips. Such convolution chips would contain an array of pixels that perform weighted addition of events. Once a pixel has added sufficient event contributions to reach a fixed threshold, the pixel fires an event, which is then routed out of the chip for further processing. Such convolution chips have been proposed to be implemented using pulsed current mode mixed analog and digital circuit techniques. In this paper we present a fully digital pixel implementation to perform the weighted additions and fire the events. This way, for a given technology, there is a fully digital implementation reference against which compare the mixed signal implementations. We have designed, implemented and tested a fully digital AER convolution pixel. This pixel will be used to implement a full AER convolution chip for programmable kernel image convolution processing.

Method and apparatus for detecting a desired behavior in digital image data

DOEpatents

Kegelmeyer, Jr., W. Philip

1997-01-01

A method for detecting stellate lesions in digitized mammographic image data includes the steps of prestoring a plurality of reference images, calculating a plurality of features for each of the pixels of the reference images, and creating a binary decision tree from features of randomly sampled pixels from each of the reference images. Once the binary decision tree has been created, a plurality of features, preferably including an ALOE feature (analysis of local oriented edges), are calculated for each of the pixels of the digitized mammographic data. Each of these plurality of features of each pixel are input into the binary decision tree and a probability is determined, for each of the pixels, corresponding to the likelihood of the presence of a stellate lesion, to create a probability image. Finally, the probability image is spatially filtered to enforce local consensus among neighboring pixels and the spatially filtered image is output.

Method and apparatus for detecting a desired behavior in digital image data

DOEpatents

Kegelmeyer, Jr., W. Philip

1997-01-01

A method for detecting stellate lesions in digitized mammographic image data includes the steps of prestoring a plurality of reference images, calculating a plurality of features for each of the pixels of the reference images, and creating a binary decision tree from features of randomly sampled pixels from each of the reference images. Once the binary decision tree has been created, a plurality of features, preferably including an ALOE feature (analysis of local oriented edges), are calculated for each of the pixels of the digitized mammographic data. Each of these plurality of features of each pixel are input into the binary decision tree and a probability is determined, for each of the pixels, corresponding to the likelihood of the presence of a stellate lesion, to create a probability image. Finally, the probability image is spacially filtered to enforce local consensus among neighboring pixels and the spacially filtered image is output.

Dependence of Adaptive Cross-correlation Algorithm Performance on the Extended Scene Image Quality

NASA Technical Reports Server (NTRS)

Sidick, Erkin

2008-01-01

Recently, we reported an adaptive cross-correlation (ACC) algorithm to estimate with high accuracy the shift as large as several pixels between two extended-scene sub-images captured by a Shack-Hartmann wavefront sensor. It determines the positions of all extended-scene image cells relative to a reference cell in the same frame using an FFT-based iterative image-shifting algorithm. It works with both point-source spot images as well as extended scene images. We have demonstrated previously based on some measured images that the ACC algorithm can determine image shifts with as high an accuracy as 0.01 pixel for shifts as large 3 pixels, and yield similar results for both point source spot images and extended scene images. The shift estimate accuracy of the ACC algorithm depends on illumination level, background, and scene content in addition to the amount of the shift between two image cells. In this paper we investigate how the performance of the ACC algorithm depends on the quality and the frequency content of extended scene images captured by a Shack-Hatmann camera. We also compare the performance of the ACC algorithm with those of several other approaches, and introduce a failsafe criterion for the ACC algorithm-based extended scene Shack-Hatmann sensors.

Error analysis of filtering operations in pixel-duplicated images of diabetic retinopathy

NASA Astrophysics Data System (ADS)

Mehrubeoglu, Mehrube; McLauchlan, Lifford

2010-08-01

In this paper, diabetic retinopathy is chosen for a sample target image to demonstrate the effectiveness of image enlargement through pixel duplication in identifying regions of interest. Pixel duplication is presented as a simpler alternative to data interpolation techniques for detecting small structures in the images. A comparative analysis is performed on different image processing schemes applied to both original and pixel-duplicated images. Structures of interest are detected and and classification parameters optimized for minimum false positive detection in the original and enlarged retinal pictures. The error analysis demonstrates the advantages as well as shortcomings of pixel duplication in image enhancement when spatial averaging operations (smoothing filters) are also applied.

Bit-level plane image encryption based on coupled map lattice with time-varying delay

NASA Astrophysics Data System (ADS)

Lv, Xiupin; Liao, Xiaofeng; Yang, Bo

2018-04-01

Most of the existing image encryption algorithms had two basic properties: confusion and diffusion in a pixel-level plane based on various chaotic systems. Actually, permutation in a pixel-level plane could not change the statistical characteristics of an image, and many of the existing color image encryption schemes utilized the same method to encrypt R, G and B components, which means that the three color components of a color image are processed three times independently. Additionally, dynamical performance of a single chaotic system degrades greatly with finite precisions in computer simulations. In this paper, a novel coupled map lattice with time-varying delay therefore is applied in color images bit-level plane encryption to solve the above issues. Spatiotemporal chaotic system with both much longer period in digitalization and much excellent performances in cryptography is recommended. Time-varying delay embedded in coupled map lattice enhances dynamical behaviors of the system. Bit-level plane image encryption algorithm has greatly reduced the statistical characteristics of an image through the scrambling processing. The R, G and B components cross and mix with one another, which reduces the correlation among the three components. Finally, simulations are carried out and all the experimental results illustrate that the proposed image encryption algorithm is highly secure, and at the same time, also demonstrates superior performance.

Binarization of Gray-Scaled Digital Images Via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominquez, Jesus A.; Klinko, Steve; Voska, Ned (Technical Monitor)

2002-01-01

A new fast-computational technique based on fuzzy entropy measure has been developed to find an optimal binary image threshold. In this method, the image pixel membership functions are dependent on the threshold value and reflect the distribution of pixel values in two classes; thus, this technique minimizes the classification error. This new method is compared with two of the best-known threshold selection techniques, Otsu and Huang-Wang. The performance of the proposed method supersedes the performance of Huang- Wang and Otsu methods when the image consists of textured background and poor printing quality. The three methods perform well but yield different binarization approaches if the background and foreground of the image have well-separated gray-level ranges.

Binarization of Gray-Scaled Digital Images Via Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominquez, Jesus A.; Klinko, Steve; Voska, Ned (Technical Monitor)

2002-01-01

A new fast-computational technique based on fuzzy entropy measure has been developed to find an optimal binary image threshold. In this method, the image pixel membership functions are dependent on the threshold value and reflect the distribution of pixel values in two classes; thus, this technique minimizes the classification error. This new method is compared with two of the best-known threshold selection techniques, Otsu and Huang-Wang. The performance of the proposed method supersedes the performance of Huang-Wang and Otsu methods when the image consists of textured background and poor printing quality. The three methods perform well but yield different binarization approaches if the background and foreground of the image have well-separated gray-level ranges.

Counter Unmanned Aerial Systems Testing: Evaluation of VIS SWIR MWIR and LWIR passive imagers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Birch, Gabriel Carlisle; Woo, Bryana Lynn

This report contains analysis of unmanned aerial systems as imaged by visible, short-wave infrared, mid-wave infrared, and long-wave infrared passive devices. Testing was conducted at the Nevada National Security Site (NNSS) during the week of August 15, 2016. Target images in all spectral bands are shown and contrast versus background is reported. Calculations are performed to determine estimated pixels-on-target for detection and assessment levels, and the number of pixels needed to cover a hemisphere for detection or assessment at defined distances. Background clutter challenges are qualitatively discussed for different spectral bands, and low contrast scenarios are highlighted for long-wave infraredmore » imagers.« less

High-sensitivity, high-speed continuous imaging system

DOEpatents

Watson, Scott A; Bender, III, Howard A

2014-11-18

A continuous imaging system for recording low levels of light typically extending over small distances with high-frame rates and with a large number of frames is described. Photodiode pixels disposed in an array having a chosen geometry, each pixel having a dedicated amplifier, analog-to-digital convertor, and memory, provide parallel operation of the system. When combined with a plurality of scintillators responsive to a selected source of radiation, in a scintillator array, the light from each scintillator being directed to a single corresponding photodiode in close proximity or lens-coupled thereto, embodiments of the present imaging system may provide images of x-ray, gamma ray, proton, and neutron sources with high efficiency.

Cerebral hypoxia during cardiopulmonary bypass: a magnetic resonance imaging study.

PubMed

Mutch, W A; Ryner, L N; Kozlowski, P; Scarth, G; Warrian, R K; Lefevre, G R; Wong, T G; Thiessen, D B; Girling, L G; Doiron, L; McCudden, C; Saunders, J K

1997-09-01

Neurocognitive deficits after open heart operations have been correlated to jugular venous oxygen desaturation on rewarming from hypothermic cardiopulmonary bypass (CPB). Using a porcine model, we looked for evidence of cerebral hypoxia by magnetic resonance imaging during CPB. Brain oxygenation was assessed by T2*-weighted imaging, based on the blood oxygenation level-dependent effect (decreased T2*-weighted signal intensity with increased tissue concentrations of deoxyhemoglobin). Pigs were placed on normothermic CPB, then cooled to 28 degrees C for 2 hours of hypothermic CPB, then rewarmed to baseline temperature. T2*-weighted, imaging was undertaken before CPB, during normothermic CPB, at 30-minute intervals during hypothermic CPB, after rewarming, and then 15 minutes after death. Imaging was with a Bruker 7.0 Tesla, 40-cm bore magnetic resonance scanner with actively shielded gradient coils. Regions of interest from the magnetic resonance images were analyzed to identify parenchymal hypoxia and correlated with jugular venous oxygen saturation. Post-hoc fuzzy clustering analysis was used to examine spatially distributed regions of interest whose pixels followed similar time courses. Attention was paid to pixels showing decreased T2* signal intensity over time. T2* signal intensity decreased with rewarming and in five of seven experiments correlated with the decrease in jugular venous oxygen saturation. T2* imaging with fuzzy clustering analysis revealed two diffusely distributed pixel groups during CPB. One large group of pixels (50% +/- 13% of total pixel count) showed increased T2* signal intensity (well-oxygenated tissue) during hypothermia, with decreased intensity on rewarming. Changes in a second group of pixels (34% +/- 8% of total pixel count) showed a progressive decrease in T2* signal intensity, independent of temperature, suggestive of increased brain hypoxia during CPB. Decreased T2* signal intensity in a diffuse spatial distribution indicates that a large proportion of cerebral parenchyma is hypoxic (evidenced by an increased proportion of tissue deoxyhemoglobin) during CPB in this porcine model. Neuronal damage secondary to parenchymal hypoxia may explain the postoperative neuropsychological dysfunction after cardiac operations.

Spatial light modulator array with heat minimization and image enhancement features

DOEpatents

Jain, Kanti [Briarcliff Manor, NY; Sweatt, William C [Albuquerque, NM; Zemel, Marc [New Rochelle, NY

2007-01-30

An enhanced spatial light modulator (ESLM) array, a microelectronics patterning system and a projection display system using such an ESLM for heat-minimization and resolution enhancement during imaging, and the method for fabricating such an ESLM array. The ESLM array includes, in each individual pixel element, a small pixel mirror (reflective region) and a much larger pixel surround. Each pixel surround includes diffraction-grating regions and resolution-enhancement regions. During imaging, a selected pixel mirror reflects a selected-pixel beamlet into the capture angle of a projection lens, while the diffraction grating of the pixel surround redirects heat-producing unused radiation away from the projection lens. The resolution-enhancement regions of selected pixels provide phase shifts that increase effective modulation-transfer function in imaging. All of the non-selected pixel surrounds redirect all radiation energy away from the projection lens. All elements of the ESLM are fabricated by deposition, patterning, etching and other microelectronic process technologies.

Supervised pixel classification using a feature space derived from an artificial visual system

NASA Technical Reports Server (NTRS)

Baxter, Lisa C.; Coggins, James M.

1991-01-01

Image segmentation involves labelling pixels according to their membership in image regions. This requires the understanding of what a region is. Using supervised pixel classification, the paper investigates how groups of pixels labelled manually according to perceived image semantics map onto the feature space created by an Artificial Visual System. Multiscale structure of regions are investigated and it is shown that pixels form clusters based on their geometric roles in the image intensity function, not by image semantics. A tentative abstract definition of a 'region' is proposed based on this behavior.

Mitigating illumination gradients in a SAR image based on the image data and antenna beam pattern

DOEpatents

Doerry, Armin W.

2013-04-30

Illumination gradients in a synthetic aperture radar (SAR) image of a target can be mitigated by determining a correction for pixel values associated with the SAR image. This correction is determined based on information indicative of a beam pattern used by a SAR antenna apparatus to illuminate the target, and also based on the pixel values associated with the SAR image. The correction is applied to the pixel values associated with the SAR image to produce corrected pixel values that define a corrected SAR image.

A novel image encryption algorithm using chaos and reversible cellular automata

NASA Astrophysics Data System (ADS)

Wang, Xingyuan; Luan, Dapeng

2013-11-01

In this paper, a novel image encryption scheme is proposed based on reversible cellular automata (RCA) combining chaos. In this algorithm, an intertwining logistic map with complex behavior and periodic boundary reversible cellular automata are used. We split each pixel of image into units of 4 bits, then adopt pseudorandom key stream generated by the intertwining logistic map to permute these units in confusion stage. And in diffusion stage, two-dimensional reversible cellular automata which are discrete dynamical systems are applied to iterate many rounds to achieve diffusion on bit-level, in which we only consider the higher 4 bits in a pixel because the higher 4 bits carry almost the information of an image. Theoretical analysis and experimental results demonstrate the proposed algorithm achieves a high security level and processes good performance against common attacks like differential attack and statistical attack. This algorithm belongs to the class of symmetric systems.

Multispectral imaging approach for simplified non-invasive in-vivo evaluation of gingival erythema

NASA Astrophysics Data System (ADS)

Eckhard, Timo; Valero, Eva M.; Nieves, Juan L.; Gallegos-Rueda, José M.; Mesa, Francisco

2012-03-01

Erythema is a common visual sign of gingivitis. In this work, a new and simple low-cost image capture and analysis method for erythema assessment is proposed. The method is based on digital still images of gingivae and applied on a pixel-by-pixel basis. Multispectral images are acquired with a conventional digital camera and multiplexed LED illumination panels at 460nm and 630nm peak wavelength. An automatic work-flow segments teeth from gingiva regions in the images and creates a map of local blood oxygenation levels, which relates to the presence of erythema. The map is computed from the ratio of the two spectral images. An advantage of the proposed approach is that the whole process is easy to manage by dental health care professionals in clinical environment.

Shadow-free single-pixel imaging

NASA Astrophysics Data System (ADS)

Li, Shunhua; Zhang, Zibang; Ma, Xiao; Zhong, Jingang

2017-11-01

Single-pixel imaging is an innovative imaging scheme and receives increasing attention in recent years, for it is applicable for imaging at non-visible wavelengths and imaging under weak light conditions. However, as in conventional imaging, shadows would likely occur in single-pixel imaging and sometimes bring negative effects in practical uses. In this paper, the principle of shadows occurrence in single-pixel imaging is analyzed, following which a technique for shadows removal is proposed. In the proposed technique, several single-pixel detectors are used to detect the backscattered light at different locations so that the shadows in the reconstructed images corresponding to each detector shadows are complementary. Shadow-free reconstruction can be derived by fusing the shadow-complementary images using maximum selection rule. To deal with the problem of intensity mismatch in image fusion, we put forward a simple calibration. As experimentally demonstrated, the technique is able to reconstruct monochromatic and full-color shadow-free images.

Fast Pixel Buffer For Processing With Lookup Tables

NASA Technical Reports Server (NTRS)

Fisher, Timothy E.

1992-01-01

Proposed scheme for buffering data on intensities of picture elements (pixels) of image increases rate or processing beyond that attainable when data read, one pixel at time, from main image memory. Scheme applied in design of specialized image-processing circuitry. Intended to optimize performance of processor in which electronic equivalent of address-lookup table used to address those pixels in main image memory required for processing.

Highly sensitive and area-efficient CMOS image sensor using a PMOSFET-type photodetector with a built-in transfer gate

NASA Astrophysics Data System (ADS)

Seo, Sang-Ho; Kim, Kyoung-Do; Kong, Jae-Sung; Shin, Jang-Kyoo; Choi, Pyung

2007-02-01

In this paper, a new CMOS image sensor is presented, which uses a PMOSFET-type photodetector with a transfer gate that has a high and variable sensitivity. The proposed CMOS image sensor has been fabricated using a 0.35 μm 2-poly 4- metal standard CMOS technology and is composed of a 256 × 256 array of 7.05 × 7.10 μm pixels. The unit pixel has a configuration of a pseudo 3-transistor active pixel sensor (APS) with the PMOSFET-type photodetector with a transfer gate, which has a function of conventional 4-transistor APS. The generated photocurrent is controlled by the transfer gate of the PMOSFET-type photodetector. The maximum responsivity of the photodetector is larger than 1.0 × 10 3 A/W without any optical lens. Fabricated 256 × 256 CMOS image sensor exhibits a good response to low-level illumination as low as 5 lux.

Adaptive pixel-to-pixel projection intensity adjustment for measuring a shiny surface using orthogonal color fringe pattern projection

NASA Astrophysics Data System (ADS)

Chen, Chao; Gao, Nan; Wang, Xiangjun; Zhang, Zonghua

2018-05-01

Three-dimensional (3D) shape measurement based on fringe pattern projection techniques has been commonly used in various fields. One of the remaining challenges in fringe pattern projection is that camera sensor saturation may occur if there is a large range of reflectivity variation across the surface that causes measurement errors. To overcome this problem, a novel fringe pattern projection method is proposed to avoid image saturation and maintain high-intensity modulation for measuring shiny surfaces by adaptively adjusting the pixel-to-pixel projection intensity according to the surface reflectivity. First, three sets of orthogonal color fringe patterns and a sequence of uniform gray-level patterns with different gray levels are projected onto a measured surface by a projector. The patterns are deformed with respect to the object surface and captured by a camera from a different viewpoint. Subsequently, the optimal projection intensity at each pixel is determined by fusing different gray levels and transforming the camera pixel coordinate system into the projector pixel coordinate system. Finally, the adapted fringe patterns are created and used for 3D shape measurement. Experimental results on a flat checkerboard and shiny objects demonstrate that the proposed method can measure shiny surfaces with high accuracy.

Detector motion method to increase spatial resolution in photon-counting detectors

NASA Astrophysics Data System (ADS)

Lee, Daehee; Park, Kyeongjin; Lim, Kyung Taek; Cho, Gyuseong

2017-03-01

Medical imaging requires high spatial resolution of an image to identify fine lesions. Photon-counting detectors in medical imaging have recently been rapidly replacing energy-integrating detectors due to the former`s high spatial resolution, high efficiency and low noise. Spatial resolution in a photon counting image is determined by the pixel size. Therefore, the smaller the pixel size, the higher the spatial resolution that can be obtained in an image. However, detector redesigning is required to reduce pixel size, and an expensive fine process is required to integrate a signal processing unit with reduced pixel size. Furthermore, as the pixel size decreases, charge sharing severely deteriorates spatial resolution. To increase spatial resolution, we propose a detector motion method using a large pixel detector that is less affected by charge sharing. To verify the proposed method, we utilized a UNO-XRI photon-counting detector (1-mm CdTe, Timepix chip) at the maximum X-ray tube voltage of 80 kVp. A similar spatial resolution of a 55- μm-pixel image was achieved by application of the proposed method to a 110- μm-pixel detector with a higher signal-to-noise ratio. The proposed method could be a way to increase spatial resolution without a pixel redesign when pixels severely suffer from charge sharing as pixel size is reduced.

Imaging through scattering media by Fourier filtering and single-pixel detection

NASA Astrophysics Data System (ADS)

Jauregui-Sánchez, Y.; Clemente, P.; Lancis, J.; Tajahuerce, E.

2018-02-01

We present a novel imaging system that combines the principles of Fourier spatial filtering and single-pixel imaging in order to recover images of an object hidden behind a turbid medium by transillumination. We compare the performance of our single-pixel imaging setup with that of a conventional system. We conclude that the introduction of Fourier gating improves the contrast of images in both cases. Furthermore, we show that the combination of single-pixel imaging and Fourier spatial filtering techniques is particularly well adapted to provide images of objects transmitted through scattering media.

Mapping spatial patterns with morphological image processing

Treesearch

Peter Vogt; Kurt H. Riitters; Christine Estreguil; Jacek Kozak; Timothy G. Wade; James D. Wickham

2006-01-01

We use morphological image processing for classifying spatial patterns at the pixel level on binary land-cover maps. Land-cover pattern is classified as 'perforated,' 'edge,' 'patch,' and 'core' with higher spatial precision and thematic accuracy compared to a previous approach based on image convolution, while retaining the...

A novel method for morphological pleomorphism and heterogeneity quantitative measurement: Named cell feature level co-occurrence matrix.

PubMed

Saito, Akira; Numata, Yasushi; Hamada, Takuya; Horisawa, Tomoyoshi; Cosatto, Eric; Graf, Hans-Peter; Kuroda, Masahiko; Yamamoto, Yoichiro

2016-01-01

Recent developments in molecular pathology and genetic/epigenetic analysis of cancer tissue have resulted in a marked increase in objective and measurable data. In comparison, the traditional morphological analysis approach to pathology diagnosis, which can connect these molecular data and clinical diagnosis, is still mostly subjective. Even though the advent and popularization of digital pathology has provided a boost to computer-aided diagnosis, some important pathological concepts still remain largely non-quantitative and their associated data measurements depend on the pathologist's sense and experience. Such features include pleomorphism and heterogeneity. In this paper, we propose a method for the objective measurement of pleomorphism and heterogeneity, using the cell-level co-occurrence matrix. Our method is based on the widely used Gray-level co-occurrence matrix (GLCM), where relations between neighboring pixel intensity levels are captured into a co-occurrence matrix, followed by the application of analysis functions such as Haralick features. In the pathological tissue image, through image processing techniques, each nucleus can be measured and each nucleus has its own measureable features like nucleus size, roundness, contour length, intra-nucleus texture data (GLCM is one of the methods). In GLCM each nucleus in the tissue image corresponds to one pixel. In this approach the most important point is how to define the neighborhood of each nucleus. We define three types of neighborhoods of a nucleus, then create the co-occurrence matrix and apply Haralick feature functions. In each image pleomorphism and heterogeneity are then determined quantitatively. For our method, one pixel corresponds to one nucleus feature, and we therefore named our method Cell Feature Level Co-occurrence Matrix (CFLCM). We tested this method for several nucleus features. CFLCM is showed as a useful quantitative method for pleomorphism and heterogeneity on histopathological image analysis.

Median filters as a tool to determine dark noise thresholds in high resolution smartphone image sensors for scientific imaging

NASA Astrophysics Data System (ADS)

Igoe, Damien P.; Parisi, Alfio V.; Amar, Abdurazaq; Rummenie, Katherine J.

2018-01-01

An evaluation of the use of median filters in the reduction of dark noise in smartphone high resolution image sensors is presented. The Sony Xperia Z1 employed has a maximum image sensor resolution of 20.7 Mpixels, with each pixel having a side length of just over 1 μm. Due to the large number of photosites, this provides an image sensor with very high sensitivity but also makes them prone to noise effects such as hot-pixels. Similar to earlier research with older models of smartphone, no appreciable temperature effects were observed in the overall average pixel values for images taken in ambient temperatures between 5 °C and 25 °C. In this research, hot-pixels are defined as pixels with intensities above a specific threshold. The threshold is determined using the distribution of pixel values of a set of images with uniform statistical properties associated with the application of median-filters of increasing size. An image with uniform statistics was employed as a training set from 124 dark images, and the threshold was determined to be 9 digital numbers (DN). The threshold remained constant for multiple resolutions and did not appreciably change even after a year of extensive field use and exposure to solar ultraviolet radiation. Although the temperature effects' uniformity masked an increase in hot-pixel occurrences, the total number of occurrences represented less than 0.1% of the total image. Hot-pixels were removed by applying a median filter, with an optimum filter size of 7 × 7; similar trends were observed for four additional smartphone image sensors used for validation. Hot-pixels were also reduced by decreasing image resolution. The method outlined in this research provides a methodology to characterise the dark noise behavior of high resolution image sensors for use in scientific investigations, especially as pixel sizes decrease.

All-passive pixel super-resolution of time-stretch imaging

PubMed Central

Chan, Antony C. S.; Ng, Ho-Cheung; Bogaraju, Sharat C. V.; So, Hayden K. H.; Lam, Edmund Y.; Tsia, Kevin K.

2017-01-01

Based on image encoding in a serial-temporal format, optical time-stretch imaging entails a stringent requirement of state-of-the-art fast data acquisition unit in order to preserve high image resolution at an ultrahigh frame rate — hampering the widespread utilities of such technology. Here, we propose a pixel super-resolution (pixel-SR) technique tailored for time-stretch imaging that preserves pixel resolution at a relaxed sampling rate. It harnesses the subpixel shifts between image frames inherently introduced by asynchronous digital sampling of the continuous time-stretch imaging process. Precise pixel registration is thus accomplished without any active opto-mechanical subpixel-shift control or other additional hardware. Here, we present the experimental pixel-SR image reconstruction pipeline that restores high-resolution time-stretch images of microparticles and biological cells (phytoplankton) at a relaxed sampling rate (≈2–5 GSa/s)—more than four times lower than the originally required readout rate (20 GSa/s) — is thus effective for high-throughput label-free, morphology-based cellular classification down to single-cell precision. Upon integration with the high-throughput image processing technology, this pixel-SR time-stretch imaging technique represents a cost-effective and practical solution for large scale cell-based phenotypic screening in biomedical diagnosis and machine vision for quality control in manufacturing. PMID:28303936

Tradeoff between picture element dimensions and noncoherent averaging in side-looking airborne radar

NASA Technical Reports Server (NTRS)

Moore, R. K.

1979-01-01

An experiment was performed in which three synthetic-aperture images and one real-aperture image were successively degraded in spatial resolution, both retaining the same number of independent samples per pixel and using the spatial degradation to allow averaging of different numbers of independent samples within each pixel. The original and degraded images were provided to three interpreters familiar with both aerial photographs and radar images. The interpreters were asked to grade each image in terms of their ability to interpret various specified features on the image. The numerical interpretability grades were then used as a quantitative measure of the utility of the different kinds of image processing and different resolutions. The experiment demonstrated empirically that the interpretability is related exponentially to the SGL volume which is the product of azimuth, range, and gray-level resolution.

Spectral analysis of views interpolated by chroma subpixel downsampling for 3D autosteroscopic displays

NASA Astrophysics Data System (ADS)

Marson, Avishai; Stern, Adrian

2015-05-01

One of the main limitations of horizontal parallax autostereoscopic displays is the horizontal resolution loss due the need to repartition the pixels of the display panel among the multiple views. Recently we have shown that this problem can be alleviated by applying a color sub-pixel rendering technique1. Interpolated views are generated by down-sampling the panel pixels at sub-pixel level, thus increasing the number of views. The method takes advantage of lower acuity of the human eye to chromatic resolution. Here we supply further support of the technique by analyzing the spectra of the subsampled images.

A fast image encryption algorithm based on only blocks in cipher text

NASA Astrophysics Data System (ADS)

Wang, Xing-Yuan; Wang, Qian

2014-03-01

In this paper, a fast image encryption algorithm is proposed, in which the shuffling and diffusion is performed simultaneously. The cipher-text image is divided into blocks and each block has k ×k pixels, while the pixels of the plain-text are scanned one by one. Four logistic maps are used to generate the encryption key stream and the new place in the cipher image of plain image pixels, including the row and column of the block which the pixel belongs to and the place where the pixel would be placed in the block. After encrypting each pixel, the initial conditions of logistic maps would be changed according to the encrypted pixel's value; after encrypting each row of plain image, the initial condition would also be changed by the skew tent map. At last, it is illustrated that this algorithm has a faster speed, big key space, and better properties in withstanding differential attacks, statistical analysis, known plaintext, and chosen plaintext attacks.

Mapping Electrical Crosstalk in Pixelated Sensor Arrays

NASA Technical Reports Server (NTRS)

Seshadri, Suresh (Inventor); Cole, David (Inventor); Smith, Roger M. (Inventor); Hancock, Bruce R. (Inventor)

2017-01-01

The effects of inter pixel capacitance in a pixilated array may be measured by first resetting all pixels in the array to a first voltage, where a first image is read out, followed by resetting only a subset of pixels in the array to a second voltage, where a second image is read out, where the difference in the first and second images provide information about the inter pixel capacitance. Other embodiments are described and claimed.

Mapping Electrical Crosstalk in Pixelated Sensor Arrays

NASA Technical Reports Server (NTRS)

Smith, Roger M (Inventor); Hancock, Bruce R. (Inventor); Cole, David (Inventor); Seshadri, Suresh (Inventor)

2013-01-01

The effects of inter pixel capacitance in a pixilated array may be measured by first resetting all pixels in the array to a first voltage, where a first image is read out, followed by resetting only a subset of pixels in the array to a second voltage, where a second image is read out, where the difference in the first and second images provide information about the inter pixel capacitance. Other embodiments are described and claimed.

How Many Pixels Does It Take to Make a Good 4"×6" Print? Pixel Count Wars Revisited

NASA Astrophysics Data System (ADS)

Kriss, Michael A.

Digital still cameras emerged following the introduction of the Sony Mavica analog prototype camera in 1981. These early cameras produced poor image quality and did not challenge film cameras for overall quality. By 1995 digital still cameras in expensive SLR formats had 6 mega-pixels and produced high quality images (with significant image processing). In 2005 significant improvement in image quality was apparent and lower prices for digital still cameras (DSCs) started a rapid decline in film usage and film camera sells. By 2010 film usage was mostly limited to professionals and the motion picture industry. The rise of DSCs was marked by a “pixel war” where the driving feature of the cameras was the pixel count where even moderate cost, ˜120, DSCs would have 14 mega-pixels. The improvement of CMOS technology pushed this trend of lower prices and higher pixel counts. Only the single lens reflex cameras had large sensors and large pixels. The drive for smaller pixels hurt the quality aspects of the final image (sharpness, noise, speed, and exposure latitude). Only today are camera manufactures starting to reverse their course and producing DSCs with larger sensors and pixels. This paper will explore why larger pixels and sensors are key to the future of DSCs.

The effect of split pixel HDR image sensor technology on MTF measurements

NASA Astrophysics Data System (ADS)

Deegan, Brian M.

2014-03-01

Split-pixel HDR sensor technology is particularly advantageous in automotive applications, because the images are captured simultaneously rather than sequentially, thereby reducing motion blur. However, split pixel technology introduces artifacts in MTF measurement. To achieve a HDR image, raw images are captured from both large and small sub-pixels, and combined to make the HDR output. In some cases, a large sub-pixel is used for long exposure captures, and a small sub-pixel for short exposures, to extend the dynamic range. The relative size of the photosensitive area of the pixel (fill factor) plays a very significant role in the output MTF measurement. Given an identical scene, the MTF will be significantly different, depending on whether you use the large or small sub-pixels i.e. a smaller fill factor (e.g. in the short exposure sub-pixel) will result in higher MTF scores, but significantly greater aliasing. Simulations of split-pixel sensors revealed that, when raw images from both sub-pixels are combined, there is a significant difference in rising edge (i.e. black-to-white transition) and falling edge (white-to-black) reproduction. Experimental results showed a difference of ~50% in measured MTF50 between the falling and rising edges of a slanted edge test chart.

Dynamically re-configurable CMOS imagers for an active vision system

NASA Technical Reports Server (NTRS)

Yang, Guang (Inventor); Pain, Bedabrata (Inventor)

2005-01-01

A vision system is disclosed. The system includes a pixel array, at least one multi-resolution window operation circuit, and a pixel averaging circuit. The pixel array has an array of pixels configured to receive light signals from an image having at least one tracking target. The multi-resolution window operation circuits are configured to process the image. Each of the multi-resolution window operation circuits processes each tracking target within a particular multi-resolution window. The pixel averaging circuit is configured to sample and average pixels within the particular multi-resolution window.

Kriging in the Shadows: Geostatistical Interpolation for Remote Sensing

NASA Technical Reports Server (NTRS)

Rossi, Richard E.; Dungan, Jennifer L.; Beck, Louisa R.

1994-01-01

It is often useful to estimate obscured or missing remotely sensed data. Traditional interpolation methods, such as nearest-neighbor or bilinear resampling, do not take full advantage of the spatial information in the image. An alternative method, a geostatistical technique known as indicator kriging, is described and demonstrated using a Landsat Thematic Mapper image in southern Chiapas, Mexico. The image was first classified into pasture and nonpasture land cover. For each pixel that was obscured by cloud or cloud shadow, the probability that it was pasture was assigned by the algorithm. An exponential omnidirectional variogram model was used to characterize the spatial continuity of the image for use in the kriging algorithm. Assuming a cutoff probability level of 50%, the error was shown to be 17% with no obvious spatial bias but with some tendency to categorize nonpasture as pasture (overestimation). While this is a promising result, the method's practical application in other missing data problems for remotely sensed images will depend on the amount and spatial pattern of the unobscured pixels and missing pixels and the success of the spatial continuity model used.

Precision measurements from very-large scale aerial digital imagery.

PubMed

Booth, D Terrance; Cox, Samuel E; Berryman, Robert D

2006-01-01

Managers need measurements and resource managers need the length/width of a variety of items including that of animals, logs, streams, plant canopies, man-made objects, riparian habitat, vegetation patches and other things important in resource monitoring and land inspection. These types of measurements can now be easily and accurately obtained from very large scale aerial (VLSA) imagery having spatial resolutions as fine as 1 millimeter per pixel by using the three new software programs described here. VLSA images have small fields of view and are used for intermittent sampling across extensive landscapes. Pixel-coverage among images is influenced by small changes in airplane altitude above ground level (AGL) and orientation relative to the ground, as well as by changes in topography. These factors affect the object-to-camera distance used for image-resolution calculations. 'ImageMeasurement' offers a user-friendly interface for accounting for pixel-coverage variation among images by utilizing a database. 'LaserLOG' records and displays airplane altitude AGL measured from a high frequency laser rangefinder, and displays the vertical velocity. 'Merge' sorts through large amounts of data generated by LaserLOG and matches precise airplane altitudes with camera trigger times for input to the ImageMeasurement database. We discuss application of these tools, including error estimates. We found measurements from aerial images (collection resolution: 5-26 mm/pixel as projected on the ground) using ImageMeasurement, LaserLOG, and Merge, were accurate to centimeters with an error less than 10%. We recommend these software packages as a means for expanding the utility of aerial image data.

Avoiding Stair-Step Artifacts in Image Registration for GOES-R Navigation and Registration Assessment

NASA Technical Reports Server (NTRS)

Grycewicz, Thomas J.; Tan, Bin; Isaacson, Peter J.; De Luccia, Frank J.; Dellomo, John

2016-01-01

In developing software for independent verification and validation (IVV) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.

Performance of a novel wafer scale CMOS active pixel sensor for bio-medical imaging.

PubMed

Esposito, M; Anaxagoras, T; Konstantinidis, A C; Zheng, Y; Speller, R D; Evans, P M; Allinson, N M; Wells, K

2014-07-07

Recently CMOS active pixels sensors (APSs) have become a valuable alternative to amorphous silicon and selenium flat panel imagers (FPIs) in bio-medical imaging applications. CMOS APSs can now be scaled up to the standard 20 cm diameter wafer size by means of a reticle stitching block process. However, despite wafer scale CMOS APS being monolithic, sources of non-uniformity of response and regional variations can persist representing a significant challenge for wafer scale sensor response. Non-uniformity of stitched sensors can arise from a number of factors related to the manufacturing process, including variation of amplification, variation between readout components, wafer defects and process variations across the wafer due to manufacturing processes. This paper reports on an investigation into the spatial non-uniformity and regional variations of a wafer scale stitched CMOS APS. For the first time a per-pixel analysis of the electro-optical performance of a wafer CMOS APS is presented, to address inhomogeneity issues arising from the stitching techniques used to manufacture wafer scale sensors. A complete model of the signal generation in the pixel array has been provided and proved capable of accounting for noise and gain variations across the pixel array. This novel analysis leads to readout noise and conversion gain being evaluated at pixel level, stitching block level and in regions of interest, resulting in a coefficient of variation ⩽1.9%. The uniformity of the image quality performance has been further investigated in a typical x-ray application, i.e. mammography, showing a uniformity in terms of CNR among the highest when compared with mammography detectors commonly used in clinical practice. Finally, in order to compare the detection capability of this novel APS with the technology currently used (i.e. FPIs), theoretical evaluation of the detection quantum efficiency (DQE) at zero-frequency has been performed, resulting in a higher DQE for this detector compared to FPIs. Optical characterization, x-ray contrast measurements and theoretical DQE evaluation suggest that a trade off can be found between the need of a large imaging area and the requirement of a uniform imaging performance, making the DynAMITe large area CMOS APS suitable for a range of bio-medical applications.

Pixel level optical-transfer-function design based on the surface-wave-interferometry aperture

PubMed Central

Zheng, Guoan; Wang, Yingmin; Yang, Changhuei

2010-01-01

The design of optical transfer function (OTF) is of significant importance for optical information processing in various imaging and vision systems. Typically, OTF design relies on sophisticated bulk optical arrangement in the light path of the optical systems. In this letter, we demonstrate a surface-wave-interferometry aperture (SWIA) that can be directly incorporated onto optical sensors to accomplish OTF design on the pixel level. The whole aperture design is based on the bull’s eye structure. It composes of a central hole (diameter of 300 nm) and periodic groove (period of 560 nm) on a 340 nm thick gold layer. We show, with both simulation and experiment, that different types of optical transfer functions (notch, highpass and lowpass filter) can be achieved by manipulating the interference between the direct transmission of the central hole and the surface wave (SW) component induced from the periodic groove. Pixel level OTF design provides a low-cost, ultra robust, highly compact method for numerous applications such as optofluidic microscopy, wavefront detection, darkfield imaging, and computational photography. PMID:20721038

Image Segmentation for Connectomics Using Machine Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tasdizen, Tolga; Seyedhosseini, Mojtaba; Liu, TIng

Reconstruction of neural circuits at the microscopic scale of individual neurons and synapses, also known as connectomics, is an important challenge for neuroscience. While an important motivation of connectomics is providing anatomical ground truth for neural circuit models, the ability to decipher neural wiring maps at the individual cell level is also important in studies of many neurodegenerative diseases. Reconstruction of a neural circuit at the individual neuron level requires the use of electron microscopy images due to their extremely high resolution. Computational challenges include pixel-by-pixel annotation of these images into classes such as cell membrane, mitochondria and synaptic vesiclesmore » and the segmentation of individual neurons. State-of-the-art image analysis solutions are still far from the accuracy and robustness of human vision and biologists are still limited to studying small neural circuits using mostly manual analysis. In this chapter, we describe our image analysis pipeline that makes use of novel supervised machine learning techniques to tackle this problem.« less

In-situ device integration of large-area patterned organic nanowire arrays for high-performance optical sensors

PubMed Central

Wu, Yiming; Zhang, Xiujuan; Pan, Huanhuan; Deng, Wei; Zhang, Xiaohong; Zhang, Xiwei; Jie, Jiansheng

2013-01-01

Single-crystalline organic nanowires (NWs) are important building blocks for future low-cost and efficient nano-optoelectronic devices due to their extraordinary properties. However, it remains a critical challenge to achieve large-scale organic NW array assembly and device integration. Herein, we demonstrate a feasible one-step method for large-area patterned growth of cross-aligned single-crystalline organic NW arrays and their in-situ device integration for optical image sensors. The integrated image sensor circuitry contained a 10 × 10 pixel array in an area of 1.3 × 1.3 mm2, showing high spatial resolution, excellent stability and reproducibility. More importantly, 100% of the pixels successfully operated at a high response speed and relatively small pixel-to-pixel variation. The high yield and high spatial resolution of the operational pixels, along with the high integration level of the device, clearly demonstrate the great potential of the one-step organic NW array growth and device construction approach for large-scale optoelectronic device integration. PMID:24287887

Pixel parallel localized driver design for a 128 x 256 pixel array 3D 1Gfps image sensor

NASA Astrophysics Data System (ADS)

Zhang, C.; Dao, V. T. S.; Etoh, T. G.; Charbon, E.

2017-02-01

In this paper, a 3D 1Gfps BSI image sensor is proposed, where 128 × 256 pixels are located in the top-tier chip and a 32 × 32 localized driver array in the bottom-tier chip. Pixels are designed with Multiple Collection Gates (MCG), which collects photons selectively with different collection gates being active at intervals of 1ns to achieve 1Gfps. For the drivers, a global PLL is designed, which consists of a ring oscillator with 6-stage current starved differential inverters, achieving a wide frequency tuning range from 40MHz to 360MHz (20ps rms jitter). The drivers are the replicas of the ring oscillator that operates within a PLL. Together with level shifters and XNOR gates, continuous 3.3V pulses are generated with desired pulse width, which is 1/12 of the PLL clock period. The driver array is activated by a START signal, which propagates through a highly balanced clock tree, to activate all the pixels at the same time with virtually negligible skew.

Level set method for image segmentation based on moment competition

NASA Astrophysics Data System (ADS)

Min, Hai; Wang, Xiao-Feng; Huang, De-Shuang; Jin, Jing; Wang, Hong-Zhi; Li, Hai

2015-05-01

We propose a level set method for image segmentation which introduces the moment competition and weakly supervised information into the energy functional construction. Different from the region-based level set methods which use force competition, the moment competition is adopted to drive the contour evolution. Here, a so-called three-point labeling scheme is proposed to manually label three independent points (weakly supervised information) on the image. Then the intensity differences between the three points and the unlabeled pixels are used to construct the force arms for each image pixel. The corresponding force is generated from the global statistical information of a region-based method and weighted by the force arm. As a result, the moment can be constructed and incorporated into the energy functional to drive the evolving contour to approach the object boundary. In our method, the force arm can take full advantage of the three-point labeling scheme to constrain the moment competition. Additionally, the global statistical information and weakly supervised information are successfully integrated, which makes the proposed method more robust than traditional methods for initial contour placement and parameter setting. Experimental results with performance analysis also show the superiority of the proposed method on segmenting different types of complicated images, such as noisy images, three-phase images, images with intensity inhomogeneity, and texture images.

Land cover mapping at sub-pixel scales

NASA Astrophysics Data System (ADS)

Makido, Yasuyo Kato

One of the biggest drawbacks of land cover mapping from remotely sensed images relates to spatial resolution, which determines the level of spatial details depicted in an image. Fine spatial resolution images from satellite sensors such as IKONOS and QuickBird are now available. However, these images are not suitable for large-area studies, since a single image is very small and therefore it is costly for large area studies. Much research has focused on attempting to extract land cover types at sub-pixel scale, and little research has been conducted concerning the spatial allocation of land cover types within a pixel. This study is devoted to the development of new algorithms for predicting land cover distribution using remote sensory imagery at sub-pixel level. The "pixel-swapping" optimization algorithm, which was proposed by Atkinson for predicting sub-pixel land cover distribution, is investigated in this study. Two limitations of this method, the arbitrary spatial range value and the arbitrary exponential model of spatial autocorrelation, are assessed. Various weighting functions, as alternatives to the exponential model, are evaluated in order to derive the optimum weighting function. Two different simulation models were employed to develop spatially autocorrelated binary class maps. In all tested models, Gaussian, Exponential, and IDW, the pixel swapping method improved classification accuracy compared with the initial random allocation of sub-pixels. However the results suggested that equal weight could be used to increase accuracy and sub-pixel spatial autocorrelation instead of using these more complex models of spatial structure. New algorithms for modeling the spatial distribution of multiple land cover classes at sub-pixel scales are developed and evaluated. Three methods are examined: sequential categorical swapping, simultaneous categorical swapping, and simulated annealing. These three methods are applied to classified Landsat ETM+ data that has been resampled to 210 meters. The result suggested that the simultaneous method can be considered as the optimum method in terms of accuracy performance and computation time. The case study employs remote sensing imagery at the following sites: tropical forests in Brazil and temperate multiple land mosaic in East China. Sub-areas for both sites are used to examine how the characteristics of the landscape affect the ability of the optimum technique. Three types of measurement: Moran's I, mean patch size (MPS), and patch size standard deviation (STDEV), are used to characterize the landscape. All results suggested that this technique could increase the classification accuracy more than traditional hard classification. The methods developed in this study can benefit researchers who employ coarse remote sensing imagery but are interested in detailed landscape information. In many cases, the satellite sensor that provides large spatial coverage has insufficient spatial detail to identify landscape patterns. Application of the super-resolution technique described in this dissertation could potentially solve this problem by providing detailed land cover predictions from the coarse resolution satellite sensor imagery.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stevens, Andrew; Browning, Nigel D.

Traditionally, microscopists have worked with the Nyquist-Shannon theory of sampling, which states that to be able to reconstruct the image fully it needs to be sampled at a rate of at least twice the highest spatial frequency in the image. This sampling rate assumes that the image is sampled at regular intervals and that every pixel contains information that is crucial for the image (it even assumes that noise is important). Images in general, and especially low dose S/TEM images, contain significantly less information than can be encoded by a grid of pixels (which is why image compression works). Mathematicallymore » speaking, the image data has a low dimensional or sparse representation. Through the application of compressive sensing methods [1,2,3] this representation can be found using pre-designed measurements that are usually random for implementation simplicity. These measurements and the compressive sensing reconstruction algorithms have the added benefit of reducing noise. This reconstruction approach can be extended into higher dimensions, whereby the random sampling in each 2-D image can be extended into: a sequence of tomographic projections (i.e. tilt images); a sequence of video frames (i.e. incorporating temporal resolution and dynamics); spectral resolution (i.e. energy filtering an image to see the distribution of elements); and ptychography (i.e. sampling a full diffraction image at each location in a 2-D grid across the sample). This approach has been employed experimentally for materials science samples requiring low-dose imaging [2], and can be readily applied to biological samples. Figure 1 shows the resolution possible in a complex biological system, mouse pancreatic islet beta cells [4], when tomogram slices are reconstructed using subsampling. Reducing the number of pixels (1/6 pix and 1/3*1/3) shows minimal degradation compared to the reconstructions using all pixels (all data and 1/3 tilt). Although subsampling 1/6 of the tilts (1/6 of overall dose) degrades the reconstruction to the point that the cellular structures cannot be identified. Using 1/3 of both the pixels and the tilts provides a high quality image at 1/9 the overall dose even for this most basic and rapid demonstration of the CS methods. Figure 2 demonstrates the theoretical tomogram reconstruction quality (vertical axis) as undersampling (horizontal axis) is increased; we examined subsampling pixels and tilt-angles individually and a combined approach in which both pixels and tilts are sub-sampled. Note that subsampling pixels maintains high quality reconstructions (solid lines). Using the inpainting algorithm to obtain tomograms can automatically reduce the dose applied to the system by an order of magnitude. Perhaps the best way to understand the impact is to consider that by using inpainting (and with minimal hardware changes), a sample that can normally withstand a dose of ~10 e/Å2 can potentially be imaged with an “equivalent quality” to a dose level of 103 e/Å2. To put this in perspective, this is approaching the dose level used for the most advanced images, in terms of spatial resolution, for inorganic systems. While there are issues for biological specimens beyond dose (structural complexity being the most important one), this sampling approach allows the methods that are traditionally used for materials science to be applied to biological systems [5]. References: [1] A Stevens, H Yang, L Carin et al. Microscopy 63(1), (2014), pp. 41. [2] L Kovarik, A Stevens, A Liyu et al. Appl. Phys. Lett. 109, 164102 (2016) [3] A Stevens, L Kovarik, P Abellan et al. Adv. Structural and Chemical Imaging 1(10), (2015), pp. 1. [4] MD Guay, W Czaja, MA Aronova et al. Scientific Reports 6, 27614 (2016) [5] Supported by the Chemical Imaging, Signature Discovery, and Analytics in Motion Initiatives at PNNL. PNNL is operated by Battelle Memorial Inst. for the US DOE; contract DE-AC05-76RL01830.« less

Breast ultrasound image segmentation: an optimization approach based on super-pixels and high-level descriptors

NASA Astrophysics Data System (ADS)

Massich, Joan; Lemaître, Guillaume; Martí, Joan; Mériaudeau, Fabrice

2015-04-01

Breast cancer is the second most common cancer and the leading cause of cancer death among women. Medical imaging has become an indispensable tool for its diagnosis and follow up. During the last decade, the medical community has promoted to incorporate Ultra-Sound (US) screening as part of the standard routine. The main reason for using US imaging is its capability to differentiate benign from malignant masses, when compared to other imaging techniques. The increasing usage of US imaging encourages the development of Computer Aided Diagnosis (CAD) systems applied to Breast Ultra-Sound (BUS) images. However accurate delineations of the lesions and structures of the breast are essential for CAD systems in order to extract information needed to perform diagnosis. This article proposes a highly modular and flexible framework for segmenting lesions and tissues present in BUS images. The proposal takes advantage of optimization strategies using super-pixels and high-level descriptors, which are analogous to the visual cues used by radiologists. Qualitative and quantitative results are provided stating a performance within the range of the state-of-the-art.

Half-unit weighted bilinear algorithm for image contrast enhancement in capsule endoscopy

NASA Astrophysics Data System (ADS)

Rukundo, Olivier

2018-04-01

This paper proposes a novel enhancement method based exclusively on the bilinear interpolation algorithm for capsule endoscopy images. The proposed method does not convert the original RBG image components to HSV or any other color space or model; instead, it processes directly RGB components. In each component, a group of four adjacent pixels and half-unit weight in the bilinear weighting function are used to calculate the average pixel value, identical for each pixel in that particular group. After calculations, groups of identical pixels are overlapped successively in horizontal and vertical directions to achieve a preliminary-enhanced image. The final-enhanced image is achieved by halving the sum of the original and preliminary-enhanced image pixels. Quantitative and qualitative experiments were conducted focusing on pairwise comparisons between original and enhanced images. Final-enhanced images have generally the best diagnostic quality and gave more details about the visibility of vessels and structures in capsule endoscopy images.

BOREAS RSS-14 Level-1a GOES-8 Visible, IR and Water Vapor Images

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Newcomer, Jeffrey A.; Faysash, David; Cooper, Harry J.; Smith, Eric A.

2000-01-01

The BOREAS RSS-14 team collected and processed several GOES-7 and GOES-8 image data sets that covered the BOREAS study region. The level-1a GOES-8 images were created by BORIS personnel from the level-1 images delivered by FSU personnel. The data cover 14-Jul-1995 to 21-Sep-1995 and 12-Feb-1996 to 03-Oct-1996. The data start out as three bands with 8-bit pixel values and end up as five bands with 10-bit pixel values. No major problems with the data have been identified. The differences between the level-1 and level-1a GOES-8 data are the formatting and packaging of the data. The images missing from the temporal series of level-1 GOES-8 images were zero-filled by BORIS staff to create files consistent in size and format. In addition, BORIS staff packaged all the images of a given type from a given day into a single file, removed the header information from the individual level-1 files, and placed it into a single descriptive ASCII header file. The data are contained in binary image format files. Due to the large size of the images, the level-1a GOES-8 data are not contained on the BOREAS CD-ROM set. An inventory listing file is supplied on the CD-ROM to inform users of what data were collected. The level-1a GOES-8 image data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). See sections 15 and 16 for more information. The data files are available on a CD-ROM (see document number 20010000884).

Method and apparatus of high dynamic range image sensor with individual pixel reset

NASA Technical Reports Server (NTRS)

Yadid-Pecht, Orly (Inventor); Pain, Bedabrata (Inventor); Fossum, Eric R. (Inventor)

2001-01-01

A wide dynamic range image sensor provides individual pixel reset to vary the integration time of individual pixels. The integration time of each pixel is controlled by column and row reset control signals which activate a logical reset transistor only when both signals coincide for a given pixel.

Entangled-photon compressive ghost imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zerom, Petros; Chan, Kam Wai Clifford; Howell, John C.

2011-12-15

We have experimentally demonstrated high-resolution compressive ghost imaging at the single-photon level using entangled photons produced by a spontaneous parametric down-conversion source and using single-pixel detectors. For a given mean-squared error, the number of photons needed to reconstruct a two-dimensional image is found to be much smaller than that in quantum ghost imaging experiments employing a raster scan. This procedure not only shortens the data acquisition time, but also suggests a more economical use of photons for low-light-level and quantum image formation.

IR CMOS: near infrared enhanced digital imaging (Presentation Recording)

NASA Astrophysics Data System (ADS)

Pralle, Martin U.; Carey, James E.; Joy, Thomas; Vineis, Chris J.; Palsule, Chintamani

2015-08-01

SiOnyx has demonstrated imaging at light levels below 1 mLux (moonless starlight) at video frame rates with a 720P CMOS image sensor in a compact, low latency camera. Low light imaging is enabled by the combination of enhanced quantum efficiency in the near infrared together with state of the art low noise image sensor design. The quantum efficiency enhancements are achieved by applying Black Silicon, SiOnyx's proprietary ultrafast laser semiconductor processing technology. In the near infrared, silicon's native indirect bandgap results in low absorption coefficients and long absorption lengths. The Black Silicon nanostructured layer fundamentally disrupts this paradigm by enhancing the absorption of light within a thin pixel layer making 5 microns of silicon equivalent to over 300 microns of standard silicon. This results in a demonstrate 10 fold improvements in near infrared sensitivity over incumbent imaging technology while maintaining complete compatibility with standard CMOS image sensor process flows. Applications include surveillance, nightvision, and 1064nm laser see spot. Imaging performance metrics will be discussed. Demonstrated performance characteristics: Pixel size : 5.6 and 10 um Array size: 720P/1.3Mpix Frame rate: 60 Hz Read noise: 2 ele/pixel Spectral sensitivity: 400 to 1200 nm (with 10x QE at 1064nm) Daytime imaging: color (Bayer pattern) Nighttime imaging: moonless starlight conditions 1064nm laser imaging: daytime imaging out to 2Km

New amorphous-silicon image sensor for x-ray diagnostic medical imaging applications

NASA Astrophysics Data System (ADS)

Weisfield, Richard L.; Hartney, Mark A.; Street, Robert A.; Apte, Raj B.

1998-07-01

This paper introduces new high-resolution amorphous Silicon (a-Si) image sensors specifically configured for demonstrating film-quality medical x-ray imaging capabilities. The devices utilizes an x-ray phosphor screen coupled to an array of a-Si photodiodes for detecting visible light, and a-Si thin-film transistors (TFTs) for connecting the photodiodes to external readout electronics. We have developed imagers based on a pixel size of 127 micrometer X 127 micrometer with an approximately page-size imaging area of 244 mm X 195 mm, and array size of 1,536 data lines by 1,920 gate lines, for a total of 2.95 million pixels. More recently, we have developed a much larger imager based on the same pixel pattern, which covers an area of approximately 406 mm X 293 mm, with 2,304 data lines by 3,200 gate lines, for a total of nearly 7.4 million pixels. This is very likely to be the largest image sensor array and highest pixel count detector fabricated on a single substrate. Both imagers connect to a standard PC and are capable of taking an image in a few seconds. Through design rule optimization we have achieved a light sensitive area of 57% and optimized quantum efficiency for x-ray phosphor output in the green part of the spectrum, yielding an average quantum efficiency between 500 and 600 nm of approximately 70%. At the same time, we have managed to reduce extraneous leakage currents on these devices to a few fA per pixel, which allows for very high dynamic range to be achieved. We have characterized leakage currents as a function of photodiode bias, time and temperature to demonstrate high stability over these large sized arrays. At the electronics level, we have adopted a new generation of low noise, charge- sensitive amplifiers coupled to 12-bit A/D converters. Considerable attention was given to reducing electronic noise in order to demonstrate a large dynamic range (over 4,000:1) for medical imaging applications. Through a combination of low data lines capacitance, readout amplifier design, optimized timing, and noise cancellation techniques, we achieve 1,000e to 2,000e of noise for the page size and large size arrays, respectively. This allows for true 12-bit performance and quantum limited images over a wide range of x-ray exposures. Various approaches to reducing line correlated noise have been implemented and will be discussed. Images documenting the improved performance will be presented. Avenues for improvement are under development, including higher resolution 97 micrometer pixel imagers, further improvements in detective quantum efficiency, and characterization of dynamic behavior.

Dynamic Black-Level Correction and Artifact Flagging in the Kepler Data Pipeline

NASA Technical Reports Server (NTRS)

Clarke, B. D.; Kolodziejczak, J. J.; Caldwell, D. A.

2013-01-01

Instrument-induced artifacts in the raw Kepler pixel data include time-varying crosstalk from the fine guidance sensor (FGS) clock signals, manifestations of drifting moiré pattern as locally correlated nonstationary noise and rolling bands in the images which find their way into the calibrated pixel time series and ultimately into the calibrated target flux time series. Using a combination of raw science pixel data, full frame images, reverse-clocked pixel data and ancillary temperature data the Keplerpipeline models and removes the FGS crosstalk artifacts by dynamically adjusting the black level correction. By examining the residuals to the model fits, the pipeline detects and flags spatial regions and time intervals of strong time-varying blacklevel (rolling bands ) on a per row per cadence basis. These flags are made available to downstream users of the data since the uncorrected rolling band artifacts could complicate processing or lead to misinterpretation of instrument behavior as stellar. This model fitting and artifact flagging is performed within the new stand-alone pipeline model called Dynablack. We discuss the implementation of Dynablack in the Kepler data pipeline and present results regarding the improvement in calibrated pixels and the expected improvement in cotrending performances as a result of including FGS corrections in the calibration. We also discuss the effectiveness of the rolling band flagging for downstream users and illustrate with some affected light curves.

Spatial resolution and chest nodule detection: an interesting incidental finding

NASA Astrophysics Data System (ADS)

Toomey, R. J.; McEntee, M. F.; Ryan, J. T.; Evanoff, M. G.; Hayes, A.; Brennan, P. C.

2010-02-01

This study reports an incidental finding from a larger work. It examines the relationship between spatial resolution and nodule detection for chest radiographs. Twelve examining radiologists with the American Board of Radiology read thirty chest radiographs in two conditions - full (1500 × 1500 pixel) resolution, and 300 × 300 pixel resolution linearly interpolated to 1500 × 1500 pixels. All images were surrounded by a 10-pixel sharp grey border to aid in focussing the observer's eye when viewing the comparatively unsharp interpolated images. Fifteen of the images contained a single simulated pulmonary nodule. Observers were asked to rate their confidence that a nodule was present on each radiograph on a scale of 1 (least confidence, certain no lesion is present) to 6 (most confidence, certain a lesion was present). All other abnormalities were to be ignored. No windowing, levelling or magnification of the images was permitted and viewing distance was constrained to approximately 70cm. Images were displayed on a 3 megapixel greyscale monitor. Receiver operating characteristic (ROC) analysis was applied to the results of the readings using the Dorfman-Berbaum-Metz multiplereader, multiple-case method. No statistically significant differences were found with either readers and cases treated as random or with cases treated as fixed. Low spatial frequency information appears to be sufficient for the detection of chest lesion of the type used in this study.

Crossword: A Fully Automated Algorithm for the Segmentation and Quality Control of Protein Microarray Images

PubMed Central

2015-01-01

Biological assays formatted as microarrays have become a critical tool for the generation of the comprehensive data sets required for systems-level understanding of biological processes. Manual annotation of data extracted from images of microarrays, however, remains a significant bottleneck, particularly for protein microarrays due to the sensitivity of this technology to weak artifact signal. In order to automate the extraction and curation of data from protein microarrays, we describe an algorithm called Crossword that logically combines information from multiple approaches to fully automate microarray segmentation. Automated artifact removal is also accomplished by segregating structured pixels from the background noise using iterative clustering and pixel connectivity. Correlation of the location of structured pixels across image channels is used to identify and remove artifact pixels from the image prior to data extraction. This component improves the accuracy of data sets while reducing the requirement for time-consuming visual inspection of the data. Crossword enables a fully automated protocol that is robust to significant spatial and intensity aberrations. Overall, the average amount of user intervention is reduced by an order of magnitude and the data quality is increased through artifact removal and reduced user variability. The increase in throughput should aid the further implementation of microarray technologies in clinical studies. PMID:24417579

Imaging with a small number of photons

PubMed Central

Morris, Peter A.; Aspden, Reuben S.; Bell, Jessica E. C.; Boyd, Robert W.; Padgett, Miles J.

2015-01-01

Low-light-level imaging techniques have application in many diverse fields, ranging from biological sciences to security. A high-quality digital camera based on a multi-megapixel array will typically record an image by collecting of order 105 photons per pixel, but by how much could this photon flux be reduced? In this work we demonstrate a single-photon imaging system based on a time-gated intensified camera from which the image of an object can be inferred from very few detected photons. We show that a ghost-imaging configuration, where the image is obtained from photons that have never interacted with the object, is a useful approach for obtaining images with high signal-to-noise ratios. The use of heralded single photons ensures that the background counts can be virtually eliminated from the recorded images. By applying principles of image compression and associated image reconstruction, we obtain high-quality images of objects from raw data formed from an average of fewer than one detected photon per image pixel. PMID:25557090

Identification of optimal mask size parameter for noise filtering in 99mTc-methylene diphosphonate bone scintigraphy images.

PubMed

Pandey, Anil K; Bisht, Chandan S; Sharma, Param D; ArunRaj, Sreedharan Thankarajan; Taywade, Sameer; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-11-01

Tc-methylene diphosphonate (Tc-MDP) bone scintigraphy images have limited number of counts per pixel. A noise filtering method based on local statistics of the image produces better results than a linear filter. However, the mask size has a significant effect on image quality. In this study, we have identified the optimal mask size that yields a good smooth bone scan image. Forty four bone scan images were processed using mask sizes 3, 5, 7, 9, 11, 13, and 15 pixels. The input and processed images were reviewed in two steps. In the first step, the images were inspected and the mask sizes that produced images with significant loss of clinical details in comparison with the input image were excluded. In the second step, the image quality of the 40 sets of images (each set had input image, and its corresponding three processed images with 3, 5, and 7-pixel masks) was assessed by two nuclear medicine physicians. They selected one good smooth image from each set of images. The image quality was also assessed quantitatively with a line profile. Fisher's exact test was used to find statistically significant differences in image quality processed with 5 and 7-pixel mask at a 5% cut-off. A statistically significant difference was found between the image quality processed with 5 and 7-pixel mask at P=0.00528. The identified optimal mask size to produce a good smooth image was found to be 7 pixels. The best mask size for the John-Sen Lee filter was found to be 7×7 pixels, which yielded Tc-methylene diphosphonate bone scan images with the highest acceptable smoothness.

Plenoptic camera image simulation for reconstruction algorithm verification

NASA Astrophysics Data System (ADS)

Schwiegerling, Jim

2014-09-01

Plenoptic cameras have emerged in recent years as a technology for capturing light field data in a single snapshot. A conventional digital camera can be modified with the addition of a lenslet array to create a plenoptic camera. Two distinct camera forms have been proposed in the literature. The first has the camera image focused onto the lenslet array. The lenslet array is placed over the camera sensor such that each lenslet forms an image of the exit pupil onto the sensor. The second plenoptic form has the lenslet array relaying the image formed by the camera lens to the sensor. We have developed a raytracing package that can simulate images formed by a generalized version of the plenoptic camera. Several rays from each sensor pixel are traced backwards through the system to define a cone of rays emanating from the entrance pupil of the camera lens. Objects that lie within this cone are integrated to lead to a color and exposure level for that pixel. To speed processing three-dimensional objects are approximated as a series of planes at different depths. Repeating this process for each pixel in the sensor leads to a simulated plenoptic image on which different reconstruction algorithms can be tested.

Rayleigh-maximum-likelihood bilateral filter for ultrasound image enhancement.

PubMed

Li, Haiyan; Wu, Jun; Miao, Aimin; Yu, Pengfei; Chen, Jianhua; Zhang, Yufeng

2017-04-17

Ultrasound imaging plays an important role in computer diagnosis since it is non-invasive and cost-effective. However, ultrasound images are inevitably contaminated by noise and speckle during acquisition. Noise and speckle directly impact the physician to interpret the images and decrease the accuracy in clinical diagnosis. Denoising method is an important component to enhance the quality of ultrasound images; however, several limitations discourage the results because current denoising methods can remove noise while ignoring the statistical characteristics of speckle and thus undermining the effectiveness of despeckling, or vice versa. In addition, most existing algorithms do not identify noise, speckle or edge before removing noise or speckle, and thus they reduce noise and speckle while blurring edge details. Therefore, it is a challenging issue for the traditional methods to effectively remove noise and speckle in ultrasound images while preserving edge details. To overcome the above-mentioned limitations, a novel method, called Rayleigh-maximum-likelihood switching bilateral filter (RSBF) is proposed to enhance ultrasound images by two steps: noise, speckle and edge detection followed by filtering. Firstly, a sorted quadrant median vector scheme is utilized to calculate the reference median in a filtering window in comparison with the central pixel to classify the target pixel as noise, speckle or noise-free. Subsequently, the noise is removed by a bilateral filter and the speckle is suppressed by a Rayleigh-maximum-likelihood filter while the noise-free pixels are kept unchanged. To quantitatively evaluate the performance of the proposed method, synthetic ultrasound images contaminated by speckle are simulated by using the speckle model that is subjected to Rayleigh distribution. Thereafter, the corrupted synthetic images are generated by the original image multiplied with the Rayleigh distributed speckle of various signal to noise ratio (SNR) levels and added with Gaussian distributed noise. Meanwhile clinical breast ultrasound images are used to visually evaluate the effectiveness of the method. To examine the performance, comparison tests between the proposed RSBF and six state-of-the-art methods for ultrasound speckle removal are performed on simulated ultrasound images with various noise and speckle levels. The results of the proposed RSBF are satisfying since the Gaussian noise and the Rayleigh speckle are greatly suppressed. The proposed method can improve the SNRs of the enhanced images to nearly 15 and 13 dB compared with images corrupted by speckle as well as images contaminated by speckle and noise under various SNR levels, respectively. The RSBF is effective in enhancing edge while smoothing the speckle and noise in clinical ultrasound images. In the comparison experiments, the proposed method demonstrates its superiority in accuracy and robustness for denoising and edge preserving under various levels of noise and speckle in terms of visual quality as well as numeric metrics, such as peak signal to noise ratio, SNR and root mean squared error. The experimental results show that the proposed method is effective for removing the speckle and the background noise in ultrasound images. The main reason is that it performs a "detect and replace" two-step mechanism. The advantages of the proposed RBSF lie in two aspects. Firstly, each central pixel is classified as noise, speckle or noise-free texture according to the absolute difference between the target pixel and the reference median. Subsequently, the Rayleigh-maximum-likelihood filter and the bilateral filter are switched to eliminate speckle and noise, respectively, while the noise-free pixels are unaltered. Therefore, it is implemented with better accuracy and robustness than the traditional methods. Generally, these traits declare that the proposed RSBF would have significant clinical application.

Method for removing RFI from SAR images

DOEpatents

Doerry, Armin W.

2003-08-19

A method of removing RFI from a SAR by comparing two SAR images on a pixel by pixel basis and selecting the pixel with the lower magnitude to form a composite image. One SAR image is the conventional image produced by the SAR. The other image is created from phase-history data which has been filtered to have the frequency bands containing the RFI removed.

Imaging properties of pixellated scintillators with deep pixels

PubMed Central

Barber, H. Bradford; Fastje, David; Lemieux, Daniel; Grim, Gary P.; Furenlid, Lars R.; Miller, Brian W.; Parkhurst, Philip; Nagarkar, Vivek V.

2015-01-01

We have investigated the light-transport properties of scintillator arrays with long, thin pixels (deep pixels) for use in high-energy gamma-ray imaging. We compared 10×10 pixel arrays of YSO:Ce, LYSO:Ce and BGO (1mm × 1mm × 20 mm pixels) made by Proteus, Inc. with similar 10×10 arrays of LSO:Ce and BGO (1mm × 1mm × 15mm pixels) loaned to us by Saint-Gobain. The imaging and spectroscopic behaviors of these scintillator arrays are strongly affected by the choice of a reflector used as an inter-pixel spacer (3M ESR in the case of the Proteus arrays and white, diffuse-reflector for the Saint-Gobain arrays). We have constructed a 3700-pixel LYSO:Ce Prototype NIF Gamma-Ray Imager for use in diagnosing target compression in inertial confinement fusion. This system was tested at the OMEGA Laser and exhibited significant optical, inter-pixel cross-talk that was traced to the use of a single-layer of ESR film as an inter-pixel spacer. We show how the optical cross-talk can be mapped, and discuss correction procedures. We demonstrate a 10×10 YSO:Ce array as part of an iQID (formerly BazookaSPECT) imager and discuss issues related to the internal activity of 176Lu in LSO:Ce and LYSO:Ce detectors. PMID:26236070

Imaging properties of pixellated scintillators with deep pixels

NASA Astrophysics Data System (ADS)

Barber, H. Bradford; Fastje, David; Lemieux, Daniel; Grim, Gary P.; Furenlid, Lars R.; Miller, Brian W.; Parkhurst, Philip; Nagarkar, Vivek V.

2014-09-01

We have investigated the light-transport properties of scintillator arrays with long, thin pixels (deep pixels) for use in high-energy gamma-ray imaging. We compared 10x10 pixel arrays of YSO:Ce, LYSO:Ce and BGO (1mm x 1mm x 20 mm pixels) made by Proteus, Inc. with similar 10x10 arrays of LSO:Ce and BGO (1mm x 1mm x 15mm pixels) loaned to us by Saint-Gobain. The imaging and spectroscopic behaviors of these scintillator arrays are strongly affected by the choice of a reflector used as an inter-pixel spacer (3M ESR in the case of the Proteus arrays and white, diffuse-reflector for the Saint-Gobain arrays). We have constructed a 3700-pixel LYSO:Ce Prototype NIF Gamma-Ray Imager for use in diagnosing target compression in inertial confinement fusion. This system was tested at the OMEGA Laser and exhibited significant optical, inter-pixel cross-talk that was traced to the use of a single-layer of ESR film as an inter-pixel spacer. We show how the optical cross-talk can be mapped, and discuss correction procedures. We demonstrate a 10x10 YSO:Ce array as part of an iQID (formerly BazookaSPECT) imager and discuss issues related to the internal activity of 176Lu in LSO:Ce and LYSO:Ce detectors.

Use of local noise power spectrum and wavelet analysis in quantitative image quality assurance for EPIDs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Soyoung

Purpose: To investigate the use of local noise power spectrum (NPS) to characterize image noise and wavelet analysis to isolate defective pixels and inter-subpanel flat-fielding artifacts for quantitative quality assurance (QA) of electronic portal imaging devices (EPIDs). Methods: A total of 93 image sets including custom-made bar-pattern images and open exposure images were collected from four iViewGT a-Si EPID systems over three years. Global quantitative metrics such as modulation transform function (MTF), NPS, and detective quantum efficiency (DQE) were computed for each image set. Local NPS was also calculated for individual subpanels by sampling region of interests within each subpanelmore » of the EPID. The 1D NPS, obtained by radially averaging the 2D NPS, was fitted to a power-law function. The r-square value of the linear regression analysis was used as a singular metric to characterize the noise properties of individual subpanels of the EPID. The sensitivity of the local NPS was first compared with the global quantitative metrics using historical image sets. It was then compared with two commonly used commercial QA systems with images collected after applying two different EPID calibration methods (single-level gain and multilevel gain). To detect isolated defective pixels and inter-subpanel flat-fielding artifacts, Haar wavelet transform was applied on the images. Results: Global quantitative metrics including MTF, NPS, and DQE showed little change over the period of data collection. On the contrary, a strong correlation between the local NPS (r-square values) and the variation of the EPID noise condition was observed. The local NPS analysis indicated image quality improvement with the r-square values increased from 0.80 ± 0.03 (before calibration) to 0.85 ± 0.03 (after single-level gain calibration) and to 0.96 ± 0.03 (after multilevel gain calibration), while the commercial QA systems failed to distinguish the image quality improvement between the two calibration methods. With wavelet analysis, defective pixels and inter-subpanel flat-fielding artifacts were clearly identified as spikes after thresholding the inversely transformed images. Conclusions: The proposed local NPS (r-square values) showed superior sensitivity to the noise level variations of individual subpanels compared with global quantitative metrics such as MTF, NPS, and DQE. Wavelet analysis was effective in detecting isolated defective pixels and inter-subpanel flat-fielding artifacts. The proposed methods are promising for the early detection of imaging artifacts of EPIDs.« less

Evaluation of PET Imaging Resolution Using 350 mu{m} Pixelated CZT as a VP-PET Insert Detector

NASA Astrophysics Data System (ADS)

Yin, Yongzhi; Chen, Ximeng; Li, Chongzheng; Wu, Heyu; Komarov, Sergey; Guo, Qingzhen; Krawczynski, Henric; Meng, Ling-Jian; Tai, Yuan-Chuan

2014-02-01

A cadmium-zinc-telluride (CZT) detector with 350 μm pitch pixels was studied in high-resolution positron emission tomography (PET) imaging applications. The PET imaging system was based on coincidence detection between a CZT detector and a lutetium oxyorthosilicate (LSO)-based Inveon PET detector in virtual-pinhole PET geometry. The LSO detector is a 20 ×20 array, with 1.6 mm pitches, and 10 mm thickness. The CZT detector uses ac 20 ×20 ×5 mm substrate, with 350 μm pitch pixelated anodes and a coplanar cathode. A NEMA NU4 Na-22 point source of 250 μm in diameter was imaged by this system. Experiments show that the image resolution of single-pixel photopeak events was 590 μm FWHM while the image resolution of double-pixel photopeak events was 640 μm FWHM. The inclusion of double-pixel full-energy events increased the sensitivity of the imaging system. To validate the imaging experiment, we conducted a Monte Carlo (MC) simulation for the same PET system in Geant4 Application for Emission Tomography. We defined LSO detectors as a scanner ring and 350 μm pixelated CZT detectors as an insert ring. GATE simulated coincidence data were sorted into an insert-scanner sinogram and reconstructed. The image resolution of MC-simulated data (which did not factor in positron range and acolinearity effect) was 460 μm at FWHM for single-pixel events. The image resolutions of experimental data, MC simulated data, and theoretical calculation are all close to 500 μm FWHM when the proposed 350 μm pixelated CZT detector is used as a PET insert. The interpolation algorithm for the charge sharing events was also investigated. The PET image that was reconstructed using the interpolation algorithm shows improved image resolution compared with the image resolution without interpolation algorithm.

Improvement of Reliability of Diffusion Tensor Metrics in Thigh Skeletal Muscles.

PubMed

Keller, Sarah; Chhabra, Avneesh; Ahmed, Shaheen; Kim, Anne C; Chia, Jonathan M; Yamamura, Jin; Wang, Zhiyue J

2018-05-01

Quantitative diffusion tensor imaging (DTI) of skeletal muscles is challenging due to the bias in DTI metrics, such as fractional anisotropy (FA) and mean diffusivity (MD), related to insufficient signal-to-noise ratio (SNR). This study compares the bias of DTI metrics in skeletal muscles via pixel-based and region-of-interest (ROI)-based analysis. DTI of the thigh muscles was conducted on a 3.0-T system in N = 11 volunteers using a fat-suppressed single-shot spin-echo echo planar imaging (SS SE-EPI) sequence with eight repetitions (number of signal averages (NSA) = 4 or 8 for each repeat). The SNR was calculated for different NSAs and estimated for the composite images combining all data (effective NSA = 48) as standard reference. The bias of MD and FA derived by pixel-based and ROI-based quantification were compared at different NSAs. An "intra-ROI diffusion direction dispersion angle (IRDDDA)" was calculated to assess the uniformity of diffusion within the ROI. Using our standard reference image with NSA = 48, the ROI-based and pixel-based measurements agreed for FA and MD. Larger disagreements were observed for the pixel-based quantification at NSA = 4. MD was less sensitive than FA to the noise level. The IRDDDA decreased with higher NSA. At NSA = 4, ROI-based FA showed a lower average bias (0.9% vs. 37.4%) and narrower 95% limits of agreement compared to the pixel-based method. The ROI-based estimation of FA is less prone to bias than the pixel-based estimations when SNR is low. The IRDDDA can be applied as a quantitative quality measure to assess reliability of ROI-based DTI metrics. Copyright © 2018 Elsevier B.V. All rights reserved.

A Hopfield neural network for image change detection.

PubMed

Pajares, Gonzalo

2006-09-01

This paper outlines an optimization relaxation approach based on the analog Hopfield neural network (HNN) for solving the image change detection problem between two images. A difference image is obtained by subtracting pixel by pixel both images. The network topology is built so that each pixel in the difference image is a node in the network. Each node is characterized by its state, which determines if a pixel has changed. An energy function is derived, so that the network converges to stable states. The analog Hopfield's model allows each node to take on analog state values. Unlike most widely used approaches, where binary labels (changed/unchanged) are assigned to each pixel, the analog property provides the strength of the change. The main contribution of this paper is reflected in the customization of the analog Hopfield neural network to derive an automatic image change detection approach. When a pixel is being processed, some existing image change detection procedures consider only interpixel relations on its neighborhood. The main drawback of such approaches is the labeling of this pixel as changed or unchanged according to the information supplied by its neighbors, where its own information is ignored. The Hopfield model overcomes this drawback and for each pixel allows a tradeoff between the influence of its neighborhood and its own criterion. This is mapped under the energy function to be minimized. The performance of the proposed method is illustrated by comparative analysis against some existing image change detection methods.

Quick probabilistic binary image matching: changing the rules of the game

NASA Astrophysics Data System (ADS)

Mustafa, Adnan A. Y.

2016-09-01

A Probabilistic Matching Model for Binary Images (PMMBI) is presented that predicts the probability of matching binary images with any level of similarity. The model relates the number of mappings, the amount of similarity between the images and the detection confidence. We show the advantage of using a probabilistic approach to matching in similarity space as opposed to a linear search in size space. With PMMBI a complete model is available to predict the quick detection of dissimilar binary images. Furthermore, the similarity between the images can be measured to a good degree if the images are highly similar. PMMBI shows that only a few pixels need to be compared to detect dissimilarity between images, as low as two pixels in some cases. PMMBI is image size invariant; images of any size can be matched at the same quick speed. Near-duplicate images can also be detected without much difficulty. We present tests on real images that show the prediction accuracy of the model.

Ultralow-dose, feedback imaging with laser-Compton X-ray and laser-Compton gamma ray sources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barty, Christopher P. J.

Ultralow-dose, x-ray or gamma-ray imaging is based on fast, electronic control of the output of a laser-Compton x-ray or gamma-ray source (LCXS or LCGS). X-ray or gamma-ray shadowgraphs are constructed one (or a few) pixel(s) at a time by monitoring the LCXS or LCGS beam energy required at each pixel of the object to achieve a threshold level of detectability at the detector. An example provides that once the threshold for detection is reached, an electronic or optical signal is sent to the LCXS/LCGS that enables a fast optical switch that diverts, either in space or time the laser pulsesmore » used to create Compton photons. In this way, one prevents the object from being exposed to any further Compton x-rays or gamma-rays until either the laser-Compton beam or the object are moved so that a new pixel location may be illumination.« less

Adaptive box filters for removal of random noise from digital images

USGS Publications Warehouse

Eliason, E.M.; McEwen, A.S.

1990-01-01

We have developed adaptive box-filtering algorithms to (1) remove random bit errors (pixel values with no relation to the image scene) and (2) smooth noisy data (pixels related to the image scene but with an additive or multiplicative component of noise). For both procedures, we use the standard deviation (??) of those pixels within a local box surrounding each pixel, hence they are adaptive filters. This technique effectively reduces speckle in radar images without eliminating fine details. -from Authors

A 25μm pitch LWIR focal plane array with pixel-level 15-bit ADC providing high well capacity and targeting 2mK NETD

NASA Astrophysics Data System (ADS)

Guellec, Fabrice; Peizerat, Arnaud; Tchagaspanian, Michael; de Borniol, Eric; Bisotto, Sylvette; Mollard, Laurent; Castelein, Pierre; Zanatta, Jean-Paul; Maillart, Patrick; Zecri, Michel; Peyrard, Jean-Christophe

2010-04-01

CEA Leti has recently developed a new readout IC (ROIC) with pixel-level ADC for cooled infrared focal plane arrays (FPAs). It operates at 50Hz frame rate in a snapshot Integrate-While-Read (IWR) mode. It targets applications that provide a large amount of integrated charge thanks to a long integration time. The pixel-level analog-to-digital conversion is based on charge packets counting. This technique offers a large well capacity that paves the way for a breakthrough in NETD performances. The 15 bits ADC resolution preserves the excellent detector SNR at full well (3Ge-). These characteristics are essential for LWIR FPAs as broad intra-scene dynamic range imaging requires high sensitivity. The ROIC, featuring a 320x256 array with 25μm pixel pitch, has been designed in a standard 0.18μm CMOS technology. The main design challenges for this digital pixel array (SNR, power consumption and layout density) are discussed. The IC has been hybridized to a LWIR detector fabricated using our in-house HgCdTe process. The first electro-optical test results of the detector dewar assembly are presented. They validate both the pixel-level ADC concept and its circuit implementation. Finally, the benefit of this LWIR FPA in terms of NETD performance is demonstrated.

CMOS foveal image sensor chip

NASA Technical Reports Server (NTRS)

Scott, Peter (Inventor); Sridhar, Ramalingam (Inventor); Bandera, Cesar (Inventor); Xia, Shu (Inventor)

2002-01-01

A foveal image sensor integrated circuit comprising a plurality of CMOS active pixel sensors arranged both within and about a central fovea region of the chip. The pixels in the central fovea region have a smaller size than the pixels arranged in peripheral rings about the central region. A new photocharge normalization scheme and associated circuitry normalizes the output signals from the different size pixels in the array. The pixels are assembled into a multi-resolution rectilinear foveal image sensor chip using a novel access scheme to reduce the number of analog RAM cells needed. Localized spatial resolution declines monotonically with offset from the imager's optical axis, analogous to biological foveal vision.

Rapid Disaster Damage Estimation

NASA Astrophysics Data System (ADS)

Vu, T. T.

2012-07-01

The experiences from recent disaster events showed that detailed information derived from high-resolution satellite images could accommodate the requirements from damage analysts and disaster management practitioners. Richer information contained in such high-resolution images, however, increases the complexity of image analysis. As a result, few image analysis solutions can be practically used under time pressure in the context of post-disaster and emergency responses. To fill the gap in employment of remote sensing in disaster response, this research develops a rapid high-resolution satellite mapping solution built upon a dual-scale contextual framework to support damage estimation after a catastrophe. The target objects are building (or building blocks) and their condition. On the coarse processing level, statistical region merging deployed to group pixels into a number of coarse clusters. Based on majority rule of vegetation index, water and shadow index, it is possible to eliminate the irrelevant clusters. The remaining clusters likely consist of building structures and others. On the fine processing level details, within each considering clusters, smaller objects are formed using morphological analysis. Numerous indicators including spectral, textural and shape indices are computed to be used in a rule-based object classification. Computation time of raster-based analysis highly depends on the image size or number of processed pixels in order words. Breaking into 2 level processing helps to reduce the processed number of pixels and the redundancy of processing irrelevant information. In addition, it allows a data- and tasks- based parallel implementation. The performance is demonstrated with QuickBird images captured a disaster-affected area of Phanga, Thailand by the 2004 Indian Ocean tsunami are used for demonstration of the performance. The developed solution will be implemented in different platforms as well as a web processing service for operational uses.

Report on recent results of the PERCIVAL soft X-ray imager

NASA Astrophysics Data System (ADS)

Khromova, A.; Cautero, G.; Giuressi, D.; Menk, R.; Pinaroli, G.; Stebel, L.; Correa, J.; Marras, A.; Wunderer, C. B.; Lange, S.; Tennert, M.; Niemann, M.; Hirsemann, H.; Smoljanin, S.; Reza, S.; Graafsma, H.; Göttlicher, P.; Shevyakov, I.; Supra, J.; Xia, Q.; Zimmer, M.; Guerrini, N.; Marsh, B.; Sedgwick, I.; Nicholls, T.; Turchetta, R.; Pedersen, U.; Tartoni, N.; Hyun, H. J.; Kim, K. S.; Rah, S. Y.; Hoenk, M. E.; Jewell, A. D.; Jones, T. J.; Nikzad, S.

2016-11-01

The PERCIVAL (Pixelated Energy Resolving CMOS Imager, Versatile And Large) soft X-ray 2D imaging detector is based on stitched, wafer-scale sensors possessing a thick epi-layer, which together with back-thinning and back-side illumination yields elevated quantum efficiency in the photon energy range of 125-1000 eV. Main application fields of PERCIVAL are foreseen in photon science with FELs and synchrotron radiation. This requires high dynamic range up to 105 ph @ 250 eV paired with single photon sensitivity with high confidence at moderate frame rates in the range of 10-120 Hz. These figures imply the availability of dynamic gain switching on a pixel-by-pixel basis and a highly parallel, low noise analog and digital readout, which has been realized in the PERCIVAL sensor layout. Different aspects of the detector performance have been assessed using prototype sensors with different pixel and ADC types. This work will report on the recent test results performed on the newest chip prototypes with the improved pixel and ADC architecture. For the target frame rates in the 10-120 Hz range an average noise floor of 14e- has been determined, indicating the ability of detecting single photons with energies above 250 eV. Owing to the successfully implemented adaptive 3-stage multiple-gain switching, the integrated charge level exceeds 4 · 106 e- or 57000 X-ray photons at 250 eV per frame at 120 Hz. For all gains the noise level remains below the Poisson limit also in high-flux conditions. Additionally, a short overview over the updates on an oncoming 2 Mpixel (P2M) detector system (expected at the end of 2016) will be reported.

Segmentation of suspicious objects in an x-ray image using automated region filling approach

NASA Astrophysics Data System (ADS)

Fu, Kenneth; Guest, Clark; Das, Pankaj

2009-08-01

To accommodate the flow of commerce, cargo inspection systems require a high probability of detection and low false alarm rate while still maintaining a minimum scan speed. Since objects of interest (high atomic-number metals) will often be heavily shielded to avoid detection, any detection algorithm must be able to identify such objects despite the shielding. Since pixels of a shielded object have a greater opacity than the shielding, we use a clustering method to classify objects in the image by pixel intensity levels. We then look within each intensity level region for sub-clusters of pixels with greater opacity than the surrounding region. A region containing an object has an enclosed-contour region (a hole) inside of it. We apply a region filling technique to fill in the hole, which represents a shielded object of potential interest. One method for region filling is seed-growing, which puts a "seed" starting point in the hole area and uses a selected structural element to fill out that region. However, automatic seed point selection is a hard problem; it requires additional information to decide if a pixel is within an enclosed region. Here, we propose a simple, robust method for region filling that avoids the problem of seed point selection. In our approach, we calculate the gradient Gx and Gy at each pixel in a binary image, and fill in 1s between a pair of x1 Gx(x1,y)=-1 and x2 Gx(x2,y)=1, and do the same thing in y-direction. The intersection of the two results will be filled region. We give a detailed discussion of our algorithm, discuss the strengths this method has over other methods, and show results of using our method.

Color constancy using bright-neutral pixels

NASA Astrophysics Data System (ADS)

Wang, Yanfang; Luo, Yupin

2014-03-01

An effective illuminant-estimation approach for color constancy is proposed. Bright and near-neutral pixels are selected to jointly represent the illuminant color and utilized for illuminant estimation. To assess the representing capability of pixels, bright-neutral strength (BNS) is proposed by combining pixel chroma and brightness. Accordingly, a certain percentage of pixels with the largest BNS is selected to be the representative set. For every input image, a proper percentage value is determined via an iterative strategy by seeking the optimal color-corrected image. To compare various color-corrected images of an input image, image color-cast degree (ICCD) is devised using means and standard deviations of RGB channels. Experimental evaluation on standard real-world datasets validates the effectiveness of the proposed approach.

Algorithm for Detecting a Bright Spot in an Image

NASA Technical Reports Server (NTRS)

2009-01-01

An algorithm processes the pixel intensities of a digitized image to detect and locate a circular bright spot, the approximate size of which is known in advance. The algorithm is used to find images of the Sun in cameras aboard the Mars Exploration Rovers. (The images are used in estimating orientations of the Rovers relative to the direction to the Sun.) The algorithm can also be adapted to tracking of circular shaped bright targets in other diverse applications. The first step in the algorithm is to calculate a dark-current ramp a correction necessitated by the scheme that governs the readout of pixel charges in the charge-coupled-device camera in the original Mars Exploration Rover application. In this scheme, the fraction of each frame period during which dark current is accumulated in a given pixel (and, hence, the dark-current contribution to the pixel image-intensity reading) is proportional to the pixel row number. For the purpose of the algorithm, the dark-current contribution to the intensity reading from each pixel is assumed to equal the average of intensity readings from all pixels in the same row, and the factor of proportionality is estimated on the basis of this assumption. Then the product of the row number and the factor of proportionality is subtracted from the reading from each pixel to obtain a dark-current-corrected intensity reading. The next step in the algorithm is to determine the best location, within the overall image, for a window of N N pixels (where N is an odd number) large enough to contain the bright spot of interest plus a small margin. (In the original application, the overall image contains 1,024 by 1,024 pixels, the image of the Sun is about 22 pixels in diameter, and N is chosen to be 29.)

An intermediate significant bit (ISB) watermarking technique using neural networks.

PubMed

Zeki, Akram; Abubakar, Adamu; Chiroma, Haruna

2016-01-01

Prior research studies have shown that the peak signal to noise ratio (PSNR) is the most frequent watermarked image quality metric that is used for determining the levels of strength and weakness of watermarking algorithms. Conversely, normalised cross correlation (NCC) is the most common metric used after attacks were applied to a watermarked image to verify the strength of the algorithm used. Many researchers have used these approaches to evaluate their algorithms. These strategies have been used for a long time, however, which unfortunately limits the value of PSNR and NCC in reflecting the strength and weakness of the watermarking algorithms. This paper considers this issue to determine the threshold values of these two parameters in reflecting the amount of strength and weakness of the watermarking algorithms. We used our novel watermarking technique for embedding four watermarks in intermediate significant bits (ISB) of six image files one-by-one through replacing the image pixels with new pixels and, at the same time, keeping the new pixels very close to the original pixels. This approach gains an improved robustness based on the PSNR and NCC values that were gathered. A neural network model was built that uses the image quality metrics (PSNR and NCC) values obtained from the watermarking of six grey-scale images that use ISB as the desired output and that are trained for each watermarked image's PSNR and NCC. The neural network predicts the watermarked image's PSNR together with NCC after the attacks when a portion of the output of the same or different types of image quality metrics (PSNR and NCC) are obtained. The results indicate that the NCC metric fluctuates before the PSNR values deteriorate.

Parallax barrier engineering for image quality improvement in an autostereoscopic 3D display.

PubMed

Kim, Sung-Kyu; Yoon, Ki-Hyuk; Yoon, Seon Kyu; Ju, Heongkyu

2015-05-18

We present a image quality improvement in a parallax barrier (PB)-based multiview autostereoscopic 3D display system under a real-time tracking of positions of a viewer's eyes. The system presented exploits a parallax barrier engineered to offer significantly improved quality of three-dimensional images for a moving viewer without an eyewear under the dynamic eye tracking. The improved image quality includes enhanced uniformity of image brightness, reduced point crosstalk, and no pseudoscopic effects. We control the relative ratio between two parameters i.e., a pixel size and the aperture of a parallax barrier slit to improve uniformity of image brightness at a viewing zone. The eye tracking that monitors positions of a viewer's eyes enables pixel data control software to turn on only pixels for view images near the viewer's eyes (the other pixels turned off), thus reducing point crosstalk. The eye tracking combined software provides right images for the respective eyes, therefore producing no pseudoscopic effects at its zone boundaries. The viewing zone can be spanned over area larger than the central viewing zone offered by a conventional PB-based multiview autostereoscopic 3D display (no eye tracking). Our 3D display system also provides multiviews for motion parallax under eye tracking. More importantly, we demonstrate substantial reduction of point crosstalk of images at the viewing zone, its level being comparable to that of a commercialized eyewear-assisted 3D display system. The multiview autostereoscopic 3D display presented can greatly resolve the point crosstalk problem, which is one of the critical factors that make it difficult for previous technologies for a multiview autostereoscopic 3D display to replace an eyewear-assisted counterpart.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Becker, Julian; Tate, Mark W.; Shanks, Katherine S.

Pixel Array Detectors (PADs) consist of an x-ray sensor layer bonded pixel-by-pixel to an underlying readout chip. This approach allows both the sensor and the custom pixel electronics to be tailored independently to best match the x-ray imaging requirements. Here we describe the hybridization of CdTe sensors to two different charge-integrating readout chips, the Keck PAD and the Mixed-Mode PAD (MM-PAD), both developed previously in our laboratory. The charge-integrating architecture of each of these PADs extends the instantaneous counting rate by many orders of magnitude beyond that obtainable with photon counting architectures. The Keck PAD chip consists of rapid, 8-frame,more » in-pixel storage elements with framing periods <150 ns. The second detector, the MM-PAD, has an extended dynamic range by utilizing an in-pixel overflow counter coupled with charge removal circuitry activated at each overflow. This allows the recording of signals from the single-photon level to tens of millions of x-rays/pixel/frame while framing at 1 kHz. Both detector chips consist of a 128×128 pixel array with (150 µm){sup 2} pixels.« less

A neural net based architecture for the segmentation of mixed gray-level and binary pictures

NASA Technical Reports Server (NTRS)

Tabatabai, Ali; Troudet, Terry P.

1991-01-01

A neural-net-based architecture is proposed to perform segmentation in real time for mixed gray-level and binary pictures. In this approach, the composite picture is divided into 16 x 16 pixel blocks, which are identified as character blocks or image blocks on the basis of a dichotomy measure computed by an adaptive 16 x 16 neural net. For compression purposes, each image block is further divided into 4 x 4 subblocks; a one-bit nonparametric quantizer is used to encode 16 x 16 character and 4 x 4 image blocks; and the binary map and quantizer levels are obtained through a neural net segmentor over each block. The efficiency of the neural segmentation in terms of computational speed, data compression, and quality of the compressed picture is demonstrated. The effect of weight quantization is also discussed. VLSI implementations of such adaptive neural nets in CMOS technology are described and simulated in real time for a maximum block size of 256 pixels.

Method to improve cancerous lesion detection sensitivity in a dedicated dual-head scintimammography system

DOEpatents

Kieper, Douglas Arthur [Seattle, WA; Majewski, Stanislaw [Morgantown, WV; Welch, Benjamin L [Hampton, VA

2012-07-03

An improved method for enhancing the contrast between background and lesion areas of a breast undergoing dual-head scintimammographic examination comprising: 1) acquiring a pair of digital images from a pair of small FOV or mini gamma cameras compressing the breast under examination from opposing sides; 2) inverting one of the pair of images to align or co-register with the other of the images to obtain co-registered pixel values; 3) normalizing the pair of images pixel-by-pixel by dividing pixel values from each of the two acquired images and the co-registered image by the average count per pixel in the entire breast area of the corresponding detector; and 4) multiplying the number of counts in each pixel by the value obtained in step 3 to produce a normalization enhanced two dimensional contrast map. This enhanced (increased contrast) contrast map enhances the visibility of minor local increases (uptakes) of activity over the background and therefore improves lesion detection sensitivity, especially of small lesions.

Method to improve cancerous lesion detection sensitivity in a dedicated dual-head scintimammography system

DOEpatents

Kieper, Douglas Arthur [Newport News, VA; Majewski, Stanislaw [Yorktown, VA; Welch, Benjamin L [Hampton, VA

2008-10-28

An improved method for enhancing the contrast between background and lesion areas of a breast undergoing dual-head scintimammographic examination comprising: 1) acquiring a pair of digital images from a pair of small FOV or mini gamma cameras compressing the breast under examination from opposing sides; 2) inverting one of the pair of images to align or co-register with the other of the images to obtain co-registered pixel values; 3) normalizing the pair of images pixel-by-pixel by dividing pixel values from each of the two acquired images and the co-registered image by the average count per pixel in the entire breast area of the corresponding detector; and 4) multiplying the number of counts in each pixel by the value obtained in step 3 to produce a normalization enhanced two dimensional contrast map. This enhanced (increased contrast) contrast map enhances the visibility of minor local increases (uptakes) of activity over the background and therefore improves lesion detection sensitivity, especially of small lesions.

Estimating pixel variances in the scenes of staring sensors

DOEpatents

Simonson, Katherine M [Cedar Crest, NM; Ma, Tian J [Albuquerque, NM

2012-01-24

A technique for detecting changes in a scene perceived by a staring sensor is disclosed. The technique includes acquiring a reference image frame and a current image frame of a scene with the staring sensor. A raw difference frame is generated based upon differences between the reference image frame and the current image frame. Pixel error estimates are generated for each pixel in the raw difference frame based at least in part upon spatial error estimates related to spatial intensity gradients in the scene. The pixel error estimates are used to mitigate effects of camera jitter in the scene between the current image frame and the reference image frame.

Variable waveband infrared imager

DOEpatents

Hunter, Scott R.

2013-06-11

A waveband imager includes an imaging pixel that utilizes photon tunneling with a thermally actuated bimorph structure to convert infrared radiation to visible radiation. Infrared radiation passes through a transparent substrate and is absorbed by a bimorph structure formed with a pixel plate. The absorption generates heat which deflects the bimorph structure and pixel plate towards the substrate and into an evanescent electric field generated by light propagating through the substrate. Penetration of the bimorph structure and pixel plate into the evanescent electric field allows a portion of the visible wavelengths propagating through the substrate to tunnel through the substrate, bimorph structure, and/or pixel plate as visible radiation that is proportional to the intensity of the incident infrared radiation. This converted visible radiation may be superimposed over visible wavelengths passed through the imaging pixel.

The CAOS camera platform: ushering in a paradigm change in extreme dynamic range imager design

NASA Astrophysics Data System (ADS)

Riza, Nabeel A.

2017-02-01

Multi-pixel imaging devices such as CCD, CMOS and Focal Plane Array (FPA) photo-sensors dominate the imaging world. These Photo-Detector Array (PDA) devices certainly have their merits including increasingly high pixel counts and shrinking pixel sizes, nevertheless, they are also being hampered by limitations in instantaneous dynamic range, inter-pixel crosstalk, quantum full well capacity, signal-to-noise ratio, sensitivity, spectral flexibility, and in some cases, imager response time. Recently invented is the Coded Access Optical Sensor (CAOS) Camera platform that works in unison with current Photo-Detector Array (PDA) technology to counter fundamental limitations of PDA-based imagers while providing high enough imaging spatial resolution and pixel counts. Using for example the Texas Instruments (TI) Digital Micromirror Device (DMD) to engineer the CAOS camera platform, ushered in is a paradigm change in advanced imager design, particularly for extreme dynamic range applications.

Photodiode area effect on performance of X-ray CMOS active pixel sensors

NASA Astrophysics Data System (ADS)

Kim, M. S.; Kim, Y.; Kim, G.; Lim, K. T.; Cho, G.; Kim, D.

2018-02-01

Compared to conventional TFT-based X-ray imaging devices, CMOS-based X-ray imaging sensors are considered next generation because they can be manufactured in very small pixel pitches and can acquire high-speed images. In addition, CMOS-based sensors have the advantage of integration of various functional circuits within the sensor. The image quality can also be improved by the high fill-factor in large pixels. If the size of the subject is small, the size of the pixel must be reduced as a consequence. In addition, the fill factor must be reduced to aggregate various functional circuits within the pixel. In this study, 3T-APS (active pixel sensor) with photodiodes of four different sizes were fabricated and evaluated. It is well known that a larger photodiode leads to improved overall performance. Nonetheless, if the size of the photodiode is > 1000 μm2, the degree to which the sensor performance increases as the photodiode size increases, is reduced. As a result, considering the fill factor, pixel-pitch > 32 μm is not necessary to achieve high-efficiency image quality. In addition, poor image quality is to be expected unless special sensor-design techniques are included for sensors with a pixel pitch of 25 μm or less.

Semantic segmentation of mFISH images using convolutional networks.

PubMed

Pardo, Esteban; Morgado, José Mário T; Malpica, Norberto

2018-04-30

Multicolor in situ hybridization (mFISH) is a karyotyping technique used to detect major chromosomal alterations using fluorescent probes and imaging techniques. Manual interpretation of mFISH images is a time consuming step that can be automated using machine learning; in previous works, pixel or patch wise classification was employed, overlooking spatial information which can help identify chromosomes. In this work, we propose a fully convolutional semantic segmentation network for the interpretation of mFISH images, which uses both spatial and spectral information to classify each pixel in an end-to-end fashion. The semantic segmentation network developed was tested on samples extracted from a public dataset using cross validation. Despite having no labeling information of the image it was tested on, our algorithm yielded an average correct classification ratio (CCR) of 87.41%. Previously, this level of accuracy was only achieved with state of the art algorithms when classifying pixels from the same image in which the classifier has been trained. These results provide evidence that fully convolutional semantic segmentation networks may be employed in the computer aided diagnosis of genetic diseases with improved performance over the current image analysis methods. © 2018 International Society for Advancement of Cytometry. © 2018 International Society for Advancement of Cytometry.

Hierarchical rendering of trees from precomputed multi-layer z-buffers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Max, N.

1996-02-01

Chen and Williams show how precomputed z-buffer images from different fixed viewing positions can be reprojected to produce an image for a new viewpoint. Here images are precomputed for twigs and branches at various levels in the hierarchical structure of a tree, and adaptively combined, depending on the position of the new viewpoint. The precomputed images contain multiple z levels to avoid missing pixels in the reconstruction, subpixel masks for anti-aliasing, and colors and normals for shading after reprojection.

High dynamic range vision sensor for automotive applications

NASA Astrophysics Data System (ADS)

Grenet, Eric; Gyger, Steve; Heim, Pascal; Heitger, Friedrich; Kaess, Francois; Nussbaum, Pascal; Ruedi, Pierre-Francois

2005-02-01

A 128 x 128 pixels, 120 dB vision sensor extracting at the pixel level the contrast magnitude and direction of local image features is used to implement a lane tracking system. The contrast representation (relative change of illumination) delivered by the sensor is independent of the illumination level. Together with the high dynamic range of the sensor, it ensures a very stable image feature representation even with high spatial and temporal inhomogeneities of the illumination. Dispatching off chip image feature is done according to the contrast magnitude, prioritizing features with high contrast magnitude. This allows to reduce drastically the amount of data transmitted out of the chip, hence the processing power required for subsequent processing stages. To compensate for the low fill factor (9%) of the sensor, micro-lenses have been deposited which increase the sensitivity by a factor of 5, corresponding to an equivalent of 2000 ASA. An algorithm exploiting the contrast representation output by the vision sensor has been developed to estimate the position of a vehicle relative to the road markings. The algorithm first detects the road markings based on the contrast direction map. Then, it performs quadratic fits on selected kernel of 3 by 3 pixels to achieve sub-pixel accuracy on the estimation of the lane marking positions. The resulting precision on the estimation of the vehicle lateral position is 1 cm. The algorithm performs efficiently under a wide variety of environmental conditions, including night and rainy conditions.

Evaluation of the MTF for a-Si:H imaging arrays

NASA Astrophysics Data System (ADS)

Yorkston, John; Antonuk, Larry E.; Seraji, N.; Huang, Weidong; Siewerdsen, Jeffrey H.; El-Mohri, Youcef

1994-05-01

Hydrogenated amorphous silicon imaging arrays are being developed for numerous applications in medical imaging. Diagnostic and megavoltage images have previously been reported and a number of the intrinsic properties of the arrays have been investigated. This paper reports on the first attempt to characterize the intrinsic spatial resolution of the imaging pixels on a 450 micrometers pitch, n-i-p imaging array fabricated at Xerox P.A.R.C. The pre- sampled modulation transfer function was measured by scanning a approximately 25 micrometers wide slit of visible wavelength light across a pixel in both the DATA and FET directions. The results show that the response of the pixel in these orthogonal directions is well described by a simple model that accounts for asymmetries in the pixel response due to geometric aspects of the pixel design.

Multiple image encryption scheme based on pixel exchange operation and vector decomposition

NASA Astrophysics Data System (ADS)

Xiong, Y.; Quan, C.; Tay, C. J.

2018-02-01

We propose a new multiple image encryption scheme based on a pixel exchange operation and a basic vector decomposition in Fourier domain. In this algorithm, original images are imported via a pixel exchange operator, from which scrambled images and pixel position matrices are obtained. Scrambled images encrypted into phase information are imported using the proposed algorithm and phase keys are obtained from the difference between scrambled images and synthesized vectors in a charge-coupled device (CCD) plane. The final synthesized vector is used as an input in a random phase encoding (DRPE) scheme. In the proposed encryption scheme, pixel position matrices and phase keys serve as additional private keys to enhance the security of the cryptosystem which is based on a 4-f system. Numerical simulations are presented to demonstrate the feasibility and robustness of the proposed encryption scheme.

High-polarization-discriminating infrared detection using a single quantum well sandwiched in plasmonic micro-cavity.

PubMed

Li, Qian; Li, ZhiFeng; Li, Ning; Chen, XiaoShuang; Chen, PingPing; Shen, XueChu; Lu, Wei

2014-09-11

Polarimetric imaging has proved its value in medical diagnostics, bionics, remote sensing, astronomy, and in many other wide fields. Pixel-level solid monolithically integrated polarimetric imaging photo-detectors are the trend for infrared polarimetric imaging devices. For better polarimetric imaging performance the high polarization discriminating detectors are very much critical. Here we demonstrate the high infrared light polarization resolving capabilities of a quantum well (QW) detector in hybrid structure of single QW and plasmonic micro-cavity that uses QW as an active structure in the near field regime of plasmonic effect enhanced cavity, in which the photoelectric conversion in such a plasmonic micro-cavity has been realized. The detector's extinction ratio reaches 65 at the wavelength of 14.7 μm, about 6 times enhanced in such a type of pixel-level polarization long wave infrared photodetectors. The enhancement mechanism is attributed to artificial plasmonic modulation on optical propagation and distribution in the plasmonic micro-cavities.

High-Polarization-Discriminating Infrared Detection Using a Single Quantum Well Sandwiched in Plasmonic Micro-Cavity

PubMed Central

Li, Qian; Li, ZhiFeng; Li, Ning; Chen, XiaoShuang; Chen, PingPing; Shen, XueChu; Lu, Wei

2014-01-01

Polarimetric imaging has proved its value in medical diagnostics, bionics, remote sensing, astronomy, and in many other wide fields. Pixel-level solid monolithically integrated polarimetric imaging photo-detectors are the trend for infrared polarimetric imaging devices. For better polarimetric imaging performance the high polarization discriminating detectors are very much critical. Here we demonstrate the high infrared light polarization resolving capabilities of a quantum well (QW) detector in hybrid structure of single QW and plasmonic micro-cavity that uses QW as an active structure in the near field regime of plasmonic effect enhanced cavity, in which the photoelectric conversion in such a plasmonic micro-cavity has been realized. The detector's extinction ratio reaches 65 at the wavelength of 14.7 μm, about 6 times enhanced in such a type of pixel-level polarization long wave infrared photodetectors. The enhancement mechanism is attributed to artificial plasmonic modulation on optical propagation and distribution in the plasmonic micro-cavities. PMID:25208580

Color filter array pattern identification using variance of color difference image

NASA Astrophysics Data System (ADS)

Shin, Hyun Jun; Jeon, Jong Ju; Eom, Il Kyu

2017-07-01

A color filter array is placed on the image sensor of a digital camera to acquire color images. Each pixel uses only one color, since the image sensor can measure only one color per pixel. Therefore, empty pixels are filled using an interpolation process called demosaicing. The original and the interpolated pixels have different statistical characteristics. If the image is modified by manipulation or forgery, the color filter array pattern is altered. This pattern change can be a clue for image forgery detection. However, most forgery detection algorithms have the disadvantage of assuming the color filter array pattern. We present an identification method of the color filter array pattern. Initially, the local mean is eliminated to remove the background effect. Subsequently, the color difference block is constructed to emphasize the difference between the original pixel and the interpolated pixel. The variance measure of the color difference image is proposed as a means of estimating the color filter array configuration. The experimental results show that the proposed method is effective in identifying the color filter array pattern. Compared with conventional methods, our method provides superior performance.

Polarimetric analysis of a CdZnTe spectro-imager under multi-pixel irradiation conditions

NASA Astrophysics Data System (ADS)

Pinto, M.; da Silva, R. M. Curado; Maia, J. M.; Simões, N.; Marques, J.; Pereira, L.; Trindade, A. M. F.; Caroli, E.; Auricchio, N.; Stephen, J. B.; Gonçalves, P.

2016-12-01

So far, polarimetry in high-energy astrophysics has been insufficiently explored due to the complexity of the required detection, electronic and signal processing systems. However, its importance is today largely recognized by the astrophysical community, therefore the next generation of high-energy space instruments will certainly provide polarimetric observations, contemporaneously with spectroscopy and imaging. We have been participating in high-energy observatory proposals submitted to ESA Cosmic Vision calls, such as GRI (Gamma-Ray Imager), DUAL and ASTROGAM, where the main instrument was a spectro-imager with polarimetric capabilities. More recently, the H2020 AHEAD project was launched with the objective to promote more coherent and mature future high-energy space mission proposals. In this context of high-energy proposal development, we have tested a CdZnTe detection plane prototype polarimeter under a partially polarized gamma-ray beam generated from an aluminum target irradiated by a 22Na (511 keV) radioactive source. The polarized beam cross section was 1 cm2, allowing the irradiation of a wide multi-pixelated area where all the pixels operate simultaneously as a scatterer and as an absorber. The methods implemented to analyze such multi-pixel irradiation are similar to those required to analyze a spectro-imager polarimeter operating in space, since celestial source photons should irradiate its full pixilated area. Correction methods to mitigate systematic errors inherent to CdZnTe and to the experimental conditions were also implemented. The polarization level ( 40%) and the polarization angle (precision of ±5° up to ±9°) obtained under multi-pixel irradiation conditions are presented and compared with simulated data.

Information extraction from multivariate images

NASA Technical Reports Server (NTRS)

Park, S. K.; Kegley, K. A.; Schiess, J. R.

1986-01-01

An overview of several multivariate image processing techniques is presented, with emphasis on techniques based upon the principal component transformation (PCT). Multiimages in various formats have a multivariate pixel value, associated with each pixel location, which has been scaled and quantized into a gray level vector, and the bivariate of the extent to which two images are correlated. The PCT of a multiimage decorrelates the multiimage to reduce its dimensionality and reveal its intercomponent dependencies if some off-diagonal elements are not small, and for the purposes of display the principal component images must be postprocessed into multiimage format. The principal component analysis of a multiimage is a statistical analysis based upon the PCT whose primary application is to determine the intrinsic component dimensionality of the multiimage. Computational considerations are also discussed.

Graph-based surface reconstruction from stereo pairs using image segmentation

NASA Astrophysics Data System (ADS)

Bleyer, Michael; Gelautz, Margrit

2005-01-01

This paper describes a novel stereo matching algorithm for epipolar rectified images. The method applies colour segmentation on the reference image. The use of segmentation makes the algorithm capable of handling large untextured regions, estimating precise depth boundaries and propagating disparity information to occluded regions, which are challenging tasks for conventional stereo methods. We model disparity inside a segment by a planar equation. Initial disparity segments are clustered to form a set of disparity layers, which are planar surfaces that are likely to occur in the scene. Assignments of segments to disparity layers are then derived by minimization of a global cost function via a robust optimization technique that employs graph cuts. The cost function is defined on the pixel level, as well as on the segment level. While the pixel level measures the data similarity based on the current disparity map and detects occlusions symmetrically in both views, the segment level propagates the segmentation information and incorporates a smoothness term. New planar models are then generated based on the disparity layers' spatial extents. Results obtained for benchmark and self-recorded image pairs indicate that the proposed method is able to compete with the best-performing state-of-the-art algorithms.

Development of a 750x750 pixels CMOS imager sensor for tracking applications

NASA Astrophysics Data System (ADS)

Larnaudie, Franck; Guardiola, Nicolas; Saint-Pé, Olivier; Vignon, Bruno; Tulet, Michel; Davancens, Robert; Magnan, Pierre; Corbière, Franck; Martin-Gonthier, Philippe; Estribeau, Magali

2017-11-01

Solid-state optical sensors are now commonly used in space applications (navigation cameras, astronomy imagers, tracking sensors...). Although the charge-coupled devices are still widely used, the CMOS image sensor (CIS), which performances are continuously improving, is a strong challenger for Guidance, Navigation and Control (GNC) systems. This paper describes a 750x750 pixels CMOS image sensor that has been specially designed and developed for star tracker and tracking sensor applications. Such detector, that is featuring smart architecture enabling very simple and powerful operations, is built using the AMIS 0.5μm CMOS technology. It contains 750x750 rectangular pixels with 20μm pitch. The geometry of the pixel sensitive zone is optimized for applications based on centroiding measurements. The main feature of this device is the on-chip control and timing function that makes the device operation easier by drastically reducing the number of clocks to be applied. This powerful function allows the user to operate the sensor with high flexibility: measurement of dark level from masked lines, direct access to the windows of interest… A temperature probe is also integrated within the CMOS chip allowing a very precise measurement through the video stream. A complete electro-optical characterization of the sensor has been performed. The major parameters have been evaluated: dark current and its uniformity, read-out noise, conversion gain, Fixed Pattern Noise, Photo Response Non Uniformity, quantum efficiency, Modulation Transfer Function, intra-pixel scanning. The characterization tests are detailed in the paper. Co60 and protons irradiation tests have been also carried out on the image sensor and the results are presented. The specific features of the 750x750 image sensor such as low power CMOS design (3.3V, power consumption<100mW), natural windowing (that allows efficient and robust tracking algorithms), simple proximity electronics (because of the on-chip control and timing function) enabling a high flexibility architecture, make this imager a good candidate for high performance tracking applications.

Unification of two fractal families

NASA Astrophysics Data System (ADS)

Liu, Ying

1995-06-01

Barnsley and Hurd classify the fractal images into two families: iterated function system fractals (IFS fractals) and fractal transform fractals, or local iterated function system fractals (LIFS fractals). We will call IFS fractals, class 2 fractals and LIFS fractals, class 3 fractals. In this paper, we will unify these two approaches plus another family of fractals, the class 5 fractals. The basic idea is given as follows: a dynamical system can be represented by a digraph, the nodes in a digraph can be divided into two parts: transient states and persistent states. For bilevel images, a persistent node is a black pixel. A transient node is a white pixel. For images with more than two gray levels, a stochastic digraph is used. A transient node is a pixel with the intensity of 0. The intensity of a persistent node is determined by a relative frequency. In this way, the two families of fractals can be generated in a similar way. In this paper, we will first present a classification of dynamical systems and introduce the transformation based on digraphs, then we will unify the two approaches for fractal binary images. We will compare the decoding algorithms of the two families. Finally, we will generalize the discussion to continuous-tone images.

Spatial clustering of pixels of a multispectral image

DOEpatents

Conger, James Lynn

2014-08-19

A method and system for clustering the pixels of a multispectral image is provided. A clustering system computes a maximum spectral similarity score for each pixel that indicates the similarity between that pixel and the most similar neighboring. To determine the maximum similarity score for a pixel, the clustering system generates a similarity score between that pixel and each of its neighboring pixels and then selects the similarity score that represents the highest similarity as the maximum similarity score. The clustering system may apply a filtering criterion based on the maximum similarity score so that pixels with similarity scores below a minimum threshold are not clustered. The clustering system changes the current pixel values of the pixels in a cluster based on an averaging of the original pixel values of the pixels in the cluster.

Recognizable or Not: Towards Image Semantic Quality Assessment for Compression

NASA Astrophysics Data System (ADS)

Liu, Dong; Wang, Dandan; Li, Houqiang

2017-12-01

Traditionally, image compression was optimized for the pixel-wise fidelity or the perceptual quality of the compressed images given a bit-rate budget. But recently, compressed images are more and more utilized for automatic semantic analysis tasks such as recognition and retrieval. For these tasks, we argue that the optimization target of compression is no longer perceptual quality, but the utility of the compressed images in the given automatic semantic analysis task. Accordingly, we propose to evaluate the quality of the compressed images neither at pixel level nor at perceptual level, but at semantic level. In this paper, we make preliminary efforts towards image semantic quality assessment (ISQA), focusing on the task of optical character recognition (OCR) from compressed images. We propose a full-reference ISQA measure by comparing the features extracted from text regions of original and compressed images. We then propose to integrate the ISQA measure into an image compression scheme. Experimental results show that our proposed ISQA measure is much better than PSNR and SSIM in evaluating the semantic quality of compressed images; accordingly, adopting our ISQA measure to optimize compression for OCR leads to significant bit-rate saving compared to using PSNR or SSIM. Moreover, we perform subjective test about text recognition from compressed images, and observe that our ISQA measure has high consistency with subjective recognizability. Our work explores new dimensions in image quality assessment, and demonstrates promising direction to achieve higher compression ratio for specific semantic analysis tasks.

Using compressive measurement to obtain images at ultra low-light-level

NASA Astrophysics Data System (ADS)

Ke, Jun; Wei, Ping

2013-08-01

In this paper, a compressive imaging architecture is used for ultra low-light-level imaging. In such a system, features, instead of object pixels, are imaged onto a photocathode, and then magnified by an image intensifier. By doing so, system measurement SNR is increased significantly. Therefore, the new system can image objects at ultra low-ligh-level, while a conventional system has difficulty. PCA projection is used to collect feature measurements in this work. Linear Wiener operator and nonlinear method based on FoE model are used to reconstruct objects. Root mean square error (RMSE) is used to quantify system reconstruction quality.

Wavelength scanning achieves pixel super-resolution in holographic on-chip microscopy

NASA Astrophysics Data System (ADS)

Luo, Wei; Göröcs, Zoltan; Zhang, Yibo; Feizi, Alborz; Greenbaum, Alon; Ozcan, Aydogan

2016-03-01

Lensfree holographic on-chip imaging is a potent solution for high-resolution and field-portable bright-field imaging over a wide field-of-view. Previous lensfree imaging approaches utilize a pixel super-resolution technique, which relies on sub-pixel lateral displacements between the lensfree diffraction patterns and the image sensor's pixel-array, to achieve sub-micron resolution under unit magnification using state-of-the-art CMOS imager chips, commonly used in e.g., mobile-phones. Here we report, for the first time, a wavelength scanning based pixel super-resolution technique in lensfree holographic imaging. We developed an iterative super-resolution algorithm, which generates high-resolution reconstructions of the specimen from low-resolution (i.e., under-sampled) diffraction patterns recorded at multiple wavelengths within a narrow spectral range (e.g., 10-30 nm). Compared with lateral shift-based pixel super-resolution, this wavelength scanning approach does not require any physical shifts in the imaging setup, and the resolution improvement is uniform in all directions across the sensor-array. Our wavelength scanning super-resolution approach can also be integrated with multi-height and/or multi-angle on-chip imaging techniques to obtain even higher resolution reconstructions. For example, using wavelength scanning together with multi-angle illumination, we achieved a halfpitch resolution of 250 nm, corresponding to a numerical aperture of 1. In addition to pixel super-resolution, the small scanning steps in wavelength also enable us to robustly unwrap phase, revealing the specimen's optical path length in our reconstructed images. We believe that this new wavelength scanning based pixel super-resolution approach can provide competitive microscopy solutions for high-resolution and field-portable imaging needs, potentially impacting tele-pathology applications in resource-limited-settings.

Local gray level S-curve transformation - A generalized contrast enhancement technique for medical images.

PubMed

Gandhamal, Akash; Talbar, Sanjay; Gajre, Suhas; Hani, Ahmad Fadzil M; Kumar, Dileep

2017-04-01

Most medical images suffer from inadequate contrast and brightness, which leads to blurred or weak edges (low contrast) between adjacent tissues resulting in poor segmentation and errors in classification of tissues. Thus, contrast enhancement to improve visual information is extremely important in the development of computational approaches for obtaining quantitative measurements from medical images. In this research, a contrast enhancement algorithm that applies gray-level S-curve transformation technique locally in medical images obtained from various modalities is investigated. The S-curve transformation is an extended gray level transformation technique that results into a curve similar to a sigmoid function through a pixel to pixel transformation. This curve essentially increases the difference between minimum and maximum gray values and the image gradient, locally thereby, strengthening edges between adjacent tissues. The performance of the proposed technique is determined by measuring several parameters namely, edge content (improvement in image gradient), enhancement measure (degree of contrast enhancement), absolute mean brightness error (luminance distortion caused by the enhancement), and feature similarity index measure (preservation of the original image features). Based on medical image datasets comprising 1937 images from various modalities such as ultrasound, mammograms, fluorescent images, fundus, X-ray radiographs and MR images, it is found that the local gray-level S-curve transformation outperforms existing techniques in terms of improved contrast and brightness, resulting in clear and strong edges between adjacent tissues. The proposed technique can be used as a preprocessing tool for effective segmentation and classification of tissue structures in medical images. Copyright © 2017 Elsevier Ltd. All rights reserved.

The AAPM/RSNA physics tutorial for residents: digital fluoroscopy.

PubMed

Pooley, R A; McKinney, J M; Miller, D A

2001-01-01

A digital fluoroscopy system is most commonly configured as a conventional fluoroscopy system (tube, table, image intensifier, video system) in which the analog video signal is converted to and stored as digital data. Other methods of acquiring the digital data (eg, digital or charge-coupled device video and flat-panel detectors) will become more prevalent in the future. Fundamental concepts related to digital imaging in general include binary numbers, pixels, and gray levels. Digital image data allow the convenient use of several image processing techniques including last image hold, gray-scale processing, temporal frame averaging, and edge enhancement. Real-time subtraction of digital fluoroscopic images after injection of contrast material has led to widespread use of digital subtraction angiography (DSA). Additional image processing techniques used with DSA include road mapping, image fade, mask pixel shift, frame summation, and vessel size measurement. Peripheral angiography performed with an automatic moving table allows imaging of the peripheral vasculature with a single contrast material injection.

A Decision-Based Modified Total Variation Diffusion Method for Impulse Noise Removal

PubMed Central

Zhu, Qingxin; Song, Xiuli; Tao, Jinsong

2017-01-01

Impulsive noise removal usually employs median filtering, switching median filtering, the total variation L1 method, and variants. These approaches however often introduce excessive smoothing and can result in extensive visual feature blurring and thus are suitable only for images with low density noise. A new method to remove noise is proposed in this paper to overcome this limitation, which divides pixels into different categories based on different noise characteristics. If an image is corrupted by salt-and-pepper noise, the pixels are divided into corrupted and noise-free; if the image is corrupted by random valued impulses, the pixels are divided into corrupted, noise-free, and possibly corrupted. Pixels falling into different categories are processed differently. If a pixel is corrupted, modified total variation diffusion is applied; if the pixel is possibly corrupted, weighted total variation diffusion is applied; otherwise, the pixel is left unchanged. Experimental results show that the proposed method is robust to different noise strengths and suitable for different images, with strong noise removal capability as shown by PSNR/SSIM results as well as the visual quality of restored images. PMID:28536602

SAR Image Change Detection Based on Fuzzy Markov Random Field Model

NASA Astrophysics Data System (ADS)

Zhao, J.; Huang, G.; Zhao, Z.

2018-04-01

Most existing SAR image change detection algorithms only consider single pixel information of different images, and not consider the spatial dependencies of image pixels. So the change detection results are susceptible to image noise, and the detection effect is not ideal. Markov Random Field (MRF) can make full use of the spatial dependence of image pixels and improve detection accuracy. When segmenting the difference image, different categories of regions have a high degree of similarity at the junction of them. It is difficult to clearly distinguish the labels of the pixels near the boundaries of the judgment area. In the traditional MRF method, each pixel is given a hard label during iteration. So MRF is a hard decision in the process, and it will cause loss of information. This paper applies the combination of fuzzy theory and MRF to the change detection of SAR images. The experimental results show that the proposed method has better detection effect than the traditional MRF method.

Image indexing using color correlograms

DOEpatents

Huang, Jing; Kumar, Shanmugasundaram Ravi; Mitra, Mandar; Zhu, Wei-Jing

2001-01-01

A color correlogram is a three-dimensional table indexed by color and distance between pixels which expresses how the spatial correlation of color changes with distance in a stored image. The color correlogram may be used to distinguish an image from other images in a database. To create a color correlogram, the colors in the image are quantized into m color values, c.sub.i . . . c.sub.m. Also, the distance values k.epsilon.[d] to be used in the correlogram are determined where [d] is the set of distances between pixels in the image, and where dmax is the maximum distance measurement between pixels in the image. Each entry (i, j, k) in the table is the probability of finding a pixel of color c.sub.i at a selected distance k from a pixel of color c.sub.i. A color autocorrelogram, which is a restricted version of the color correlogram that considers color pairs of the form (i,i) only, may also be used to identify an image.

The effect of imposing 'fractional abundance constraints' onto the multilayer perceptron for sub-pixel land cover classification

NASA Astrophysics Data System (ADS)

Heremans, Stien; Suykens, Johan A. K.; Van Orshoven, Jos

2016-02-01

To be physically interpretable, sub-pixel land cover fractions or abundances should fulfill two constraints, the Abundance Non-negativity Constraint (ANC) and the Abundance Sum-to-one Constraint (ASC). This paper focuses on the effect of imposing these constraints onto the MultiLayer Perceptron (MLP) for a multi-class sub-pixel land cover classification of a time series of low resolution MODIS-images covering the northern part of Belgium. Two constraining modes were compared, (i) an in-training approach that uses 'softmax' as the transfer function in the MLP's output layer and (ii) a post-training approach that linearly rescales the outputs of the unconstrained MLP. Our results demonstrate that the pixel-level prediction accuracy is markedly increased by the explicit enforcement, both in-training and post-training, of the ANC and the ASC. For aggregations of pixels (municipalities), the constrained perceptrons perform at least as well as their unconstrained counterparts. Although the difference in performance between the in-training and post-training approach is small, we recommend the former for integrating the fractional abundance constraints into MLPs meant for sub-pixel land cover estimation, regardless of the targeted level of spatial aggregation.

Experimental single-chip color HDTV image acquisition system with 8M-pixel CMOS image sensor

NASA Astrophysics Data System (ADS)

Shimamoto, Hiroshi; Yamashita, Takayuki; Funatsu, Ryohei; Mitani, Kohji; Nojiri, Yuji

2006-02-01

We have developed an experimental single-chip color HDTV image acquisition system using 8M-pixel CMOS image sensor. The sensor has 3840 × 2160 effective pixels and is progressively scanned at 60 frames per second. We describe the color filter array and interpolation method to improve image quality with a high-pixel-count single-chip sensor. We also describe an experimental image acquisition system we used to measured spatial frequency characteristics in the horizontal direction. The results indicate good prospects for achieving a high quality single chip HDTV camera that reduces pseudo signals and maintains high spatial frequency characteristics within the frequency band for HDTV.

Travel time tomography with local image regularization by sparsity constrained dictionary learning

NASA Astrophysics Data System (ADS)

Bianco, M.; Gerstoft, P.

2017-12-01

We propose a regularization approach for 2D seismic travel time tomography which models small rectangular groups of slowness pixels, within an overall or `global' slowness image, as sparse linear combinations of atoms from a dictionary. The groups of slowness pixels are referred to as patches and a dictionary corresponds to a collection of functions or `atoms' describing the slowness in each patch. These functions could for example be wavelets.The patch regularization is incorporated into the global slowness image. The global image models the broad features, while the local patch images incorporate prior information from the dictionary. Further, high resolution slowness within patches is permitted if the travel times from the global estimates support it. The proposed approach is formulated as an algorithm, which is repeated until convergence is achieved: 1) From travel times, find the global slowness image with a minimum energy constraint on the pixel variance relative to a reference. 2) Find the patch level solutions to fit the global estimate as a sparse linear combination of dictionary atoms.3) Update the reference as the weighted average of the patch level solutions.This approach relies on the redundancy of the patches in the seismic image. Redundancy means that the patches are repetitions of a finite number of patterns, which are described by the dictionary atoms. Redundancy in the earth's structure was demonstrated in previous works in seismics where dictionaries of wavelet functions regularized inversion. We further exploit redundancy of the patches by using dictionary learning algorithms, a form of unsupervised machine learning, to estimate optimal dictionaries from the data in parallel with the inversion. We demonstrate our approach on densely, but irregularly sampled synthetic seismic images.

Single pulse two-photon fluorescence lifetime imaging (SP-FLIM) with MHz pixel rate and an all fiber based setup

NASA Astrophysics Data System (ADS)

Eibl, Matthias; Karpf, Sebastian; Hakert, Hubertus; Weng, Daniel; Pfeiffer, Tom; Kolb, Jan Philip; Huber, Robert

2017-07-01

Newly developed microscopy methods have the goal to give researches in bio-molecular science a better understanding of processes ongoing on a cellular level. Especially two-photon excited fluorescence (TPEF) microscopy is a readily applied and widespread modality. Compared to one photon fluorescence imaging, it is possible to image not only the surface but also deeper lying structures. Together with fluorescence lifetime imaging (FLIM), which provides information on the chemical composition of a specimen, deeper insights on a molecular level can be gained. However, the need for elaborate light sources for TPEF and speed limitations for FLIM hinder an even wider application. In this contribution, we present a way to overcome this limitations by combining a robust and inexpensive fiber laser for nonlinear excitation with a fast analog digitization method for rapid FLIM imaging. The applied sub nanosecond pulsed laser source is perfectly suited for fiber delivery as typically limiting non-linear effects like self-phase or cross-phase modulation (SPM, XPM) are negligible. Furthermore, compared to the typically applied femtosecond pulses, our longer pulses produce much more fluorescence photons per single shot. In this paper, we show that this higher number of fluorescence photons per pulse combined with a high analog bandwidth detection makes it possible to not only use a single pulse per pixel for TPEF imaging but also to resolve the exponential time decay for FLIM. To evaluate our system, we acquired FLIM images of a dye solution with single exponential behavior to assess the accuracy of our lifetime determination and also FLIM images of a plant stem at a pixel rate of 1 MHz to show the speed performance of our single pulse two-photon FLIM (SP-FLIM) system.

System for Continuous Delivery of MODIS Imagery to Internet Mapping Applications

NASA Technical Reports Server (NTRS)

Plesea, Lucian

2008-01-01

This software represents a complete, unsupervised processing chain that generates a continuously updating global image of the Earth from the most recent available MODIS Level 1B scenes. The software constantly updates a global image of the Earth at 250 m per pixel.

High resolution phoswich gamma-ray imager utilizing monolithic MPPC arrays with submillimeter pixelized crystals

NASA Astrophysics Data System (ADS)

Kato, T.; Kataoka, J.; Nakamori, T.; Kishimoto, A.; Yamamoto, S.; Sato, K.; Ishikawa, Y.; Yamamura, K.; Kawabata, N.; Ikeda, H.; Kamada, K.

2013-05-01

We report the development of a high spatial resolution tweezers-type coincidence gamma-ray camera for medical imaging. This application consists of large-area monolithic Multi-Pixel Photon Counters (MPPCs) and submillimeter pixelized scintillator matrices. The MPPC array has 4 × 4 channels with a three-side buttable, very compact package. For typical operational gain of 7.5 × 105 at + 20 °C, gain fluctuation over the entire MPPC device is only ± 5.6%, and dark count rates (as measured at the 1 p.e. level) amount to <= 400 kcps per channel. We selected Ce-doped (Lu,Y)2(SiO4)O (Ce:LYSO) and a brand-new scintillator, Ce-doped Gd3Al2Ga3O12 (Ce:GAGG) due to their high light yield and density. To improve the spatial resolution, these scintillators were fabricated into 15 × 15 matrices of 0.5 × 0.5 mm2 pixels. The Ce:LYSO and Ce:GAGG scintillator matrices were assembled into phosphor sandwich (phoswich) detectors, and then coupled to the MPPC array along with an acrylic light guide measuring 1 mm thick, and with summing operational amplifiers that compile the signals into four position-encoded analog outputs being used for signal readout. Spatial resolution of 1.1 mm was achieved with the coincidence imaging system using a 22Na point source. These results suggest that the gamma-ray imagers offer excellent potential for applications in high spatial medical imaging.

High speed imager test station

DOEpatents

Yates, George J.; Albright, Kevin L.; Turko, Bojan T.

1995-01-01

A test station enables the performance of a solid state imager (herein called a focal plane array or FPA) to be determined at high image frame rates. A programmable waveform generator is adapted to generate clock pulses at determinable rates for clock light-induced charges from a FPA. The FPA is mounted on an imager header board for placing the imager in operable proximity to level shifters for receiving the clock pulses and outputting pulses effective to clock charge from the pixels forming the FPA. Each of the clock level shifters is driven by leading and trailing edge portions of the clock pulses to reduce power dissipation in the FPA. Analog circuits receive output charge pulses clocked from the FPA pixels. The analog circuits condition the charge pulses to cancel noise in the pulses and to determine and hold a peak value of the charge for digitizing. A high speed digitizer receives the peak signal value and outputs a digital representation of each one of the charge pulses. A video system then displays an image associated with the digital representation of the output charge pulses clocked from the FPA. In one embodiment, the FPA image is formatted to a standard video format for display on conventional video equipment.

High speed imager test station

DOEpatents

Yates, G.J.; Albright, K.L.; Turko, B.T.

1995-11-14

A test station enables the performance of a solid state imager (herein called a focal plane array or FPA) to be determined at high image frame rates. A programmable waveform generator is adapted to generate clock pulses at determinable rates for clock light-induced charges from a FPA. The FPA is mounted on an imager header board for placing the imager in operable proximity to level shifters for receiving the clock pulses and outputting pulses effective to clock charge from the pixels forming the FPA. Each of the clock level shifters is driven by leading and trailing edge portions of the clock pulses to reduce power dissipation in the FPA. Analog circuits receive output charge pulses clocked from the FPA pixels. The analog circuits condition the charge pulses to cancel noise in the pulses and to determine and hold a peak value of the charge for digitizing. A high speed digitizer receives the peak signal value and outputs a digital representation of each one of the charge pulses. A video system then displays an image associated with the digital representation of the output charge pulses clocked from the FPA. In one embodiment, the FPA image is formatted to a standard video format for display on conventional video equipment. 12 figs.

Noise Reduction Effect of Multiple-Sampling-Based Signal-Readout Circuits for Ultra-Low Noise CMOS Image Sensors.

PubMed

Kawahito, Shoji; Seo, Min-Woong

2016-11-06

This paper discusses the noise reduction effect of multiple-sampling-based signal readout circuits for implementing ultra-low-noise image sensors. The correlated multiple sampling (CMS) technique has recently become an important technology for high-gain column readout circuits in low-noise CMOS image sensors (CISs). This paper reveals how the column CMS circuits, together with a pixel having a high-conversion-gain charge detector and low-noise transistor, realizes deep sub-electron read noise levels based on the analysis of noise components in the signal readout chain from a pixel to the column analog-to-digital converter (ADC). The noise measurement results of experimental CISs are compared with the noise analysis and the effect of noise reduction to the sampling number is discussed at the deep sub-electron level. Images taken with three CMS gains of two, 16, and 128 show distinct advantage of image contrast for the gain of 128 (noise(median): 0.29 e - rms ) when compared with the CMS gain of two (2.4 e - rms ), or 16 (1.1 e - rms ).

Noise Reduction Effect of Multiple-Sampling-Based Signal-Readout Circuits for Ultra-Low Noise CMOS Image Sensors

PubMed Central

Kawahito, Shoji; Seo, Min-Woong

2016-01-01

This paper discusses the noise reduction effect of multiple-sampling-based signal readout circuits for implementing ultra-low-noise image sensors. The correlated multiple sampling (CMS) technique has recently become an important technology for high-gain column readout circuits in low-noise CMOS image sensors (CISs). This paper reveals how the column CMS circuits, together with a pixel having a high-conversion-gain charge detector and low-noise transistor, realizes deep sub-electron read noise levels based on the analysis of noise components in the signal readout chain from a pixel to the column analog-to-digital converter (ADC). The noise measurement results of experimental CISs are compared with the noise analysis and the effect of noise reduction to the sampling number is discussed at the deep sub-electron level. Images taken with three CMS gains of two, 16, and 128 show distinct advantage of image contrast for the gain of 128 (noise(median): 0.29 e−rms) when compared with the CMS gain of two (2.4 e−rms), or 16 (1.1 e−rms). PMID:27827972

Random On-Board Pixel Sampling (ROPS) X-Ray Camera

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Zhehui; Iaroshenko, O.; Li, S.

Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. Here we first illustratemore » the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.« less

A compressed sensing X-ray camera with a multilayer architecture

NASA Astrophysics Data System (ADS)

Wang, Zhehui; Iaroshenko, O.; Li, S.; Liu, T.; Parab, N.; Chen, W. W.; Chu, P.; Kenyon, G. T.; Lipton, R.; Sun, K.-X.

2018-01-01

Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. Here we first illustrate the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.

An efficient approach for pixel decomposition to increase the spatial resolution of land surface temperature images from MODIS thermal infrared band data.

PubMed

Wang, Fei; Qin, Zhihao; Li, Wenjuan; Song, Caiying; Karnieli, Arnon; Zhao, Shuhe

2014-12-25

Land surface temperature (LST) images retrieved from the thermal infrared (TIR) band data of Moderate Resolution Imaging Spectroradiometer (MODIS) have much lower spatial resolution than the MODIS visible and near-infrared (VNIR) band data. The coarse pixel scale of MODIS LST images (1000 m under nadir) have limited their capability in applying to many studies required high spatial resolution in comparison of the MODIS VNIR band data with pixel scale of 250-500 m. In this paper we intend to develop an efficient approach for pixel decomposition to increase the spatial resolution of MODIS LST image using the VNIR band data as assistance. The unique feature of this approach is to maintain the thermal radiance of parent pixels in the MODIS LST image unchanged after they are decomposed into the sub-pixels in the resulted image. There are two important steps in the decomposition: initial temperature estimation and final temperature determination. Therefore the approach can be termed double-step pixel decomposition (DSPD). Both steps involve a series of procedures to achieve the final result of decomposed LST image, including classification of the surface patterns, establishment of LST change with normalized difference of vegetation index (NDVI) and building index (NDBI), reversion of LST into thermal radiance through Planck equation, and computation of weights for the sub-pixels of the resulted image. Since the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with much higher spatial resolution than MODIS data was on-board the same platform (Terra) as MODIS for Earth observation, an experiment had been done in the study to validate the accuracy and efficiency of our approach for pixel decomposition. The ASTER LST image was used as the reference to compare with the decomposed LST image. The result showed that the spatial distribution of the decomposed LST image was very similar to that of the ASTER LST image with a root mean square error (RMSE) of 2.7 K for entire image. Comparison with the evaluation DisTrad (E-DisTrad) and re-sampling methods for pixel decomposition also indicate that our DSPD has the lowest RMSE in all cases, including urban region, water bodies, and natural terrain. The obvious increase in spatial resolution remarkably uplifts the capability of the coarse MODIS LST images in highlighting the details of LST variation. Therefore it can be concluded that, in spite of complicated procedures, the proposed DSPD approach provides an alternative to improve the spatial resolution of MODIS LST image hence expand its applicability to the real world.

Design, optimization and evaluation of a "smart" pixel sensor array for low-dose digital radiography

NASA Astrophysics Data System (ADS)

Wang, Kai; Liu, Xinghui; Ou, Hai; Chen, Jun

2016-04-01

Amorphous silicon (a-Si:H) thin-film transistors (TFTs) have been widely used to build flat-panel X-ray detectors for digital radiography (DR). As the demand for low-dose X-ray imaging grows, a detector with high signal-to-noise-ratio (SNR) pixel architecture emerges. "Smart" pixel is intended to use a dual-gate photosensitive TFT for sensing, storage, and switch. It differs from a conventional passive pixel sensor (PPS) and active pixel sensor (APS) in that all these three functions are combined into one device instead of three separate units in a pixel. Thus, it is expected to have high fill factor and high spatial resolution. In addition, it utilizes the amplification effect of the dual-gate photosensitive TFT to form a one-transistor APS that leads to a potentially high SNR. This paper addresses the design, optimization and evaluation of the smart pixel sensor and array for low-dose DR. We will design and optimize the smart pixel from the scintillator to TFT levels and validate it through optical and electrical simulation and experiments of a 4x4 sensor array.

CognitionMaster: an object-based image analysis framework

PubMed Central

2013-01-01

Background Automated image analysis methods are becoming more and more important to extract and quantify image features in microscopy-based biomedical studies and several commercial or open-source tools are available. However, most of the approaches rely on pixel-wise operations, a concept that has limitations when high-level object features and relationships between objects are studied and if user-interactivity on the object-level is desired. Results In this paper we present an open-source software that facilitates the analysis of content features and object relationships by using objects as basic processing unit instead of individual pixels. Our approach enables also users without programming knowledge to compose “analysis pipelines“ that exploit the object-level approach. We demonstrate the design and use of example pipelines for the immunohistochemistry-based cell proliferation quantification in breast cancer and two-photon fluorescence microscopy data about bone-osteoclast interaction, which underline the advantages of the object-based concept. Conclusions We introduce an open source software system that offers object-based image analysis. The object-based concept allows for a straight-forward development of object-related interactive or fully automated image analysis solutions. The presented software may therefore serve as a basis for various applications in the field of digital image analysis. PMID:23445542

Geometric and Radiometric Evaluation of Rasat Images

NASA Astrophysics Data System (ADS)

Cam, Ali; Topan, Hüseyin; Oruç, Murat; Özendi, Mustafa; Bayık, Çağlar

2016-06-01

RASAT, the second remote sensing satellite of Turkey, was designed and assembled, and also is being operated by TÜBİTAK Uzay (Space) Technologies Research Institute (Ankara). RASAT images in various levels are available free-of-charge via Gezgin portal for Turkish citizens. In this paper, the images in panchromatic (7.5 m GSD) and RGB (15 m GSD) bands in various levels were investigated with respect to its geometric and radiometric characteristics. The first geometric analysis is the estimation of the effective GSD as less than 1 pixel for radiometrically processed level (L1R) of both panchromatic and RGB images. Secondly, 2D georeferencing accuracy is estimated by various non-physical transformation models (similarity, 2D affine, polynomial, affine projection, projective, DLT and GCP based RFM) reaching sub-pixel accuracy using minimum 39 and maximum 52 GCPs. The radiometric characteristics are also investigated for 8 bits, estimating SNR between 21.8-42.2, and noise 0.0-3.5 for panchromatic and MS images for L1R when the sea is masked to obtain the results for land areas. The analysis show that RASAT images satisfies requirements for various applications. The research is carried out in Zonguldak test site which is mountainous and partly covered by dense forest and urban areas.

Compressed sensing with cyclic-S Hadamard matrix for terahertz imaging applications

NASA Astrophysics Data System (ADS)

Ermeydan, Esra Şengün; ćankaya, Ilyas

2018-01-01

Compressed Sensing (CS) with Cyclic-S Hadamard matrix is proposed for single pixel imaging applications in this study. In single pixel imaging scheme, N = r . c samples should be taken for r×c pixel image where . denotes multiplication. CS is a popular technique claiming that the sparse signals can be reconstructed with samples under Nyquist rate. Therefore to solve the slow data acquisition problem in Terahertz (THz) single pixel imaging, CS is a good candidate. However, changing mask for each measurement is a challenging problem since there is no commercial Spatial Light Modulators (SLM) for THz band yet, therefore circular masks are suggested so that for each measurement one or two column shifting will be enough to change the mask. The CS masks are designed using cyclic-S matrices based on Hadamard transform for 9 × 7 and 15 × 17 pixel images within the framework of this study. The %50 compressed images are reconstructed using total variation based TVAL3 algorithm. Matlab simulations demonstrates that cyclic-S matrices can be used for single pixel imaging based on CS. The circular masks have the advantage to reduce the mechanical SLMs to a single sliding strip, whereas the CS helps to reduce acquisition time and energy since it allows to reconstruct the image from fewer samples.

Roughness effects on thermal-infrared emissivities estimated from remotely sensed images

NASA Astrophysics Data System (ADS)

Mushkin, Amit; Danilina, Iryna; Gillespie, Alan R.; Balick, Lee K.; McCabe, Matthew F.

2007-10-01

Multispectral thermal-infrared images from the Mauna Loa caldera in Hawaii, USA are examined to study the effects of surface roughness on remotely retrieved emissivities. We find up to a 3% decrease in spectral contrast in ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) 90-m/pixel emissivities due to sub-pixel surface roughness variations on the caldera floor. A similar decrease in spectral contrast of emissivities extracted from MASTER (MODIS/ASTER Airborne Simulator) ~12.5-m/pixel data can be described as a function of increasing surface roughness, which was measured remotely from ASTER 15-m/pixel stereo images. The ratio between ASTER stereo images provides a measure of sub-pixel surface-roughness variations across the scene. These independent roughness estimates complement a radiosity model designed to quantify the unresolved effects of multiple scattering and differential solar heating due to sub-pixel roughness elements and to compensate for both sub-pixel temperature dispersion and cavity radiation on TIR measurements.

Toward real-time quantum imaging with a single pixel camera

DOE PAGES

Lawrie, B. J.; Pooser, R. C.

2013-03-19

In this paper, we present a workbench for the study of real-time quantum imaging by measuring the frame-by-frame quantum noise reduction of multi-spatial-mode twin beams generated by four wave mixing in Rb vapor. Exploiting the multiple spatial modes of this squeezed light source, we utilize spatial light modulators to selectively pass macropixels of quantum correlated modes from each of the twin beams to a high quantum efficiency balanced detector. Finally, in low-light-level imaging applications, the ability to measure the quantum correlations between individual spatial modes and macropixels of spatial modes with a single pixel camera will facilitate compressive quantum imagingmore » with sensitivity below the photon shot noise limit.« less

A hyperspectral image optimizing method based on sub-pixel MTF analysis

NASA Astrophysics Data System (ADS)

Wang, Yun; Li, Kai; Wang, Jinqiang; Zhu, Yajie

2015-04-01

Hyperspectral imaging is used to collect tens or hundreds of images continuously divided across electromagnetic spectrum so that the details under different wavelengths could be represented. A popular hyperspectral imaging methods uses a tunable optical band-pass filter settled in front of the focal plane to acquire images of different wavelengths. In order to alleviate the influence of chromatic aberration in some segments in a hyperspectral series, in this paper, a hyperspectral optimizing method uses sub-pixel MTF to evaluate image blurring quality was provided. This method acquired the edge feature in the target window by means of the line spread function (LSF) to calculate the reliable position of the edge feature, then the evaluation grid in each line was interpolated by the real pixel value based on its relative position to the optimal edge and the sub-pixel MTF was used to analyze the image in frequency domain, by which MTF calculation dimension was increased. The sub-pixel MTF evaluation was reliable, since no image rotation and pixel value estimation was needed, and no artificial information was introduced. With theoretical analysis, the method proposed in this paper is reliable and efficient when evaluation the common images with edges of small tilt angle in real scene. It also provided a direction for the following hyperspectral image blurring evaluation and the real-time focal plane adjustment in real time in related imaging system.

Improving the scalability of hyperspectral imaging applications on heterogeneous platforms using adaptive run-time data compression

NASA Astrophysics Data System (ADS)

Plaza, Antonio; Plaza, Javier; Paz, Abel

2010-10-01

Latest generation remote sensing instruments (called hyperspectral imagers) are now able to generate hundreds of images, corresponding to different wavelength channels, for the same area on the surface of the Earth. In previous work, we have reported that the scalability of parallel processing algorithms dealing with these high-dimensional data volumes is affected by the amount of data to be exchanged through the communication network of the system. However, large messages are common in hyperspectral imaging applications since processing algorithms are pixel-based, and each pixel vector to be exchanged through the communication network is made up of hundreds of spectral values. Thus, decreasing the amount of data to be exchanged could improve the scalability and parallel performance. In this paper, we propose a new framework based on intelligent utilization of wavelet-based data compression techniques for improving the scalability of a standard hyperspectral image processing chain on heterogeneous networks of workstations. This type of parallel platform is quickly becoming a standard in hyperspectral image processing due to the distributed nature of collected hyperspectral data as well as its flexibility and low cost. Our experimental results indicate that adaptive lossy compression can lead to improvements in the scalability of the hyperspectral processing chain without sacrificing analysis accuracy, even at sub-pixel precision levels.

Automated Detection of Synapses in Serial Section Transmission Electron Microscopy Image Stacks

PubMed Central

Kreshuk, Anna; Koethe, Ullrich; Pax, Elizabeth; Bock, Davi D.; Hamprecht, Fred A.

2014-01-01

We describe a method for fully automated detection of chemical synapses in serial electron microscopy images with highly anisotropic axial and lateral resolution, such as images taken on transmission electron microscopes. Our pipeline starts from classification of the pixels based on 3D pixel features, which is followed by segmentation with an Ising model MRF and another classification step, based on object-level features. Classifiers are learned on sparse user labels; a fully annotated data subvolume is not required for training. The algorithm was validated on a set of 238 synapses in 20 serial 7197×7351 pixel images (4.5×4.5×45 nm resolution) of mouse visual cortex, manually labeled by three independent human annotators and additionally re-verified by an expert neuroscientist. The error rate of the algorithm (12% false negative, 7% false positive detections) is better than state-of-the-art, even though, unlike the state-of-the-art method, our algorithm does not require a prior segmentation of the image volume into cells. The software is based on the ilastik learning and segmentation toolkit and the vigra image processing library and is freely available on our website, along with the test data and gold standard annotations (http://www.ilastik.org/synapse-detection/sstem). PMID:24516550

Cerebral vessels segmentation for light-sheet microscopy image using convolutional neural networks

NASA Astrophysics Data System (ADS)

Hu, Chaoen; Hui, Hui; Wang, Shuo; Dong, Di; Liu, Xia; Yang, Xin; Tian, Jie

2017-03-01

Cerebral vessel segmentation is an important step in image analysis for brain function and brain disease studies. To extract all the cerebrovascular patterns, including arteries and capillaries, some filter-based methods are used to segment vessels. However, the design of accurate and robust vessel segmentation algorithms is still challenging, due to the variety and complexity of images, especially in cerebral blood vessel segmentation. In this work, we addressed a problem of automatic and robust segmentation of cerebral micro-vessels structures in cerebrovascular images acquired by light-sheet microscope for mouse. To segment micro-vessels in large-scale image data, we proposed a convolutional neural networks (CNNs) architecture trained by 1.58 million pixels with manual label. Three convolutional layers and one fully connected layer were used in the CNNs model. We extracted a patch of size 32x32 pixels in each acquired brain vessel image as training data set to feed into CNNs for classification. This network was trained to output the probability that the center pixel of input patch belongs to vessel structures. To build the CNNs architecture, a series of mouse brain vascular images acquired from a commercial light sheet fluorescence microscopy (LSFM) system were used for training the model. The experimental results demonstrated that our approach is a promising method for effectively segmenting micro-vessels structures in cerebrovascular images with vessel-dense, nonuniform gray-level and long-scale contrast regions.

In-flight calibration of the Hitomi Soft X-ray Spectrometer. (2) Point spread function

NASA Astrophysics Data System (ADS)

Maeda, Yoshitomo; Sato, Toshiki; Hayashi, Takayuki; Iizuka, Ryo; Angelini, Lorella; Asai, Ryota; Furuzawa, Akihiro; Kelley, Richard; Koyama, Shu; Kurashima, Sho; Ishida, Manabu; Mori, Hideyuki; Nakaniwa, Nozomi; Okajima, Takashi; Serlemitsos, Peter J.; Tsujimoto, Masahiro; Yaqoob, Tahir

2018-03-01

We present results of inflight calibration of the point spread function of the Soft X-ray Telescope that focuses X-rays onto the pixel array of the Soft X-ray Spectrometer system. We make a full array image of a point-like source by extracting a pulsed component of the Crab nebula emission. Within the limited statistics afforded by an exposure time of only 6.9 ks and limited knowledge of the systematic uncertainties, we find that the raytracing model of 1 {^'.} 2 half-power-diameter is consistent with an image of the observed event distributions across pixels. The ratio between the Crab pulsar image and the raytracing shows scatter from pixel to pixel that is 40% or less in all except one pixel. The pixel-to-pixel ratio has a spread of 20%, on average, for the 15 edge pixels, with an averaged statistical error of 17% (1 σ). In the central 16 pixels, the corresponding ratio is 15% with an error of 6%.

A pilot quantitative study of topographic correlation between reticular pseudodrusen and the choroidal vasculature using en face optical coherence tomography.

PubMed

Grewal, Dilraj S; Chou, Jonathan; Rollins, Stuart D; Fawzi, Amani A

2014-01-01

To analyze the topographic correlation between reticular pseudodrusen (RPD) visualized on infrared reflectance (IR) and choroidal vasculature using en-face volumetric spectral-domain optical coherence tomography (SD-OCT). A masked observer marked individual RPD on IR images using ImageJ (NIH, Bethesda, MD). Using the macular volume scan (Cirrus, Carl Zeiss Meditec Inc, Dublin, CA), the RPE slab function was used to generate a C-scan of the most superficial choroidal vasculature. An independent masked grader created a topographic binary map of the choroidal vasculature by thresholding the en-face image, which was overlaid onto the IR map of RPD. For each IR image, ImageJ was used to generate a random set of dots as "control lesions". 17 eyes of 11 patients (78±13.7 years) with RPD were analyzed. The average number of RPD lesions identified on IR images was 414±71.5, of which 49.6±4.3% were located overlying the choroidal vasculature, compared to 45.4±4.0% in controls (p = 0.014). 50.4±4.3% of lesions overlay the choroidal stroma, of which 76.5±3.1% were ≤3 pixels from the choroidal vessels. The percentage of RPD lesions located within ≤3 pixels from the choroidal vasculature was significantly greater than the percentage located ≥7 pixels away. (p<0.0001). Compared to controls (71.6±3.8%), RPD were more likely to be located ≤3 pixels away from choroidal vessels (p = 0.014). In contrast, control lesions were more likely to be ≥7 pixels away from choroidal vessels than RPD (9.1±1.9% vs. 4.8±1.2%, respectively, p = 0.002). Our analysis shows that RPD lesions follow the underlying choroidal vasculature. Approximately half the RPD directly overlay the choroidal vessels and the majority of the remaining lesions were ≤3 pixels (≤30 microns) from the vessel edge, supporting the hypothesis that RPD maybe related to pathologic changes at the choroidal level.

Comparison of 32 x 128 and 32 x 32 Geiger-mode APD FPAs for single photon 3D LADAR imaging

NASA Astrophysics Data System (ADS)

Itzler, Mark A.; Entwistle, Mark; Owens, Mark; Patel, Ketan; Jiang, Xudong; Slomkowski, Krystyna; Rangwala, Sabbir; Zalud, Peter F.; Senko, Tom; Tower, John; Ferraro, Joseph

2011-05-01

We present results obtained from 3D imaging focal plane arrays (FPAs) employing planar-geometry InGaAsP/InP Geiger-mode avalanche photodiodes (GmAPDs) with high-efficiency single photon sensitivity at 1.06 μm. We report results obtained for new 32 x 128 format FPAs with 50 μm pitch and compare these results to those obtained for 32 x 32 format FPAs with 100 μm pitch. We show excellent pixel-level yield-including 100% pixel operability-for both formats. The dark count rate (DCR) and photon detection efficiency (PDE) performance is found to be similar for both types of arrays, including the fundamental DCR vs. PDE tradeoff. The optical crosstalk due to photon emission induced by pixel-level avalanche detection events is found to be qualitatively similar for both formats, with some crosstalk metrics for the 32 x 128 format found to be moderately elevated relative to the 32 x 32 FPA results. Timing jitter measurements are also reported for the 32 x 128 FPAs.

Digital mammography: observer performance study of the effects of pixel size on radiologists' characterization of malignant and benign microcalcifications

NASA Astrophysics Data System (ADS)

Chan, Heang-Ping; Helvie, Mark A.; Petrick, Nicholas; Sahiner, Berkman; Adler, Dorit D.; Blane, Caroline E.; Joynt, Lynn K.; Paramagul, Chintana; Roubidoux, Marilyn A.; Wilson, Todd E.; Hadjiiski, Lubomir M.; Goodsitt, Mitchell M.

1999-05-01

A receiver operating characteristic (ROC) experiment was conducted to evaluate the effects of pixel size on the characterization of mammographic microcalcifications. Digital mammograms were obtained by digitizing screen-film mammograms with a laser film scanner. One hundred twelve two-view mammograms with biopsy-proven microcalcifications were digitized at a pixel size of 35 micrometer X 35 micrometer. A region of interest (ROI) containing the microcalcifications was extracted from each image. ROI images with pixel sizes of 70 micrometers, 105 micrometers, and 140 micrometers were derived from the ROI of 35 micrometer pixel size by averaging 2 X 2, 3 X 3, and 4 X 4 neighboring pixels, respectively. The ROI images were printed on film with a laser imager. Seven MQSA-approved radiologists participated as observers. The likelihood of malignancy of the microcalcifications was rated on a 10-point confidence rating scale and analyzed with ROC methodology. The classification accuracy was quantified by the area, Az, under the ROC curve. The statistical significance of the differences in the Az values for different pixel sizes was estimated with the Dorfman-Berbaum-Metz (DBM) method for multi-reader, multi-case ROC data. It was found that five of the seven radiologists demonstrated a higher classification accuracy with the 70 micrometer or 105 micrometer images. The average Az also showed a higher classification accuracy in the range of 70 to 105 micrometer pixel size. However, the differences in A(subscript z/ between different pixel sizes did not achieve statistical significance. The low specificity of image features of microcalcifications an the large interobserver and intraobserver variabilities may have contributed to the relatively weak dependence of classification accuracy on pixel size.

Near-infrared hyperspectral imaging for detecting Aflatoxin B1 of maize kernels

USDA-ARS?s Scientific Manuscript database

The feasibility of detecting the Aflatoxin B1 in maize kernels inoculated with Aspergillus flavus conidia in the field was assessed using near-infrared hyperspectral imaging technique. After pixel-level calibration, wavelength dependent offset, the masking method was adopted to reduce the noise and ...

Daylight characterization through vision-based sensing of lighting conditions in buildings

NASA Astrophysics Data System (ADS)

di Dio, Joseph, III

A new method for describing daylight under unknown weather conditions, as captured in images of a room, is proposed. This method considers pixel brightness information to be a linear combination of diffuse and directional light components, as received by a web cam from the walls and ceiling of an occupied office. The nature of these components in each image is determined by building orientation, room geometry, neighboring structures and the position of the sun. Considering daylight in this manner also allows for an estimation of the sky conditions at a given instant to be made, and presents a means to uncover seasonal trends in the behavior of light simply by monitoring the brightness variations of points on the walls and ceiling. Significantly, this daylight characterization method also allows for an estimation of the illumination level on a target surface to be made from image data. Currently, illumination at a target surface is estimated through the use of a ceiling-mounted photosensor, as part of a lighting control system, in the hopes of achieving a suitable balance between daylight and electrical lighting in a space. Improving the ability of a sensor to estimate the illumination is of great importance to those who wish to minimize unnecessary energy consumption, as a significant percentage of all U.S. electricity is currently consumed by light fixtures. A photosensor detects light that falls on its location, which does not necessarily correspond in a fixed manner to the light level on the target areas that the photosensor is meant to monitor. Additionally, a photosensor cannot discern variations in light distribution across a room, which often occur with daylight. By considering pixel brightness information to be a linear combination of diffuse and directional light components at selected pixels in an image, information about the light reaching these pixels can be extracted from observed patterns of brightness, under different light conditions. In this manner, each pixel provides information about the light field at its corresponding point in the room, and thus each pixel can be considered to behave as if it were a remote photosensor. By using multiple pixel readings in lieu of a single photosensor reading of a given light condition, an improved assessment of the illumination level on a target surface can been achieved. It is shown that on average, the camera-based method was approximately 25% more accurate in estimating illuminance in the test room than was a simulated ceiling-mounted photosensor. It is hoped that the methodology detailed here will aid in the eventual development of a camera-based daylight characterization sensor for use in lighting control systems, so that the potential for enhanced energy savings can be realized.

Some new classification methods for hyperspectral remote sensing

NASA Astrophysics Data System (ADS)

Du, Pei-jun; Chen, Yun-hao; Jones, Simon; Ferwerda, Jelle G.; Chen, Zhi-jun; Zhang, Hua-peng; Tan, Kun; Yin, Zuo-xia

2006-10-01

Hyperspectral Remote Sensing (HRS) is one of the most significant recent achievements of Earth Observation Technology. Classification is the most commonly employed processing methodology. In this paper three new hyperspectral RS image classification methods are analyzed. These methods are: Object-oriented FIRS image classification, HRS image classification based on information fusion and HSRS image classification by Back Propagation Neural Network (BPNN). OMIS FIRS image is used as the example data. Object-oriented techniques have gained popularity for RS image classification in recent years. In such method, image segmentation is used to extract the regions from the pixel information based on homogeneity criteria at first, and spectral parameters like mean vector, texture, NDVI and spatial/shape parameters like aspect ratio, convexity, solidity, roundness and orientation for each region are calculated, finally classification of the image using the region feature vectors and also using suitable classifiers such as artificial neural network (ANN). It proves that object-oriented methods can improve classification accuracy since they utilize information and features both from the point and the neighborhood, and the processing unit is a polygon (in which all pixels are homogeneous and belong to the class). HRS image classification based on information fusion, divides all bands of the image into different groups initially, and extracts features from every group according to the properties of each group. Three levels of information fusion: data level fusion, feature level fusion and decision level fusion are used to HRS image classification. Artificial Neural Network (ANN) can perform well in RS image classification. In order to promote the advances of ANN used for HIRS image classification, Back Propagation Neural Network (BPNN), the most commonly used neural network, is used to HRS image classification.

Rolling Band Artifact Flagging in the Kepler Data Pipeline

NASA Astrophysics Data System (ADS)

Clarke, Bruce; Kolodziejczak, Jeffery J; Caldwell, Douglas A.

2014-06-01

Instrument-induced artifacts in the raw Kepler pixel data include time-varying crosstalk from the fine guidance sensor (FGS) clock signals, manifestations of drifting moiré pattern as locally correlated nonstationary noise and rolling bands in the images. These systematics find their way into the calibrated pixel time series and ultimately into the target flux time series. The Kepler pipeline module Dynablack models the FGS crosstalk artifacts using a combination of raw science pixel data, full frame images, reverse-clocked pixel data and ancillary temperature data. The calibration module (CAL) uses the fitted Dynablack models to remove FGS crosstalk artifacts in the calibrated pixels by adjusting the black level correction per cadence. Dynablack also detects and flags spatial regions and time intervals of strong time-varying black-level. These rolling band artifact (RBA) flags are produced on a per row per cadence basis by searching for transit signatures in the Dynablack fit residuals. The Photometric Analysis module (PA) generates per target per cadence data quality flags based on the Dynablack RBA flags. Proposed future work includes using the target data quality flags as a basis for de-weighting in the Presearch Data Conditioning (PDC), Transiting Planet Search (TPS) and Data Validation (DV) pipeline modules. We discuss the effectiveness of RBA flagging for downstream users and illustrate with some affected light curves. We also discuss the implementation of Dynablack in the Kepler data pipeline and present results regarding the improvement in calibrated pixels and the expected improvement in cotrending performance as a result of including FGS corrections in the calibration. Funding for the Kepler Mission has been provided by the NASA Science Mission Directorate.

Methods in quantitative image analysis.

PubMed

Oberholzer, M; Ostreicher, M; Christen, H; Brühlmann, M

1996-05-01

The main steps of image analysis are image capturing, image storage (compression), correcting imaging defects (e.g. non-uniform illumination, electronic-noise, glare effect), image enhancement, segmentation of objects in the image and image measurements. Digitisation is made by a camera. The most modern types include a frame-grabber, converting the analog-to-digital signal into digital (numerical) information. The numerical information consists of the grey values describing the brightness of every point within the image, named a pixel. The information is stored in bits. Eight bits are summarised in one byte. Therefore, grey values can have a value between 0 and 256 (2(8)). The human eye seems to be quite content with a display of 5-bit images (corresponding to 64 different grey values). In a digitised image, the pixel grey values can vary within regions that are uniform in the original scene: the image is noisy. The noise is mainly manifested in the background of the image. For an optimal discrimination between different objects or features in an image, uniformity of illumination in the whole image is required. These defects can be minimised by shading correction [subtraction of a background (white) image from the original image, pixel per pixel, or division of the original image by the background image]. The brightness of an image represented by its grey values can be analysed for every single pixel or for a group of pixels. The most frequently used pixel-based image descriptors are optical density, integrated optical density, the histogram of the grey values, mean grey value and entropy. The distribution of the grey values existing within an image is one of the most important characteristics of the image. However, the histogram gives no information about the texture of the image. The simplest way to improve the contrast of an image is to expand the brightness scale by spreading the histogram out to the full available range. Rules for transforming the grey value histogram of an existing image (input image) into a new grey value histogram (output image) are most quickly handled by a look-up table (LUT). The histogram of an image can be influenced by gain, offset and gamma of the camera. Gain defines the voltage range, offset defines the reference voltage and gamma the slope of the regression line between the light intensity and the voltage of the camera. A very important descriptor of neighbourhood relations in an image is the co-occurrence matrix. The distance between the pixels (original pixel and its neighbouring pixel) can influence the various parameters calculated from the co-occurrence matrix. The main goals of image enhancement are elimination of surface roughness in an image (smoothing), correction of defects (e.g. noise), extraction of edges, identification of points, strengthening texture elements and improving contrast. In enhancement, two types of operations can be distinguished: pixel-based (point operations) and neighbourhood-based (matrix operations). The most important pixel-based operations are linear stretching of grey values, application of pre-stored LUTs and histogram equalisation. The neighbourhood-based operations work with so-called filters. These are organising elements with an original or initial point in their centre. Filters can be used to accentuate or to suppress specific structures within the image. Filters can work either in the spatial or in the frequency domain. The method used for analysing alterations of grey value intensities in the frequency domain is the Hartley transform. Filter operations in the spatial domain can be based on averaging or ranking the grey values occurring in the organising element. The most important filters, which are usually applied, are the Gaussian filter and the Laplace filter (both averaging filters), and the median filter, the top hat filter and the range operator (all ranking filters). Segmentation of objects is traditionally based on threshold grey values. (AB

Single-pixel non-imaging object recognition by means of Fourier spectrum acquisition

NASA Astrophysics Data System (ADS)

Chen, Huichao; Shi, Jianhong; Liu, Xialin; Niu, Zhouzhou; Zeng, Guihua

2018-04-01

Single-pixel imaging has emerged over recent years as a novel imaging technique, which has significant application prospects. In this paper, we propose and experimentally demonstrate a scheme that can achieve single-pixel non-imaging object recognition by acquiring the Fourier spectrum. In an experiment, a four-step phase-shifting sinusoid illumination light is used to irradiate the object image, the value of the light intensity is measured with a single-pixel detection unit, and the Fourier coefficients of the object image are obtained by a differential measurement. The Fourier coefficients are first cast into binary numbers to obtain the hash value. We propose a new method of perceptual hashing algorithm, which is combined with a discrete Fourier transform to calculate the hash value. The hash distance is obtained by calculating the difference of the hash value between the object image and the contrast images. By setting an appropriate threshold, the object image can be quickly and accurately recognized. The proposed scheme realizes single-pixel non-imaging perceptual hashing object recognition by using fewer measurements. Our result might open a new path for realizing object recognition with non-imaging.

Carotid Stenosis And Ulcer Detectability As A Function Of Pixel Size

NASA Astrophysics Data System (ADS)

Mintz, Leslie J.; Enzmann, Dieter R.; Keyes, Gary S.; Mainiero, Louis M.; Brody, William R.

1981-11-01

Digital radiography, in conjunction with digital subtraction methods can provide high quality images of the vascular system,1-4 Spatial resolution is one important limiting factor of this imaging technique. Since spatial resolution of a digital image is a function of pixel size, it is important to determine the pixel size threshold necessary to provide information comparable to that of conventional angiograms. This study was designed to establish the pixel size necessary to identify accurately stenotic and ulcerative lesions of the carotid artery.

A novel multiphoton microscopy images segmentation method based on superpixel and watershed.

PubMed

Wu, Weilin; Lin, Jinyong; Wang, Shu; Li, Yan; Liu, Mingyu; Liu, Gaoqiang; Cai, Jianyong; Chen, Guannan; Chen, Rong

2017-04-01

Multiphoton microscopy (MPM) imaging technique based on two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) shows fantastic performance for biological imaging. The automatic segmentation of cellular architectural properties for biomedical diagnosis based on MPM images is still a challenging issue. A novel multiphoton microscopy images segmentation method based on superpixels and watershed (MSW) is presented here to provide good segmentation results for MPM images. The proposed method uses SLIC superpixels instead of pixels to analyze MPM images for the first time. The superpixels segmentation based on a new distance metric combined with spatial, CIE Lab color space and phase congruency features, divides the images into patches which keep the details of the cell boundaries. Then the superpixels are used to reconstruct new images by defining an average value of superpixels as image pixels intensity level. Finally, the marker-controlled watershed is utilized to segment the cell boundaries from the reconstructed images. Experimental results show that cellular boundaries can be extracted from MPM images by MSW with higher accuracy and robustness. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Angiogram, fundus, and oxygen saturation optic nerve head image fusion

NASA Astrophysics Data System (ADS)

Cao, Hua; Khoobehi, Bahram

2009-02-01

A novel multi-modality optic nerve head image fusion approach has been successfully designed. The new approach has been applied on three ophthalmologic modalities: angiogram, fundus, and oxygen saturation retinal optic nerve head images. It has achieved an excellent result by giving the visualization of fundus or oxygen saturation images with a complete angiogram overlay. During this study, two contributions have been made in terms of novelty, efficiency, and accuracy. The first contribution is the automated control point detection algorithm for multi-sensor images. The new method employs retina vasculature and bifurcation features by identifying the initial good-guess of control points using the Adaptive Exploratory Algorithm. The second contribution is the heuristic optimization fusion algorithm. In order to maximize the objective function (Mutual-Pixel-Count), the iteration algorithm adjusts the initial guess of the control points at the sub-pixel level. A refinement of the parameter set is obtained at the end of each loop, and finally an optimal fused image is generated at the end of the iteration. It is the first time that Mutual-Pixel-Count concept has been introduced into biomedical image fusion area. By locking the images in one place, the fused image allows ophthalmologists to match the same eye over time and get a sense of disease progress and pinpoint surgical tools. The new algorithm can be easily expanded to human or animals' 3D eye, brain, or body image registration and fusion.

Spectral imaging as a potential tool for optical sentinel lymph node biopsies

NASA Astrophysics Data System (ADS)

O'Sullivan, Jack D.; Hoy, Paul R.; Rutt, Harvey N.

2011-07-01

Sentinel Lymph Node Biopsy (SLNB) is an increasingly standard procedure to help oncologists accurately stage cancers. It is performed as an alternative to full axillary lymph node dissection in breast cancer patients, reducing the risk of longterm health problems associated with lymph node removal. Intraoperative analysis is currently performed using touchprint cytology, which can introduce significant delay into the procedure. Spectral imaging is forming a multi-plane image where reflected intensities from a number of spectral bands are recorded at each pixel in the spatial plane. We investigate the possibility of using spectral imaging to assess sentinel lymph nodes of breast cancer patients with a view to eventually developing an optical technique that could significantly reduce the time required to perform this procedure. We investigate previously reported spectra of normal and metastatic tissue in the visible and near infrared region, using them as the basis of dummy spectral images. We analyse these images using the spectral angle map (SAM), a tool routinely used in other fields where spectral imaging is prevalent. We simulate random noise in these images in order to determine whether the SAM can discriminate between normal and metastatic pixels as the quality of the images deteriorates. We show that even in cases where noise levels are up to 20% of the maximum signal, the spectral angle map can distinguish healthy pixels from metastatic. We believe that this makes spectral imaging a good candidate for further study in the development of an optical SLNB.

A Novel Color Image Encryption Algorithm Based on Quantum Chaos Sequence

NASA Astrophysics Data System (ADS)

Liu, Hui; Jin, Cong

2017-03-01

In this paper, a novel algorithm of image encryption based on quantum chaotic is proposed. The keystreams are generated by the two-dimensional logistic map as initial conditions and parameters. And then general Arnold scrambling algorithm with keys is exploited to permute the pixels of color components. In diffusion process, a novel encryption algorithm, folding algorithm, is proposed to modify the value of diffused pixels. In order to get the high randomness and complexity, the two-dimensional logistic map and quantum chaotic map are coupled with nearest-neighboring coupled-map lattices. Theoretical analyses and computer simulations confirm that the proposed algorithm has high level of security.

Time multiplexing for increased FOV and resolution in virtual reality

NASA Astrophysics Data System (ADS)

Miñano, Juan C.; Benitez, Pablo; Grabovičkić, Dejan; Zamora, Pablo; Buljan, Marina; Narasimhan, Bharathwaj

2017-06-01

We introduce a time multiplexing strategy to increase the total pixel count of the virtual image seen in a VR headset. This translates into an improvement of the pixel density or the Field of View FOV (or both) A given virtual image is displayed by generating a succession of partial real images, each representing part of the virtual image and together representing the virtual image. Each partial real image uses the full set of physical pixels available in the display. The partial real images are successively formed and combine spatially and temporally to form a virtual image viewable from the eye position. Partial real images are imaged through different optical channels depending of its time slot. Shutters or other schemes are used to avoid that a partial real image be imaged through the wrong optical channels or at the wrong time slot. This time multiplexing strategy needs real images be shown at high frame rates (>120fps). Available display and shutters technologies are discussed. Several optical designs for achieving this time multiplexing scheme in a compact format are shown. This time multiplexing scheme allows increasing the resolution/FOV of the virtual image not only by increasing the physical pixel density but also by decreasing the pixels switching time, a feature that may be simpler to achieve in certain circumstances.

Automatic Rooftop Extraction in Stereo Imagery Using Distance and Building Shape Regularized Level Set Evolution

NASA Astrophysics Data System (ADS)

Tian, J.; Krauß, T.; d'Angelo, P.

2017-05-01

Automatic rooftop extraction is one of the most challenging problems in remote sensing image analysis. Classical 2D image processing techniques are expensive due to the high amount of features required to locate buildings. This problem can be avoided when 3D information is available. In this paper, we show how to fuse the spectral and height information of stereo imagery to achieve an efficient and robust rooftop extraction. In the first step, the digital terrain model (DTM) and in turn the normalized digital surface model (nDSM) is generated by using a newly step-edge approach. In the second step, the initial building locations and rooftop boundaries are derived by removing the low-level pixels and high-level pixels with higher probability to be trees and shadows. This boundary is then served as the initial level set function, which is further refined to fit the best possible boundaries through distance regularized level-set curve evolution. During the fitting procedure, the edge-based active contour model is adopted and implemented by using the edges indicators extracted from panchromatic image. The performance of the proposed approach is tested by using the WorldView-2 satellite data captured over Munich.

Argentina from MODIS

NASA Technical Reports Server (NTRS)

2002-01-01

This Moderate-resolution Imaging Spectroradiometer (MODIS) image over Argentina was acquired on April 24, 2000, and was produced using a combination of the sensor's 250-m and 500-m resolution 'true color' bands. This image was presented on June 13, 2000 as a GIFt to Argentinian President Fernando de la Rua by NASA Administrator Dan Goldin. Note the Parana River which runs due south from the top of the image before turning east to empty into the Atlantic Ocean. Note the yellowish sediment from the Parana River mixing with the redish sediment from the Uruguay River as it empties into the Rio de la Plata. The water level of the Parana seems high, which could explain the high sediment discharge. A variety of land surface features are visible in this image. To the north, the greenish pixels show forest regions, as well as characteristic clusters of rectangular patterns of agricultural fields. In the lower left of the image, the lighter green pixels show arable regions where there is grazing and farming. (Image courtesy Jacques Descloitres, MODIS Land Group, NASA GSFC)

14C autoradiography with an energy-sensitive silicon pixel detector.

PubMed

Esposito, M; Mettivier, G; Russo, P

2011-04-07

The first performance tests are presented of a carbon-14 ((14)C) beta-particle digital autoradiography system with an energy-sensitive hybrid silicon pixel detector based on the Timepix readout circuit. Timepix was developed by the Medipix2 Collaboration and it is similar to the photon-counting Medipix2 circuit, except for an added time-based synchronization logic which allows derivation of energy information from the time-over-threshold signal. This feature permits direct energy measurements in each pixel of the detector array. Timepix is bump-bonded to a 300 µm thick silicon detector with 256 × 256 pixels of 55 µm pitch. Since an energetic beta-particle could release its kinetic energy in more than one detector pixel as it slows down in the semiconductor detector, an off-line image analysis procedure was adopted in which the single-particle cluster of hit pixels is recognized; its total energy is calculated and the position of interaction on the detector surface is attributed to the centre of the charge cluster. Measurements reported are detector sensitivity, (4.11 ± 0.03) × 10(-3) cps mm(-2) kBq(-1) g, background level, (3.59 ± 0.01) × 10(-5) cps mm(-2), and minimum detectable activity, 0.0077 Bq. The spatial resolution is 76.9 µm full-width at half-maximum. These figures are compared with several digital imaging detectors for (14)C beta-particle digital autoradiography.

Probabilistic multi-resolution human classification

NASA Astrophysics Data System (ADS)

Tu, Jun; Ran, H.

2006-02-01

Recently there has been some interest in using infrared cameras for human detection because of the sharply decreasing prices of infrared cameras. The training data used in our work for developing the probabilistic template consists images known to contain humans in different poses and orientation but having the same height. Multiresolution templates are performed. They are based on contour and edges. This is done so that the model does not learn the intensity variations among the background pixels and intensity variations among the foreground pixels. Each template at every level is then translated so that the centroid of the non-zero pixels matches the geometrical center of the image. After this normalization step, for each pixel of the template, the probability of it being pedestrian is calculated based on the how frequently it appears as 1 in the training data. We also use periodicity gait to verify the pedestrian in a Bayesian manner for the whole blob in a probabilistic way. The videos had quite a lot of variations in the scenes, sizes of people, amount of occlusions and clutter in the backgrounds as is clearly evident. Preliminary experiments show the robustness.

Distance-based over-segmentation for single-frame RGB-D images

NASA Astrophysics Data System (ADS)

Fang, Zhuoqun; Wu, Chengdong; Chen, Dongyue; Jia, Tong; Yu, Xiaosheng; Zhang, Shihong; Qi, Erzhao

2017-11-01

Over-segmentation, known as super-pixels, is a widely used preprocessing step in segmentation algorithms. Oversegmentation algorithm segments an image into regions of perceptually similar pixels, but performs badly based on only color image in the indoor environments. Fortunately, RGB-D images can improve the performances on the images of indoor scene. In order to segment RGB-D images into super-pixels effectively, we propose a novel algorithm, DBOS (Distance-Based Over-Segmentation), which realizes full coverage of super-pixels on the image. DBOS fills the holes in depth images to fully utilize the depth information, and applies SLIC-like frameworks for fast running. Additionally, depth features such as plane projection distance are extracted to compute distance which is the core of SLIC-like frameworks. Experiments on RGB-D images of NYU Depth V2 dataset demonstrate that DBOS outperforms state-ofthe-art methods in quality while maintaining speeds comparable to them.

Heterogeneity of Particle Deposition by Pixel Analysis of 2D Gamma Scintigraphy Images

PubMed Central

Xie, Miao; Zeman, Kirby; Hurd, Harry; Donaldson, Scott

2015-01-01

Abstract Background: Heterogeneity of inhaled particle deposition in airways disease may be a sensitive indicator of physiologic changes in the lungs. Using planar gamma scintigraphy, we developed new methods to locate and quantify regions of high (hot) and low (cold) particle deposition in the lungs. Methods: Initial deposition and 24 hour retention images were obtained from healthy (n=31) adult subjects and patients with mild cystic fibrosis lung disease (CF) (n=14) following inhalation of radiolabeled particles (Tc99m-sulfur colloid, 5.4 μm MMAD) under controlled breathing conditions. The initial deposition image of the right lung was normalized to (i.e., same median pixel value), and then divided by, a transmission (Tc99m) image in the same individual to obtain a pixel-by-pixel ratio image. Hot spots were defined where pixel values in the deposition image were greater than 2X those of the transmission, and cold spots as pixels where the deposition image was less than 0.5X of the transmission. The number ratio (NR) of the hot and cold pixels to total lung pixels, and the sum ratio (SR) of total counts in hot pixels to total lung counts were compared between healthy and CF subjects. Other traditional measures of regional particle deposition, nC/P and skew of the pixel count histogram distribution, were also compared. Results: The NR of cold spots was greater in mild CF, 0.221±0.047(CF) vs. 0.186±0.038 (healthy) (p<0.005) and was significantly correlated with FEV1 %pred in the patients (R=−0.70). nC/P (central to peripheral count ratio), skew of the count histogram, and hot NR or SR were not different between the healthy and mild CF patients. Conclusions: These methods may provide more sensitive measures of airway function and localization of deposition that might be useful for assessing treatment efficacy in these patients. PMID:25393109

Layer by layer: complex analysis with OCT technology

NASA Astrophysics Data System (ADS)

Florin, Christian

2017-03-01

Standard visualisation systems capture two- dimensional images and need more or less fast image processing systems. Now, the ASP Array (Actives sensor pixel array) opens a new world in imaging. On the ASP array, each pixel is provided with its own lens and with its own signal pre-processing. The OCT technology works in "real time" with highest accuracy. In the ASP array systems functionalities of the data acquisition and signal processing are even integrated onto the "pixel level". For the extraction of interferometric features, the time-of-flight principle (TOF) is used. The ASP architecture offers the demodulation of the optical signal within a pixel with up to 100 kHz and the reconstruction of the amplitude and its phase. The dynamics of image capture with the ASP array is higher by two orders of magnitude in comparison with conventional image sensors!!! The OCT- Technology allows a topographic imaging in real time with an extremely high geometric spatial resolution. The optical path length is generated by an axial movement of the reference mirror. The amplitude-modulated optical signal and the carrier frequency are proportional to the scan rate and contains the depth information. Each maximum of the signal envelope corresponds to a reflection (or scattering) within a sample. The ASP array produces at same time 300 * 300 axial Interferorgrams which touch each other on all sides. The signal demodulation for detecting the envelope is not limited by the frame rate of the ASP array in comparison to standard OCT systems. If an optical signal arrives to a pixel of the ASP Array an electrical signal is generated. The background is faded to saturation of pixels by high light intensity to avoid. The sampled signal is integrated continuously multiplied by a signal of the same frequency and two paths whose phase is shifted by 90 degrees from each other are averaged. The outputs of the two paths are routed to the PC, where the envelope amplitude and the phase calculate a three-dimensional tomographic image. For 3D measuring technique specially designed ASP- arrays with a very high image rate are available. If ASP- Arrays are coupled with the OCT method, layer thicknesses can be determined without contact, sealing seams can be inspected or geometrical shapes can be measured. From a stack of hundreds of single OCT images, interesting images can be selected and fed to the computer to analyse them.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mateos, M-J; Brandan, M-E; Gastelum, A

Purpose: To evaluate the time evolution of texture parameters, based on the gray level co-occurrence matrix (GLCM), in subtracted images of 17 patients (10 malignant and 7 benign) subjected to contrast-enhanced digital mammography (CEDM). The goal is to determine the sensitivity of texture to iodine uptake at the lesion, and its correlation (or lack of) with mean-pixel-value (MPV). Methods: Acquisition of clinical images followed a single-energy CEDM protocol using Rh/Rh/48 kV plus external 0.5 cm Al from a Senographe DS unit. Prior to the iodine-based contrast medium (CM) administration a mask image was acquired; four CM images were obtained 1,more » 2, 3, and 5 minutes after CM injection. Temporal series were obtained by logarithmic subtraction of registered CM minus mask images.Regions of interest (ROI) for the lesion were drawn by a radiologist and the texture was analyzed. GLCM was evaluated at a 3 pixel distance, 0° angle, and 64 gray-levels. Pixels identified as registration errors were excluded from the computation. 17 texture parameters were chosen, classified according to similarity into 7 groups, and analyzed. Results: In all cases the texture parameters within a group have similar dynamic behavior. Two texture groups (associated to cluster and sum mean) show a strong correlation with MPV; their average correlation coefficient (ACC) is r{sup 2}=0.90. Other two groups (contrast, homogeneity) remain constant with time, that is, a low-sensitivity to CM uptake. Three groups (regularity, lacunarity and diagonal moment) are sensitive to CM uptake but less correlated with MPV; their ACC is r{sup 2}=0.78. Conclusion: This analysis has shown that, at least groups associated to regularity, lacunarity and diagonal moment offer dynamical information additional to the mean pixel value due to the presence of CM at the lesion. The next step will be the analysis in terms of the lesion pathology. Authors thank PAPIIT-IN105813 for support. Consejo Nacional de Ciencia Y Tecnologia, PAPIIT-IN105813.« less

KENIS: a high-performance thermal imager developed using the OSPREY IR detector

NASA Astrophysics Data System (ADS)

Goss, Tristan M.; Baker, Ian M.

2000-07-01

`KENIS', a complete, high performance, compact and lightweight thermal imager, is built around the `OSPREY' infrared detector from BAE systems Infrared Ltd. The `OSPREY' detector uses a 384 X 288 element CMT array with a 20 micrometers pixel size and cooled to 120 K. The relatively small pixel size results in very compact cryogenics and optics, and the relatively high operating temperature provides fast start-up time, low power consumption and long operating life. Requiring single input supply voltage and consuming less than 30 watts of power, the thermal imager generates both analogue and digital format outputs. The `KENIS' lens assembly features a near diffraction limited dual field-of-view optical system that has been designed to be athermalized and switches between fields in less than one second. The `OSPREY' detector produces near background limited performance with few defects and has special, pixel level circuitry to eliminate crosstalk and blooming effects. This, together with signal processing based on an effective two-point fixed pattern noise correction algorithm, results in high quality imagery and a thermal imager that is suitable for most traditional thermal imaging applications. This paper describes the rationale used in the development of the `KENIS' thermal imager, and highlights the potential performance benefits to the user's system, primarily gained by selecting the `OSPREY' infra-red detector within the core of the thermal imager.

CMOS Image Sensors for High Speed Applications.

PubMed

El-Desouki, Munir; Deen, M Jamal; Fang, Qiyin; Liu, Louis; Tse, Frances; Armstrong, David

2009-01-01

Recent advances in deep submicron CMOS technologies and improved pixel designs have enabled CMOS-based imagers to surpass charge-coupled devices (CCD) imaging technology for mainstream applications. The parallel outputs that CMOS imagers can offer, in addition to complete camera-on-a-chip solutions due to being fabricated in standard CMOS technologies, result in compelling advantages in speed and system throughput. Since there is a practical limit on the minimum pixel size (4∼5 μm) due to limitations in the optics, CMOS technology scaling can allow for an increased number of transistors to be integrated into the pixel to improve both detection and signal processing. Such smart pixels truly show the potential of CMOS technology for imaging applications allowing CMOS imagers to achieve the image quality and global shuttering performance necessary to meet the demands of ultrahigh-speed applications. In this paper, a review of CMOS-based high-speed imager design is presented and the various implementations that target ultrahigh-speed imaging are described. This work also discusses the design, layout and simulation results of an ultrahigh acquisition rate CMOS active-pixel sensor imager that can take 8 frames at a rate of more than a billion frames per second (fps).

Identification of coffee bean varieties using hyperspectral imaging: influence of preprocessing methods and pixel-wise spectra analysis.

PubMed

Zhang, Chu; Liu, Fei; He, Yong

2018-02-01

Hyperspectral imaging was used to identify and to visualize the coffee bean varieties. Spectral preprocessing of pixel-wise spectra was conducted by different methods, including moving average smoothing (MA), wavelet transform (WT) and empirical mode decomposition (EMD). Meanwhile, spatial preprocessing of the gray-scale image at each wavelength was conducted by median filter (MF). Support vector machine (SVM) models using full sample average spectra and pixel-wise spectra, and the selected optimal wavelengths by second derivative spectra all achieved classification accuracy over 80%. Primarily, the SVM models using pixel-wise spectra were used to predict the sample average spectra, and these models obtained over 80% of the classification accuracy. Secondly, the SVM models using sample average spectra were used to predict pixel-wise spectra, but achieved with lower than 50% of classification accuracy. The results indicated that WT and EMD were suitable for pixel-wise spectra preprocessing. The use of pixel-wise spectra could extend the calibration set, and resulted in the good prediction results for pixel-wise spectra and sample average spectra. The overall results indicated the effectiveness of using spectral preprocessing and the adoption of pixel-wise spectra. The results provided an alternative way of data processing for applications of hyperspectral imaging in food industry.

X-ray analog pixel array detector for single synchrotron bunch time-resolved imaging.

PubMed

Koerner, Lucas J; Gruner, Sol M

2011-03-01

Dynamic X-ray studies can reach temporal resolutions limited by only the X-ray pulse duration if the detector is fast enough to segregate synchrotron pulses. An analog integrating pixel array detector with in-pixel storage and temporal resolution of around 150 ns, sufficient to isolate pulses, is presented. Analog integration minimizes count-rate limitations and in-pixel storage captures successive pulses. Fundamental tests of noise and linearity as well as high-speed laser measurements are shown. The detector resolved individual bunch trains at the Cornell High Energy Synchrotron Source at levels of up to 3.7 × 10(3) X-rays per pixel per train. When applied to turn-by-turn X-ray beam characterization, single-shot intensity measurements were made with a repeatability of 0.4% and horizontal oscillations of the positron cloud were detected.

X-ray analog pixel array detector for single synchrotron bunch time-resolved imaging

PubMed Central

Koerner, Lucas J.; Gruner, Sol M.

2011-01-01

Dynamic X-ray studies can reach temporal resolutions limited by only the X-ray pulse duration if the detector is fast enough to segregate synchrotron pulses. An analog integrating pixel array detector with in-pixel storage and temporal resolution of around 150 ns, sufficient to isolate pulses, is presented. Analog integration minimizes count-rate limitations and in-pixel storage captures successive pulses. Fundamental tests of noise and linearity as well as high-speed laser measurements are shown. The detector resolved individual bunch trains at the Cornell High Energy Synchrotron Source at levels of up to 3.7 × 103 X-rays per pixel per train. When applied to turn-by-turn X-ray beam characterization, single-shot intensity measurements were made with a repeatability of 0.4% and horizontal oscillations of the positron cloud were detected. PMID:21335901

Pixels, Imagers and Related Fabrication Methods

NASA Technical Reports Server (NTRS)

Pain, Bedabrata (Inventor); Cunningham, Thomas J. (Inventor)

2014-01-01

Pixels, imagers and related fabrication methods are described. The described methods result in cross-talk reduction in imagers and related devices by generating depletion regions. The devices can also be used with electronic circuits for imaging applications.

Pixels, Imagers and Related Fabrication Methods

NASA Technical Reports Server (NTRS)

Pain, Bedabrata (Inventor); Cunningham, Thomas J. (Inventor)

2016-01-01

Pixels, imagers and related fabrication methods are described. The described methods result in cross-talk reduction in imagers and related devices by generating depletion regions. The devices can also be used with electronic circuits for imaging applications.

An adaptive enhancement algorithm for infrared video based on modified k-means clustering

NASA Astrophysics Data System (ADS)

Zhang, Linze; Wang, Jingqi; Wu, Wen

2016-09-01

In this paper, we have proposed a video enhancement algorithm to improve the output video of the infrared camera. Sometimes the video obtained by infrared camera is very dark since there is no clear target. In this case, infrared video should be divided into frame images by frame extraction, in order to carry out the image enhancement. For the first frame image, which can be divided into k sub images by using K-means clustering according to the gray interval it occupies before k sub images' histogram equalization according to the amount of information per sub image, we used a method to solve a problem that final cluster centers close to each other in some cases; and for the other frame images, their initial cluster centers can be determined by the final clustering centers of the previous ones, and the histogram equalization of each sub image will be carried out after image segmentation based on K-means clustering. The histogram equalization can make the gray value of the image to the whole gray level, and the gray level of each sub image is determined by the ratio of pixels to a frame image. Experimental results show that this algorithm can improve the contrast of infrared video where night target is not obvious which lead to a dim scene, and reduce the negative effect given by the overexposed pixels adaptively in a certain range.

Log polar image sensor in CMOS technology

NASA Astrophysics Data System (ADS)

Scheffer, Danny; Dierickx, Bart; Pardo, Fernando; Vlummens, Jan; Meynants, Guy; Hermans, Lou

1996-08-01

We report on the design, design issues, fabrication and performance of a log-polar CMOS image sensor. The sensor is developed for the use in a videophone system for deaf and hearing impaired people, who are not capable of communicating through a 'normal' telephone. The system allows 15 detailed images per second to be transmitted over existing telephone lines. This framerate is sufficient for conversations by means of sign language or lip reading. The pixel array of the sensor consists of 76 concentric circles with (up to) 128 pixels per circle, in total 8013 pixels. The interior pixels have a pitch of 14 micrometers, up to 250 micrometers at the border. The 8013-pixels image is mapped (log-polar transformation) in a X-Y addressable 76 by 128 array.

A Multi-Modality CMOS Sensor Array for Cell-Based Assay and Drug Screening.

PubMed

Chi, Taiyun; Park, Jong Seok; Butts, Jessica C; Hookway, Tracy A; Su, Amy; Zhu, Chengjie; Styczynski, Mark P; McDevitt, Todd C; Wang, Hua

2015-12-01

In this paper, we present a fully integrated multi-modality CMOS cellular sensor array with four sensing modalities to characterize different cell physiological responses, including extracellular voltage recording, cellular impedance mapping, optical detection with shadow imaging and bioluminescence sensing, and thermal monitoring. The sensor array consists of nine parallel pixel groups and nine corresponding signal conditioning blocks. Each pixel group comprises one temperature sensor and 16 tri-modality sensor pixels, while each tri-modality sensor pixel can be independently configured for extracellular voltage recording, cellular impedance measurement (voltage excitation/current sensing), and optical detection. This sensor array supports multi-modality cellular sensing at the pixel level, which enables holistic cell characterization and joint-modality physiological monitoring on the same cellular sample with a pixel resolution of 80 μm × 100 μm. Comprehensive biological experiments with different living cell samples demonstrate the functionality and benefit of the proposed multi-modality sensing in cell-based assay and drug screening.

Terahertz Array Receivers with Integrated Antennas

NASA Technical Reports Server (NTRS)

Chattopadhyay, Goutam; Llombart, Nuria; Lee, Choonsup; Jung, Cecile; Lin, Robert; Cooper, Ken B.; Reck, Theodore; Siles, Jose; Schlecht, Erich; Peralta, Alessandro;

Multimodal imaging of the human knee down to the cellular level

NASA Astrophysics Data System (ADS)

Schulz, G.; Götz, C.; Müller-Gerbl, M.; Zanette, I.; Zdora, M.-C.; Khimchenko, A.; Deyhle, H.; Thalmann, P.; Müller, B.

2017-06-01

Computed tomography reaches the best spatial resolution for the three-dimensional visualization of human tissues among the available nondestructive clinical imaging techniques. Nowadays, sub-millimeter voxel sizes are regularly obtained. Regarding investigations on true micrometer level, lab-based micro-CT (μCT) has become gold standard. The aim of the present study is firstly the hierarchical investigation of a human knee post mortem using hard X-ray μCT and secondly a multimodal imaging using absorption and phase contrast modes in order to investigate hard (bone) and soft (cartilage) tissues on the cellular level. After the visualization of the entire knee using a clinical CT, a hierarchical imaging study was performed using the lab-system nanotom® m. First, the entire knee was measured with a pixel length of 65 μm. The highest resolution with a pixel length of 3 μm could be achieved after extracting cylindrically shaped plugs from the femoral bones. For the visualization of the cartilage, grating-based phase contrast μCT (I13-2, Diamond Light Source) was performed. With an effective voxel size of 2.3 μm it was possible to visualize individual chondrocytes within the cartilage.

Mapping Capacitive Coupling Among Pixels in a Sensor Array

NASA Technical Reports Server (NTRS)

Seshadri, Suresh; Cole, David M.; Smith, Roger M.

2010-01-01

An improved method of mapping the capacitive contribution to cross-talk among pixels in an imaging array of sensors (typically, an imaging photodetector array) has been devised for use in calibrating and/or characterizing such an array. The method involves a sequence of resets of subarrays of pixels to specified voltages and measurement of the voltage responses of neighboring non-reset pixels.

A compressed sensing X-ray camera with a multilayer architecture

DOE PAGES

Wang, Zhehui; Laroshenko, O.; Li, S.; ...

2018-01-25

Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. In this work, wemore » first illustrate the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.« less

A compressed sensing X-ray camera with a multilayer architecture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Zhehui; Laroshenko, O.; Li, S.

Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. In this work, wemore » first illustrate the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.« less

A 100 Mfps image sensor for biological applications

NASA Astrophysics Data System (ADS)

Etoh, T. Goji; Shimonomura, Kazuhiro; Nguyen, Anh Quang; Takehara, Kosei; Kamakura, Yoshinari; Goetschalckx, Paul; Haspeslagh, Luc; De Moor, Piet; Dao, Vu Truong Son; Nguyen, Hoang Dung; Hayashi, Naoki; Mitsui, Yo; Inumaru, Hideo

2018-02-01

Two ultrahigh-speed CCD image sensors with different characteristics were fabricated for applications to advanced scientific measurement apparatuses. The sensors are BSI MCG (Backside-illuminated Multi-Collection-Gate) image sensors with multiple collection gates around the center of the front side of each pixel, placed like petals of a flower. One has five collection gates and one drain gate at the center, which can capture consecutive five frames at 100 Mfps with the pixel count of about 600 kpixels (512 x 576 x 2 pixels). In-pixel signal accumulation is possible for repetitive image capture of reproducible events. The target application is FLIM. The other is equipped with four collection gates each connected to an in-situ CCD memory with 305 elements, which enables capture of 1,220 (4 x 305) consecutive images at 50 Mfps. The CCD memory is folded and looped with the first element connected to the last element, which also makes possible the in-pixel signal accumulation. The sensor is a small test sensor with 32 x 32 pixels. The target applications are imaging TOF MS, pulse neutron tomography and dynamic PSP. The paper also briefly explains an expression of the temporal resolution of silicon image sensors theoretically derived by the authors in 2017. It is shown that the image sensor designed based on the theoretical analysis achieves imaging of consecutive frames at the frame interval of 50 ps.

Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations.

PubMed

Huang, Rongyong; Zheng, Shunyi; Hu, Kun

2018-06-01

Registration of large-scale optical images with airborne LiDAR data is the basis of the integration of photogrammetry and LiDAR. However, geometric misalignments still exist between some aerial optical images and airborne LiDAR point clouds. To eliminate such misalignments, we extended a method for registering close-range optical images with terrestrial LiDAR data to a variety of large-scale aerial optical images and airborne LiDAR data. The fundamental principle is to minimize the distances from the photogrammetric matching points to the terrestrial LiDAR data surface. Except for the satisfactory efficiency of about 79 s per 6732 × 8984 image, the experimental results also show that the unit weighted root mean square (RMS) of the image points is able to reach a sub-pixel level (0.45 to 0.62 pixel), and the actual horizontal and vertical accuracy can be greatly improved to a high level of 1/4⁻1/2 (0.17⁻0.27 m) and 1/8⁻1/4 (0.10⁻0.15 m) of the average LiDAR point distance respectively. Finally, the method is proved to be more accurate, feasible, efficient, and practical in variety of large-scale aerial optical image and LiDAR data.

Automated coregistration of MTI spectral bands

NASA Astrophysics Data System (ADS)

Theiler, James P.; Galbraith, Amy E.; Pope, Paul A.; Ramsey, Keri A.; Szymanski, John J.

2002-08-01

In the focal plane of a pushbroom imager, a linear array of pixels is scanned across the scene, building up the image one row at a time. For the Multispectral Thermal Imager (MTI), each of fifteen different spectral bands has its own linear array. These arrays are pushed across the scene together, but since each band's array is at a different position on the focal plane, a separate image is produced for each band. The standard MTI data products (LEVEL1B_R_COREG and LEVEL1B_R_GEO) resample these separate images to a common grid and produce coregistered multispectral image cubes. The coregistration software employs a direct ``dead reckoning' approach. Every pixel in the calibrated image is mapped to an absolute position on the surface of the earth, and these are resampled to produce an undistorted coregistered image of the scene. To do this requires extensive information regarding the satellite position and pointing as a function of time, the precise configuration of the focal plane, and the distortion due to the optics. These must be combined with knowledge about the position and altitude of the target on the rotating ellipsoidal earth. We will discuss the direct approach to MTI coregistration, as well as more recent attempts to tweak the precision of the band-to-band registration using correlations in the imagery itself.

An Efficient Approach for Pixel Decomposition to Increase the Spatial Resolution of Land Surface Temperature Images from MODIS Thermal Infrared Band Data

PubMed Central

Wang, Fei; Qin, Zhihao; Li, Wenjuan; Song, Caiying; Karnieli, Arnon; Zhao, Shuhe

2015-01-01

Land surface temperature (LST) images retrieved from the thermal infrared (TIR) band data of Moderate Resolution Imaging Spectroradiometer (MODIS) have much lower spatial resolution than the MODIS visible and near-infrared (VNIR) band data. The coarse pixel scale of MODIS LST images (1000 m under nadir) have limited their capability in applying to many studies required high spatial resolution in comparison of the MODIS VNIR band data with pixel scale of 250–500 m. In this paper we intend to develop an efficient approach for pixel decomposition to increase the spatial resolution of MODIS LST image using the VNIR band data as assistance. The unique feature of this approach is to maintain the thermal radiance of parent pixels in the MODIS LST image unchanged after they are decomposed into the sub-pixels in the resulted image. There are two important steps in the decomposition: initial temperature estimation and final temperature determination. Therefore the approach can be termed double-step pixel decomposition (DSPD). Both steps involve a series of procedures to achieve the final result of decomposed LST image, including classification of the surface patterns, establishment of LST change with normalized difference of vegetation index (NDVI) and building index (NDBI), reversion of LST into thermal radiance through Planck equation, and computation of weights for the sub-pixels of the resulted image. Since the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with much higher spatial resolution than MODIS data was on-board the same platform (Terra) as MODIS for Earth observation, an experiment had been done in the study to validate the accuracy and efficiency of our approach for pixel decomposition. The ASTER LST image was used as the reference to compare with the decomposed LST image. The result showed that the spatial distribution of the decomposed LST image was very similar to that of the ASTER LST image with a root mean square error (RMSE) of 2.7 K for entire image. Comparison with the evaluation DisTrad (E-DisTrad) and re-sampling methods for pixel decomposition also indicate that our DSPD has the lowest RMSE in all cases, including urban region, water bodies, and natural terrain. The obvious increase in spatial resolution remarkably uplifts the capability of the coarse MODIS LST images in highlighting the details of LST variation. Therefore it can be concluded that, in spite of complicated procedures, the proposed DSPD approach provides an alternative to improve the spatial resolution of MODIS LST image hence expand its applicability to the real world. PMID:25609048

On edge-aware path-based color spatial sampling for Retinex: from Termite Retinex to Light Energy-driven Termite Retinex

NASA Astrophysics Data System (ADS)

Simone, Gabriele; Cordone, Roberto; Serapioni, Raul Paolo; Lecca, Michela

2017-05-01

Retinex theory estimates the human color sensation at any observed point by correcting its color based on the spatial arrangement of the colors in proximate regions. We revise two recent path-based, edge-aware Retinex implementations: Termite Retinex (TR) and Energy-driven Termite Retinex (ETR). As the original Retinex implementation, TR and ETR scan the neighborhood of any image pixel by paths and rescale their chromatic intensities by intensity levels computed by reworking the colors of the pixels on the paths. Our interest in TR and ETR is due to their unique, content-based scanning scheme, which uses the image edges to define the paths and exploits a swarm intelligence model for guiding the spatial exploration of the image. The exploration scheme of ETR has been showed to be particularly effective: its paths are local minima of an energy functional, designed to favor the sampling of image pixels highly relevant to color sensation. Nevertheless, since its computational complexity makes ETR poorly practicable, here we present a light version of it, named Light Energy-driven TR, and obtained from ETR by implementing a modified, optimized minimization procedure and by exploiting parallel computing.

CMOS image sensor with lateral electric field modulation pixels for fluorescence lifetime imaging with sub-nanosecond time response

NASA Astrophysics Data System (ADS)

Li, Zhuo; Seo, Min-Woong; Kagawa, Keiichiro; Yasutomi, Keita; Kawahito, Shoji

2016-04-01

This paper presents the design and implementation of a time-resolved CMOS image sensor with a high-speed lateral electric field modulation (LEFM) gating structure for time domain fluorescence lifetime measurement. Time-windowed signal charge can be transferred from a pinned photodiode (PPD) to a pinned storage diode (PSD) by turning on a pair of transfer gates, which are situated beside the channel. Unwanted signal charge can be drained from the PPD to the drain by turning on another pair of gates. The pixel array contains 512 (V) × 310 (H) pixels with 5.6 × 5.6 µm2 pixel size. The imager chip was fabricated using 0.11 µm CMOS image sensor process technology. The prototype sensor has a time response of 150 ps at 374 nm. The fill factor of the pixels is 5.6%. The usefulness of the prototype sensor is demonstrated for fluorescence lifetime imaging through simulation and measurement results.

Resolution Enhancement of MODIS-derived Water Indices for Studying Persistent Flooding

NASA Astrophysics Data System (ADS)

Underwood, L. W.; Kalcic, M. T.; Fletcher, R. M.

2012-12-01

Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250-m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.

Resolution Enhancement of MODIS-Derived Water Indices for Studying Persistent Flooding

NASA Technical Reports Server (NTRS)

Underwood, L. W.; Kalcic, Maria; Fletcher, Rose

2012-01-01

Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250-m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.

Structural colour printing from a reusable generic nanosubstrate masked for the target image

NASA Astrophysics Data System (ADS)

Rezaei, M.; Jiang, H.; Kaminska, B.

2016-02-01

Structural colour printing has advantages over traditional pigment-based colour printing. However, the high fabrication cost has hindered its applications in printing large-area images because each image requires patterning structural pixels in nanoscale resolution. In this work, we present a novel strategy to print structural colour images from a pixelated substrate which is called a nanosubstrate. The nanosubstrate is fabricated only once using nanofabrication tools and can be reused for printing a large quantity of structural colour images. It contains closely packed arrays of nanostructures from which red, green, blue and infrared structural pixels can be imprinted. To print a target colour image, the nanosubstrate is first covered with a mask layer to block all the structural pixels. The mask layer is subsequently patterned according to the target colour image to make apertures of controllable sizes on top of the wanted primary colour pixels. The masked nanosubstrate is then used as a stamp to imprint the colour image onto a separate substrate surface using nanoimprint lithography. Different visual colours are achieved by properly mixing the red, green and blue primary colours into appropriate ratios controlled by the aperture sizes on the patterned mask layer. Such a strategy significantly reduces the cost and complexity of printing a structural colour image from lengthy nanoscale patterning into high throughput micro-patterning and makes it possible to apply structural colour printing in personalized security features and data storage. In this paper, nanocone array grating pixels were used as the structural pixels and the nanosubstrate contains structures to imprint the nanocone arrays. Laser lithography was implemented to pattern the mask layer with submicron resolution. The optical properties of the nanocone array gratings are studied in detail. Multiple printed structural colour images with embedded covert information are demonstrated.

How many pixels does it take to make a good 4"×6" print? Pixel count wars revisited

NASA Astrophysics Data System (ADS)

Kriss, Michael A.

2011-01-01

In the early 1980's the future of conventional silver-halide photographic systems was of great concern due to the potential introduction of electronic imaging systems then typified by the Sony Mavica analog electronic camera. The focus was on the quality of film-based systems as expressed in the number of equivalent number pixels and bits-per-pixel, and how many pixels would be required to create an equivalent quality image from a digital camera. It was found that 35-mm frames, for ISO 100 color negative film, contained equivalent pixels of 12 microns for a total of 18 million pixels per frame (6 million pixels per layer) with about 6 bits of information per pixel; the introduction of new emulsion technology, tabular AgX grains, increased the value to 8 bit per pixel. Higher ISO speed films had larger equivalent pixels, fewer pixels per frame, but retained the 8 bits per pixel. Further work found that a high quality 3.5" x 5.25" print could be obtained from a three layer system containing 1300 x 1950 pixels per layer or about 7.6 million pixels in all. In short, it became clear that when a digital camera contained about 6 million pixels (in a single layer using a color filter array and appropriate image processing) that digital systems would challenge and replace conventional film-based system for the consumer market. By 2005 this became the reality. Since 2005 there has been a "pixel war" raging amongst digital camera makers. The question arises about just how many pixels are required and are all pixels equal? This paper will provide a practical look at how many pixels are needed for a good print based on the form factor of the sensor (sensor size) and the effective optical modulation transfer function (optical spread function) of the camera lens. Is it better to have 16 million, 5.7-micron pixels or 6 million 7.8-micron pixels? How does intrinsic (no electronic boost) ISO speed and exposure latitude vary with pixel size? A systematic review of these issues will be provided within the context of image quality and ISO speed models developed over the last 15 years.

a Data Field Method for Urban Remotely Sensed Imagery Classification Considering Spatial Correlation

NASA Astrophysics Data System (ADS)

Zhang, Y.; Qin, K.; Zeng, C.; Zhang, E. B.; Yue, M. X.; Tong, X.

2016-06-01

Spatial correlation between pixels is important information for remotely sensed imagery classification. Data field method and spatial autocorrelation statistics have been utilized to describe and model spatial information of local pixels. The original data field method can represent the spatial interactions of neighbourhood pixels effectively. However, its focus on measuring the grey level change between the central pixel and the neighbourhood pixels results in exaggerating the contribution of the central pixel to the whole local window. Besides, Geary's C has also been proven to well characterise and qualify the spatial correlation between each pixel and its neighbourhood pixels. But the extracted object is badly delineated with the distracting salt-and-pepper effect of isolated misclassified pixels. To correct this defect, we introduce the data field method for filtering and noise limitation. Moreover, the original data field method is enhanced by considering each pixel in the window as the central pixel to compute statistical characteristics between it and its neighbourhood pixels. The last step employs a support vector machine (SVM) for the classification of multi-features (e.g. the spectral feature and spatial correlation feature). In order to validate the effectiveness of the developed method, experiments are conducted on different remotely sensed images containing multiple complex object classes inside. The results show that the developed method outperforms the traditional method in terms of classification accuracies.

Digital radiology using active matrix readout: amplified pixel detector array for fluoroscopy.

PubMed

Matsuura, N; Zhao, W; Huang, Z; Rowlands, J A

1999-05-01

Active matrix array technology has made possible the concept of flat panel imaging systems for radiography. In the conventional approach a thin-film circuit built on glass contains the necessary switching components (thin-film transistors or TFTs) to readout an image formed in either a phosphor or photoconductor layer. Extension of this concept to real time imaging--fluoroscopy--has had problems due to the very low noise required. A new design strategy for fluoroscopic active matrix flat panel detectors has therefore been investigated theoretically. In this approach, the active matrix has integrated thin-film amplifiers and readout electronics at each pixel and is called the amplified pixel detector array (APDA). Each amplified pixel consists of three thin-film transistors: an amplifier, a readout, and a reset TFT. The performance of the APDA approach compared to the conventional active matrix was investigated for two semiconductors commonly used to construct active matrix arrays--hydrogenated amorphous silicon and polycrystalline silicon. The results showed that with amplification close to the pixel, the noise from the external charge preamplifiers becomes insignificant. The thermal and flicker noise of the readout and the amplifying TFTs at the pixel become the dominant sources of noise. The magnitude of these noise sources is strongly dependent on the TFT geometry and its fabrication process. Both of these could be optimized to make the APDA active matrix operate at lower noise levels than is possible with the conventional approach. However, the APDA cannot be made to operate ideally (i.e., have noise limited only by the amount of radiation used) at the lowest exposure rate required in medical fluoroscopy.

47 CFR 73.9003 - Compliance requirements for covered demodulator products: Unscreened content.

Code of Federal Regulations, 2010 CFR

2010-10-01

... operating in a mode compatible with the digital visual interface (DVI) rev. 1.0 Specification as an image having the visual equivalent of no more than 350,000 pixels per frame (e.g. an image with resolution of 720×480 pixels for a 4:3 (nonsquare pixel) aspect ratio), and 30 frames per second. Such an image may...

47 CFR 73.9004 - Compliance requirements for covered demodulator products: Marked content.

Code of Federal Regulations, 2010 CFR

2010-10-01

... compatible with the digital visual interface (DVI) Rev. 1.0 Specification as an image having the visual equivalent of no more than 350,000 pixels per frame (e.g., an image with resolution of 720×480 pixels for a 4:3 (nonsquare pixel) aspect ratio), and 30 frames per second. Such an image may be attained by...

Pixelated camouflage patterns from the perspective of hyperspectral imaging

NASA Astrophysics Data System (ADS)

Racek, František; Jobánek, Adam; Baláž, Teodor; Krejčí, Jaroslav

2016-10-01

Pixelated camouflage patterns fulfill the role of both principles the matching and the disrupting that are exploited for blending the target into the background. It means that pixelated pattern should respect natural background in spectral and spatial characteristics embodied in micro and macro patterns. The HS imaging plays the similar, however the reverse role in the field of reconnaissance systems. The HS camera fundamentally records and extracts both the spectral and spatial information belonging to the recorded scenery. Therefore, the article deals with problems of hyperspectral (HS) imaging and subsequent processing of HS images of pixelated camouflage patterns which are among others characterized by their specific spatial frequency heterogeneity.

Faxed document image restoration method based on local pixel patterns

NASA Astrophysics Data System (ADS)

Akiyama, Teruo; Miyamoto, Nobuo; Oguro, Masami; Ogura, Kenji

1998-04-01

A method for restoring degraded faxed document images using the patterns of pixels that construct small areas in a document is proposed. The method effectively restores faxed images that contain the halftone textures and/or density salt-and-pepper noise that degrade OCR system performance. The halftone image restoration process, white-centered 3 X 3 pixels, in which black-and-white pixels alternate, are identified first using the distribution of the pixel values as halftone textures, and then the white center pixels are inverted to black. To remove high-density salt- and-pepper noise, it is assumed that the degradation is caused by ill-balanced bias and inappropriate thresholding of the sensor output which results in the addition of random noise. Restored image can be estimated using an approximation that uses the inverse operation of the assumed original process. In order to process degraded faxed images, the algorithms mentioned above are combined. An experiment is conducted using 24 especially poor quality examples selected from data sets that exemplify what practical fax- based OCR systems cannot handle. The maximum recovery rate in terms of mean square error was 98.8 percent.

Active pixel image sensor with a winner-take-all mode of operation

NASA Technical Reports Server (NTRS)

Yadid-Pecht, Orly (Inventor); Mead, Carver (Inventor); Fossum, Eric R. (Inventor)

2003-01-01

An integrated CMOS semiconductor imaging device having two modes of operation that can be performed simultaneously to produce an output image and provide information of a brightest or darkest pixel in the image.

Weber-aware weighted mutual information evaluation for infrared-visible image fusion

NASA Astrophysics Data System (ADS)

Luo, Xiaoyan; Wang, Shining; Yuan, Ding

2016-10-01

A performance metric for infrared and visible image fusion is proposed based on Weber's law. To indicate the stimulus of source images, two Weber components are provided. One is differential excitation to reflect the spectral signal of visible and infrared images, and the other is orientation to capture the scene structure feature. By comparing the corresponding Weber component in infrared and visible images, the source pixels can be marked with different dominant properties in intensity or structure. If the pixels have the same dominant property label, the pixels are grouped to calculate the mutual information (MI) on the corresponding Weber components between dominant source and fused images. Then, the final fusion metric is obtained via weighting the group-wise MI values according to the number of pixels in different groups. Experimental results demonstrate that the proposed metric performs well on popular image fusion cases and outperforms other image fusion metrics.

Multi-Scale Fractal Analysis of Image Texture and Pattern

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Lam, Nina Siu-Ngan; Quattrochi, Dale A.

1999-01-01

Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images is the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimension-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.

Multi-Scale Fractal Analysis of Image Texture and Pattern

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Lam, Nina Siu-Ngan; Quattrochi, Dale A.

1999-01-01

Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images of the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimensional-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.

A 128 x 128 CMOS Active Pixel Image Sensor for Highly Integrated Imaging Systems

NASA Technical Reports Server (NTRS)

Mendis, Sunetra K.; Kemeny, Sabrina E.; Fossum, Eric R.

1993-01-01

A new CMOS-based image sensor that is intrinsically compatible with on-chip CMOS circuitry is reported. The new CMOS active pixel image sensor achieves low noise, high sensitivity, X-Y addressability, and has simple timing requirements. The image sensor was fabricated using a 2 micrometer p-well CMOS process, and consists of a 128 x 128 array of 40 micrometer x 40 micrometer pixels. The CMOS image sensor technology enables highly integrated smart image sensors, and makes the design, incorporation and fabrication of such sensors widely accessible to the integrated circuit community.

Calibration Methods for a 3D Triangulation Based Camera

NASA Astrophysics Data System (ADS)

Schulz, Ulrike; Böhnke, Kay

A sensor in a camera takes a gray level image (1536 x 512 pixels), which is reflected by a reference body. The reference body is illuminated by a linear laser line. This gray level image can be used for a 3D calibration. The following paper describes how a calibration program calculates the calibration factors. The calibration factors serve to determine the size of an unknown reference body.

UV Imaging of R136 with the GHRS and the WFPC-2

NASA Astrophysics Data System (ADS)

Malumuth, E. M.; Ebbets, D.; Heap, S. R.; Maran, S. P.; Hutchings, J. B.; Lindler, D. J.

1994-05-01

Now that the COSTAR corrective optics have been installed and aligned in the Hubble Space Telescope (HST), the Goddard High Resolution Spectrograph (GHRS) can obtain clean spectra and images of stars in very crowded fields. To demonstrate this restored capability, an Early Release Observation program to observe hot, luminous stars in the center of R136a (the central cluster of the 30 Doradus complex in the Large Magellanic Cloud) has been scheduled in early April. Through this program we will obtain a series of UV images through the Small Science Aperture (SSA) and Large Science Aperture (LSA) of the GHRS. The images will be taken with the N2 mirror and D2 detector (CsTe cathode on a MgF_2 window) and thus will have a bandpass that extends from 1150 to 3200 Angstroms. The SSA images will consist of 13 x 13 pixels with a pixel spacing of 0\\farcs027 pixel(-1) . Each pixel covers a 0\\farcs11 x 0\\farcs11 area on the sky. Thus each image will cover the entire SSA (0\\farcs22 x 0\\farcs22). The SSA images will include one centered on the initial pointing (located between R136a1 and R136a2; separation = 0\\farcs12), an image of R136a2, and an image of R136a5 (0\\farcs18 from R136a2). Two LSA images of the central region of R136 will be taken. The first, a 3 x 3 mosaic centered on R136a5, will consist of 22 x 22 pixels each, with a pixel spacing of 0\\farcs11 pixel(-1) . Together these images cover a 5\\farcs22 x 5\\farcs22 area. The second, will cover the central 1\\farcs2 x 1\\farcs2 with a pixel spacing of 0\\farcs055 pixel(-1) . These images will be examined to determine the true pointing for the spectra of R136a2 and R136a5, the imaging characteristics of the GHRS, and the UV brightnesses of all of the stars within the field. In addition to these images, 3 WFPC-2 PC exposures will be obtained with the F336W filter. These images are 5, 10 and 20 seconds in duration. Photometry of the stars in these images will be compared with the GHRS UV photometry, as well as published WFPC photometry.

Laser doppler blood flow imaging using a CMOS imaging sensor with on-chip signal processing.

PubMed

He, Diwei; Nguyen, Hoang C; Hayes-Gill, Barrie R; Zhu, Yiqun; Crowe, John A; Gill, Cally; Clough, Geraldine F; Morgan, Stephen P

2013-09-18

The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF) imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used off-chip cannot be implemented. Therefore the analog signal processing at each pixel is a tailored design for LDBF signals with balanced optimization for signal-to-noise ratio and silicon area. This custom made sensor offers key advantages over conventional sensors, viz. the analog signal processing at the pixel level carries out signal normalization; the AC amplification in combination with an anti-aliasing filter allows analog-to-digital conversion with a low number of bits; low resource implementation of the digital processor enables on-chip processing and the data bottleneck that exists between the detector and processing electronics has been overcome. The sensor demonstrates good agreement with simulation at each design stage. The measured optical performance of the sensor is demonstrated using modulated light signals and in vivo blood flow experiments. Images showing blood flow changes with arterial occlusion and an inflammatory response to a histamine skin-prick demonstrate that the sensor array is capable of detecting blood flow signals from tissue.

Salt Lake City, Utah

NASA Technical Reports Server (NTRS)

2002-01-01

Salt Lake City, Utah, will host the 2002 Winter Olympic Games. The city is located on the southeastern shore of the Great Salt Lake and sits to the west of the Wasatch Mountains, which rise more than 3,500 meters (10,000 feet) above sea level. The city was first settled in 1847 by pioneers seeking relief from religious persecution. Today Salt Lake City, the capital of Utah, is home to more than 170,000 residents. This true-color image of Salt Lake City was acquired by the Enhanced Thematic Mapper Plus (ETM+), flying aboard Landsat 7, on May 26, 2000. The southeastern tip of the Great Salt Lake is visible in the upper left of the image. The furrowed green and brown landscape running north-south is a portion of the Wasatch Mountains, some of which are snow-capped (white pixels). The greyish pixels in the center of the image show the developed areas of the city. A number of water reservoirs can be seen east of the mountain range. Salt Lake City International Airport is visible on the northwestern edge of the city. About 20 miles south of the airport is the Bingham Canyon Copper Mine (tan pixels), the world's largest open pit excavation. See also this MODIS image of Utah. Image courtesy NASA Landsat7 Science Team and USGS Eros Data Center

Chromatic Modulator for a High-Resolution CCD or APS

NASA Technical Reports Server (NTRS)

Hartley, Frank; Hull, Anthony

2008-01-01

A chromatic modulator has been proposed to enable the separate detection of the red, green, and blue (RGB) color components of the same scene by a single charge-coupled device (CCD), active-pixel sensor (APS), or similar electronic image detector. Traditionally, the RGB color-separation problem in an electronic camera has been solved by use of either (1) fixed color filters over three separate image detectors; (2) a filter wheel that repeatedly imposes a red, then a green, then a blue filter over a single image detector; or (3) different fixed color filters over adjacent pixels. The use of separate image detectors necessitates precise registration of the detectors and the use of complicated optics; filter wheels are expensive and add considerably to the bulk of the camera; and fixed pixelated color filters reduce spatial resolution and introduce color-aliasing effects. The proposed chromatic modulator would not exhibit any of these shortcomings. The proposed chromatic modulator would be an electromechanical device fabricated by micromachining. It would include a filter having a spatially periodic pattern of RGB strips at a pitch equal to that of the pixels of the image detector. The filter would be placed in front of the image detector, supported at its periphery by a spring suspension and electrostatic comb drive. The spring suspension would bias the filter toward a middle position in which each filter strip would be registered with a row of pixels of the image detector. Hard stops would limit the excursion of the spring suspension to precisely one pixel row above and one pixel row below the middle position. In operation, the electrostatic comb drive would be actuated to repeatedly snap the filter to the upper extreme, middle, and lower extreme positions. This action would repeatedly place a succession of the differently colored filter strips in front of each pixel of the image detector. To simplify the processing, it would be desirable to encode information on the color of the filter strip over each row (or at least over some representative rows) of pixels at a given instant of time in synchronism with the pixel output at that instant.

Improved discrimination among similar agricultural plots using red-and-green-based pseudo-colour imaging

NASA Astrophysics Data System (ADS)

Doi, Ryoichi

2016-04-01

The effects of a pseudo-colour imaging method were investigated by discriminating among similar agricultural plots in remote sensing images acquired using the Airborne Visible/Infrared Imaging Spectrometer (Indiana, USA) and the Landsat 7 satellite (Fergana, Uzbekistan), and that provided by GoogleEarth (Toyama, Japan). From each dataset, red (R)-green (G)-R-G-blue yellow (RGrgbyB), and RGrgby-1B pseudo-colour images were prepared. From each, cyan, magenta, yellow, key black, L*, a*, and b* derivative grayscale images were generated. In the Airborne Visible/Infrared Imaging Spectrometer image, pixels were selected for corn no tillage (29 pixels), corn minimum tillage (27), and soybean (34) plots. Likewise, in the Landsat 7 image, pixels representing corn (73 pixels), cotton (110), and wheat (112) plots were selected, and in the GoogleEarth image, those representing soybean (118 pixels) and rice (151) were selected. When the 14 derivative grayscale images were used together with an RGB yellow grayscale image, the overall classification accuracy improved from 74 to 94% (Airborne Visible/Infrared Imaging Spectrometer), 64 to 83% (Landsat), or 77 to 90% (GoogleEarth). As an indicator of discriminatory power, the kappa significance improved 1018-fold (Airborne Visible/Infrared Imaging Spectrometer) or greater. The derivative grayscale images were found to increase the dimensionality and quantity of data. Herein, the details of the increases in dimensionality and quantity are further analysed and discussed.

Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks

PubMed Central

Xu, Xin; Gui, Rong; Pu, Fangling

2018-01-01

Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods. PMID:29510499

Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks.

PubMed

Wang, Lei; Xu, Xin; Dong, Hao; Gui, Rong; Pu, Fangling

2018-03-03

Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods.

Pixelated coatings and advanced IR coatings

NASA Astrophysics Data System (ADS)

Pradal, Fabien; Portier, Benjamin; Oussalah, Meihdi; Leplan, Hervé

2017-09-01

Reosc developed pixelated infrared coatings on detector. Reosc manufactured thick pixelated multilayer stacks on IR-focal plane arrays for bi-spectral imaging systems, demonstrating high filter performance, low crosstalk, and no deterioration of the device sensitivities. More recently, a 5-pixel filter matrix was designed and fabricated. Recent developments in pixelated coatings, shows that high performance infrared filters can be coated directly on detector for multispectral imaging. Next generation space instrument can benefit from this technology to reduce their weight and consumptions.

A noise-immune cryptographic information protection method for facsimile information transmission and the realization algorithms

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Bardachenko, Vitaliy F.; Nikolsky, Alexander I.; Lazarev, Alexander A.; Ogorodnik, Konstantin V.

2006-04-01

We analyse the existent methods of cryptographic defence for the facsimile information transfer, consider their shortcomings and prove the necessity of better information protection degree. The method of information protection that is based on presentation of input data as images is proposed. We offer a new noise-immune algorithm for realization of this method which consists in transformation of an input frame by pixels transposition according to an entered key. At decoding mode the reverse transformation of image with the use of the same key is used. Practical realization of the given method takes into account noise in the transmission channels and information distortions by scanners, faxes and others like that. We show that the given influences are reduced to the transformation of the input image coordinates. We show the algorithm in detail and consider its basic steps. We show the possibility of the offered method by the means of the developed software. The realized algorithm corrects curvature of frames: turn, scaling, fallout of pixels and others like that. At low noise level (loss of pixel information less than 10 percents) it is possible to encode, transfer and decode any types of images and texts with 12-size font character. The software filters for information restore and noise removing allow to transfer fax data with 30 percents pixels loss at 18-size font text. This percent of data loss can be considerably increased by the use of the software character recognition block that can be realized on fuzzy-neural algorithms. Examples of encoding and decryption of images and texts are shown.

Supervised pixel classification for segmenting geographic atrophy in fundus autofluorescene images

NASA Astrophysics Data System (ADS)

Hu, Zhihong; Medioni, Gerard G.; Hernandez, Matthias; Sadda, SriniVas R.

2014-03-01

Age-related macular degeneration (AMD) is the leading cause of blindness in people over the age of 65. Geographic atrophy (GA) is a manifestation of the advanced or late-stage of the AMD, which may result in severe vision loss and blindness. Techniques to rapidly and precisely detect and quantify GA lesions would appear to be of important value in advancing the understanding of the pathogenesis of GA and the management of GA progression. The purpose of this study is to develop an automated supervised pixel classification approach for segmenting GA including uni-focal and multi-focal patches in fundus autofluorescene (FAF) images. The image features include region wise intensity (mean and variance) measures, gray level co-occurrence matrix measures (angular second moment, entropy, and inverse difference moment), and Gaussian filter banks. A k-nearest-neighbor (k-NN) pixel classifier is applied to obtain a GA probability map, representing the likelihood that the image pixel belongs to GA. A voting binary iterative hole filling filter is then applied to fill in the small holes. Sixteen randomly chosen FAF images were obtained from sixteen subjects with GA. The algorithm-defined GA regions are compared with manual delineation performed by certified graders. Two-fold cross-validation is applied for the evaluation of the classification performance. The mean Dice similarity coefficients (DSC) between the algorithm- and manually-defined GA regions are 0.84 +/- 0.06 for one test and 0.83 +/- 0.07 for the other test and the area correlations between them are 0.99 (p < 0.05) and 0.94 (p < 0.05) respectively.

Synthetic aperture radar images with composite azimuth resolution

DOEpatents

Bielek, Timothy P; Bickel, Douglas L

2015-03-31

A synthetic aperture radar (SAR) image is produced by using all phase histories of a set of phase histories to produce a first pixel array having a first azimuth resolution, and using less than all phase histories of the set to produce a second pixel array having a second azimuth resolution that is coarser than the first azimuth resolution. The first and second pixel arrays are combined to produce a third pixel array defining a desired SAR image that shows distinct shadows of moving objects while preserving detail in stationary background clutter.

A custom hardware classifier for bruised apple detection in hyperspectral images

NASA Astrophysics Data System (ADS)

Cárdenas, Javier; Figueroa, Miguel; Pezoa, Jorge E.

2015-09-01

We present a custom digital architecture for bruised apple classification using hyperspectral images in the near infrared (NIR) spectrum. The algorithm classifies each pixel in an image into one of three classes: bruised, non-bruised, and background. We extract two 5-element feature vectors for each pixel using only 10 out of the 236 spectral bands provided by the hyperspectral camera, thereby greatly reducing both the requirements of the imager and the computational complexity of the algorithm. We then use two linear-kernel support vector machine (SVM) to classify each pixel. Each SVM was trained with 504 windows of size 17×17-pixel taken from 14 hyperspectral images of 320×320 pixels each, for each class. The architecture then computes the percentage of bruised pixels in each apple in order to adequately classify the fruit. We implemented the architecture on a Xilinx Zynq Z-7010 field-programmable gate array (FPGA) and tested it on images from a NIR N17E push-broom camera with a frame rate of 25 fps, a band-pixel rate of 1.888 MHz, and 236 spectral bands between 900 and 1700 nanometers in laboratory conditions. Using 28-bit fixed-point arithmetic, the circuit accurately discriminates 95.2% of the pixels corresponding to an apple, 81% of the pixels corresponding to a bruised apple, and 96.4% of the background. With the default threshold settings, the highest false positive (FP) for a bruised apple is 18.7%. The circuit operates at the native frame rate of the camera, consumes 67 mW of dynamic power, and uses less than 10% of the logic resources on the FPGA.

Pixel-level plasmonic microcavity infrared photodetector

PubMed Central

Jing, You Liang; Li, Zhi Feng; Li, Qian; Chen, Xiao Shuang; Chen, Ping Ping; Wang, Han; Li, Meng Yao; Li, Ning; Lu, Wei

2016-01-01

Recently, plasmonics has been central to the manipulation of photons on the subwavelength scale, and superior infrared imagers have opened novel applications in many fields. Here, we demonstrate the first pixel-level plasmonic microcavity infrared photodetector with a single quantum well integrated between metal patches and a reflection layer. Greater than one order of magnitude enhancement of the peak responsivity has been observed. The significant improvement originates from the highly confined optical mode in the cavity, leading to a strong coupling between photons and the quantum well, resulting in the enhanced photo-electric conversion process. Such strong coupling from the localized surface plasmon mode inside the cavity is independent of incident angles, offering a unique solution to high-performance focal plane array devices. This demonstration paves the way for important infrared optoelectronic devices for sensing and imaging. PMID:27181111

Hyperspectral image denoising and anomaly detection based on low-rank and sparse representations

NASA Astrophysics Data System (ADS)

Zhuang, Lina; Gao, Lianru; Zhang, Bing; Bioucas-Dias, José M.

2017-10-01

The very high spectral resolution of Hyperspectral Images (HSIs) enables the identification of materials with subtle differences and the extraction subpixel information. However, the increasing of spectral resolution often implies an increasing in the noise linked with the image formation process. This degradation mechanism limits the quality of extracted information and its potential applications. Since HSIs represent natural scenes and their spectral channels are highly correlated, they are characterized by a high level of self-similarity and are well approximated by low-rank representations. These characteristic underlies the state-of-the-art in HSI denoising. However, in presence of rare pixels, the denoising performance of those methods is not optimal and, in addition, it may compromise the future detection of those pixels. To address these hurdles, we introduce RhyDe (Robust hyperspectral Denoising), a powerful HSI denoiser, which implements explicit low-rank representation, promotes self-similarity, and, by using a form of collaborative sparsity, preserves rare pixels. The denoising and detection effectiveness of the proposed robust HSI denoiser is illustrated using semi-real data.

Movie denoising by average of warped lines.

PubMed

Bertalmío, Marcelo; Caselles, Vicent; Pardo, Alvaro

2007-09-01

Here, we present an efficient method for movie denoising that does not require any motion estimation. The method is based on the well-known fact that averaging several realizations of a random variable reduces the variance. For each pixel to be denoised, we look for close similar samples along the level surface passing through it. With these similar samples, we estimate the denoised pixel. The method to find close similar samples is done via warping lines in spatiotemporal neighborhoods. For that end, we present an algorithm based on a method for epipolar line matching in stereo pairs which has per-line complexity O (N), where N is the number of columns in the image. In this way, when applied to the image sequence, our algorithm is computationally efficient, having a complexity of the order of the total number of pixels. Furthermore, we show that the presented method is unsupervised and is adapted to denoise image sequences with an additive white noise while respecting the visual details on the movie frames. We have also experimented with other types of noise with satisfactory results.

a Study of the Impact of Insolation on Remote Sensing-Based Landcover and Landuse Data Extraction

NASA Astrophysics Data System (ADS)

Becek, K.; Borkowski, A.; Mekik, Ç.

2016-06-01

We examined the dependency of the pixel reflectance of hyperspectral imaging spectrometer data (HISD) on a normalized total insolation index (NTII). The NTII was estimated using a light detection and ranging (LiDAR)-derived digital surface model (DSM). The NTII and the pixel reflectance were dependent, to various degrees, on the band considered, and on the properties of the objects. The findings could be used to improve land cover (LC)/land use (LU) classification, using indices constructed from the spectral bands of imaging spectrometer data (ISD). To study this possibility, we investigated the normalized difference vegetation index (NDVI) at various NTII levels. The results also suggest that the dependency of the pixel reflectance and NTII could be used to mitigate the shadows in ISD. This project was carried out using data provided by the Hyperspectral Image Analysis Group and the NSF-funded Centre for Airborne Laser Mapping (NCALM), University of Houston, for the purpose of organizing the 2013 Data Fusion Contest (IEEE 2014). This contest was organized by the IEEE GRSS Data Fusion Technical Committee.

WE-EF-207-07: Dual Energy CT with One Full Scan and a Second Sparse-View Scan Using Structure Preserving Iterative Reconstruction (SPIR)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, T; Zhu, L

Purpose: Conventional dual energy CT (DECT) reconstructs CT and basis material images from two full-size projection datasets with different energy spectra. To relax the data requirement, we propose an iterative DECT reconstruction algorithm using one full scan and a second sparse-view scan by utilizing redundant structural information of the same object acquired at two different energies. Methods: We first reconstruct a full-scan CT image using filtered-backprojection (FBP) algorithm. The material similarities of each pixel with other pixels are calculated by an exponential function about pixel value differences. We assume that the material similarities of pixels remains in the second CTmore » scan, although pixel values may vary. An iterative method is designed to reconstruct the second CT image from reduced projections. Under the data fidelity constraint, the algorithm minimizes the L2 norm of the difference between pixel value and its estimation, which is the average of other pixel values weighted by their similarities. The proposed algorithm, referred to as structure preserving iterative reconstruction (SPIR), is evaluated on physical phantoms. Results: On the Catphan600 phantom, SPIR-based DECT method with a second 10-view scan reduces the noise standard deviation of a full-scan FBP CT reconstruction by a factor of 4 with well-maintained spatial resolution, while iterative reconstruction using total-variation regularization (TVR) degrades the spatial resolution at the same noise level. The proposed method achieves less than 1% measurement difference on electron density map compared with the conventional two-full-scan DECT. On an anthropomorphic pediatric phantom, our method successfully reconstructs the complicated vertebra structures and decomposes bone and soft tissue. Conclusion: We develop an effective method to reduce the number of views and therefore data acquisition in DECT. We show that SPIR-based DECT using one full scan and a second 10-view scan can provide high-quality DECT images and accurate electron density maps as conventional two-full-scan DECT.« less

Compression of color-mapped images

NASA Technical Reports Server (NTRS)

Hadenfeldt, A. C.; Sayood, Khalid

1992-01-01

In a standard image coding scenario, pixel-to-pixel correlation nearly always exists in the data, especially if the image is a natural scene. This correlation is what allows predictive coding schemes (e.g., DPCM) to perform efficient compression. In a color-mapped image, the values stored in the pixel array are no longer directly related to the pixel intensity. Two color indices which are numerically adjacent (close) may point to two very different colors. The correlation still exists, but only via the colormap. This fact can be exploited by sorting the color map to reintroduce the structure. The sorting of colormaps is studied and it is shown how the resulting structure can be used in both lossless and lossy compression of images.

PIXEL PUSHER

NASA Technical Reports Server (NTRS)

Stanfill, D. F.

1994-01-01

Pixel Pusher is a Macintosh application used for viewing and performing minor enhancements on imagery. It will read image files in JPL's two primary image formats- VICAR and PDS - as well as the Macintosh PICT format. VICAR (NPO-18076) handles an array of image processing capabilities which may be used for a variety of applications including biomedical image processing, cartography, earth resources, and geological exploration. Pixel Pusher can also import VICAR format color lookup tables for viewing images in pseudocolor (256 colors). This program currently supports only eight bit images but will work on monitors with any number of colors. Arbitrarily large image files may be viewed in a normal Macintosh window. Color and contrast enhancement can be performed with a graphical "stretch" editor (as in contrast stretch). In addition, VICAR images may be saved as Macintosh PICT files for exporting into other Macintosh programs, and individual pixels can be queried to determine their locations and actual data values. Pixel Pusher is written in Symantec's Think C and was developed for use on a Macintosh SE30, LC, or II series computer running System Software 6.0.3 or later and 32 bit QuickDraw. Pixel Pusher will only run on a Macintosh which supports color (whether a color monitor is being used or not). The standard distribution medium for this program is a set of three 3.5 inch Macintosh format diskettes. The program price includes documentation. Pixel Pusher was developed in 1991 and is a copyrighted work with all copyright vested in NASA. Think C is a trademark of Symantec Corporation. Macintosh is a registered trademark of Apple Computer, Inc.

WE-G-204-03: Photon-Counting Hexagonal Pixel Array CdTe Detector: Optimal Resampling to Square Pixels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shrestha, S; Vedantham, S; Karellas, A

Purpose: Detectors with hexagonal pixels require resampling to square pixels for distortion-free display of acquired images. In this work, the presampling modulation transfer function (MTF) of a hexagonal pixel array photon-counting CdTe detector for region-of-interest fluoroscopy was measured and the optimal square pixel size for resampling was determined. Methods: A 0.65mm thick CdTe Schottky sensor capable of concurrently acquiring up to 3 energy-windowed images was operated in a single energy-window mode to include ≥10 KeV photons. The detector had hexagonal pixels with apothem of 30 microns resulting in pixel spacing of 60 and 51.96 microns along the two orthogonal directions.more » Images of a tungsten edge test device acquired under IEC RQA5 conditions were double Hough transformed to identify the edge and numerically differentiated. The presampling MTF was determined from the finely sampled line spread function that accounted for the hexagonal sampling. The optimal square pixel size was determined in two ways; the square pixel size for which the aperture function evaluated at the Nyquist frequencies along the two orthogonal directions matched that from the hexagonal pixel aperture functions, and the square pixel size for which the mean absolute difference between the square and hexagonal aperture functions was minimized over all frequencies up to the Nyquist limit. Results: Evaluation of the aperture functions over the entire frequency range resulted in square pixel size of 53 microns with less than 2% difference from the hexagonal pixel. Evaluation of the aperture functions at Nyquist frequencies alone resulted in 54 microns square pixels. For the photon-counting CdTe detector and after resampling to 53 microns square pixels using quadratic interpolation, the presampling MTF at Nyquist frequency of 9.434 cycles/mm along the two directions were 0.501 and 0.507. Conclusion: Hexagonal pixel array photon-counting CdTe detector after resampling to square pixels provides high-resolution imaging suitable for fluoroscopy.« less

Compact SPAD-Based Pixel Architectures for Time-Resolved Image Sensors

PubMed Central

Perenzoni, Matteo; Pancheri, Lucio; Stoppa, David

2016-01-01

This paper reviews the state of the art of single-photon avalanche diode (SPAD) image sensors for time-resolved imaging. The focus of the paper is on pixel architectures featuring small pixel size (<25 μm) and high fill factor (>20%) as a key enabling technology for the successful implementation of high spatial resolution SPAD-based image sensors. A summary of the main CMOS SPAD implementations, their characteristics and integration challenges, is provided from the perspective of targeting large pixel arrays, where one of the key drivers is the spatial uniformity. The main analog techniques aimed at time-gated photon counting and photon timestamping suitable for compact and low-power pixels are critically discussed. The main features of these solutions are the adoption of analog counting techniques and time-to-analog conversion, in NMOS-only pixels. Reliable quantum-limited single-photon counting, self-referenced analog-to-digital conversion, time gating down to 0.75 ns and timestamping with 368 ps jitter are achieved. PMID:27223284

Correction of clipped pixels in color images.

PubMed

Xu, Di; Doutre, Colin; Nasiopoulos, Panos

2011-03-01

Conventional images store a very limited dynamic range of brightness. The true luma in the bright area of such images is often lost due to clipping. When clipping changes the R, G, B color ratios of a pixel, color distortion also occurs. In this paper, we propose an algorithm to enhance both the luma and chroma of the clipped pixels. Our method is based on the strong chroma spatial correlation between clipped pixels and their surrounding unclipped area. After identifying the clipped areas in the image, we partition the clipped areas into regions with similar chroma, and estimate the chroma of each clipped region based on the chroma of its surrounding unclipped region. We correct the clipped R, G, or B color channels based on the estimated chroma and the unclipped color channel(s) of the current pixel. The last step involves smoothing of the boundaries between regions of different clipping scenarios. Both objective and subjective experimental results show that our algorithm is very effective in restoring the color of clipped pixels. © 2011 IEEE

Label-Free Biomedical Imaging Using High-Speed Lock-In Pixel Sensor for Stimulated Raman Scattering

PubMed Central

Mars, Kamel; Kawahito, Shoji; Yasutomi, Keita; Kagawa, Keiichiro; Yamada, Takahiro

2017-01-01

Raman imaging eliminates the need for staining procedures, providing label-free imaging to study biological samples. Recent developments in stimulated Raman scattering (SRS) have achieved fast acquisition speed and hyperspectral imaging. However, there has been a problem of lack of detectors suitable for MHz modulation rate parallel detection, detecting multiple small SRS signals while eliminating extremely strong offset due to direct laser light. In this paper, we present a complementary metal-oxide semiconductor (CMOS) image sensor using high-speed lock-in pixels for stimulated Raman scattering that is capable of obtaining the difference of Stokes-on and Stokes-off signal at modulation frequency of 20 MHz in the pixel before reading out. The generated small SRS signal is extracted and amplified in a pixel using a high-speed and large area lateral electric field charge modulator (LEFM) employing two-step ion implantation and an in-pixel pair of low-pass filter, a sample and hold circuit and a switched capacitor integrator using a fully differential amplifier. A prototype chip is fabricated using 0.11 μm CMOS image sensor technology process. SRS spectra and images of stearic acid and 3T3-L1 samples are successfully obtained. The outcomes suggest that hyperspectral and multi-focus SRS imaging at video rate is viable after slight modifications to the pixel architecture and the acquisition system. PMID:29120358

Label-Free Biomedical Imaging Using High-Speed Lock-In Pixel Sensor for Stimulated Raman Scattering.

PubMed

Mars, Kamel; Lioe, De Xing; Kawahito, Shoji; Yasutomi, Keita; Kagawa, Keiichiro; Yamada, Takahiro; Hashimoto, Mamoru

2017-11-09

Raman imaging eliminates the need for staining procedures, providing label-free imaging to study biological samples. Recent developments in stimulated Raman scattering (SRS) have achieved fast acquisition speed and hyperspectral imaging. However, there has been a problem of lack of detectors suitable for MHz modulation rate parallel detection, detecting multiple small SRS signals while eliminating extremely strong offset due to direct laser light. In this paper, we present a complementary metal-oxide semiconductor (CMOS) image sensor using high-speed lock-in pixels for stimulated Raman scattering that is capable of obtaining the difference of Stokes-on and Stokes-off signal at modulation frequency of 20 MHz in the pixel before reading out. The generated small SRS signal is extracted and amplified in a pixel using a high-speed and large area lateral electric field charge modulator (LEFM) employing two-step ion implantation and an in-pixel pair of low-pass filter, a sample and hold circuit and a switched capacitor integrator using a fully differential amplifier. A prototype chip is fabricated using 0.11 μm CMOS image sensor technology process. SRS spectra and images of stearic acid and 3T3-L1 samples are successfully obtained. The outcomes suggest that hyperspectral and multi-focus SRS imaging at video rate is viable after slight modifications to the pixel architecture and the acquisition system.

Discovery of Finely Structured Dynamic Solar Corona Observed in the Hi-C Telescope

NASA Technical Reports Server (NTRS)

Winebarger, A.; Cirtain, J.; Golub, L.; DeLuca, E.; Savage, S.; Alexander, C.; Schuler, T.

2014-01-01

In the summer of 2012, the High-resolution Coronal Imager (Hi-C) flew aboard a NASA sounding rocket and collected the highest spatial resolution images ever obtained of the solar corona. One of the goals of the Hi-C flight was to characterize the substructure of the solar corona. We therefore examine how the intensity scales from AIA resolution to Hi-C resolution. For each low-resolution pixel, we calculate the standard deviation in the contributing high-resolution pixel intensities and compare that to the expected standard deviation calculated from the noise. If these numbers are approximately equal, the corona can be assumed to be smoothly varying, i.e. have no evidence of substructure in the Hi-C image to within Hi-C's ability to measure it given its throughput and readout noise. A standard deviation much larger than the noise value indicates the presence of substructure. We calculate these values for each low-resolution pixel for each frame of the Hi-C data. On average, 70 percent of the pixels in each Hi-C image show no evidence of substructure. The locations where substructure is prevalent is in the moss regions and in regions of sheared magnetic field. We also find that the level of substructure varies significantly over the roughly 160 s of the Hi-C data analyzed here. This result indicates that the finely structured corona is concentrated in regions of heating and is highly time dependent.

DISCOVERY OF FINELY STRUCTURED DYNAMIC SOLAR CORONA OBSERVED IN THE Hi-C TELESCOPE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winebarger, Amy R.; Cirtain, Jonathan; Savage, Sabrina

In the Summer of 2012, the High-resolution Coronal Imager (Hi-C) flew on board a NASA sounding rocket and collected the highest spatial resolution images ever obtained of the solar corona. One of the goals of the Hi-C flight was to characterize the substructure of the solar corona. We therefore examine how the intensity scales from AIA resolution to Hi-C resolution. For each low-resolution pixel, we calculate the standard deviation in the contributing high-resolution pixel intensities and compare that to the expected standard deviation calculated from the noise. If these numbers are approximately equal, the corona can be assumed to bemore » smoothly varying, i.e., have no evidence of substructure in the Hi-C image to within Hi-C's ability to measure it given its throughput and readout noise. A standard deviation much larger than the noise value indicates the presence of substructure. We calculate these values for each low-resolution pixel for each frame of the Hi-C data. On average, 70% of the pixels in each Hi-C image show no evidence of substructure. The locations where substructure is prevalent is in the moss regions and in regions of sheared magnetic field. We also find that the level of substructure varies significantly over the roughly 160 s of the Hi-C data analyzed here. This result indicates that the finely structured corona is concentrated in regions of heating and is highly time dependent.« less

PET-CT image fusion using random forest and à-trous wavelet transform.

PubMed

Seal, Ayan; Bhattacharjee, Debotosh; Nasipuri, Mita; Rodríguez-Esparragón, Dionisio; Menasalvas, Ernestina; Gonzalo-Martin, Consuelo

2018-03-01

New image fusion rules for multimodal medical images are proposed in this work. Image fusion rules are defined by random forest learning algorithm and a translation-invariant à-trous wavelet transform (AWT). The proposed method is threefold. First, source images are decomposed into approximation and detail coefficients using AWT. Second, random forest is used to choose pixels from the approximation and detail coefficients for forming the approximation and detail coefficients of the fused image. Lastly, inverse AWT is applied to reconstruct fused image. All experiments have been performed on 198 slices of both computed tomography and positron emission tomography images of a patient. A traditional fusion method based on Mallat wavelet transform has also been implemented on these slices. A new image fusion performance measure along with 4 existing measures has been presented, which helps to compare the performance of 2 pixel level fusion methods. The experimental results clearly indicate that the proposed method outperforms the traditional method in terms of visual and quantitative qualities and the new measure is meaningful. Copyright © 2017 John Wiley & Sons, Ltd.

Computational polarization difference underwater imaging based on image fusion

NASA Astrophysics Data System (ADS)

Han, Hongwei; Zhang, Xiaohui; Guan, Feng

2016-01-01

Polarization difference imaging can improve the quality of images acquired underwater, whether the background and veiling light are unpolarized or partial polarized. Computational polarization difference imaging technique which replaces the mechanical rotation of polarization analyzer and shortens the time spent to select the optimum orthogonal ǁ and ⊥axes is the improvement of the conventional PDI. But it originally gets the output image by setting the weight coefficient manually to an identical constant for all pixels. In this paper, a kind of algorithm is proposed to combine the Q and U parameters of the Stokes vector through pixel-level image fusion theory based on non-subsample contourlet transform. The experimental system built by the green LED array with polarizer to illuminate a piece of flat target merged in water and the CCD with polarization analyzer to obtain target image under different angle is used to verify the effect of the proposed algorithm. The results showed that the output processed by our algorithm could show more details of the flat target and had higher contrast compared to original computational polarization difference imaging.

Development of high energy micro-tomography system at SPring-8

NASA Astrophysics Data System (ADS)

Uesugi, Kentaro; Hoshino, Masato

2017-09-01

A high energy X-ray micro-tomography system has been developed at BL20B2 in SPring-8. The available range of the energy is between 20keV and 113keV with a Si (511) double crystal monochromator. The system enables us to image large or heavy materials such as fossils and metals. The X-ray image detector consists of visible light conversion system and sCMOS camera. The effective pixel size is variable by changing a tandem lens between 6.5 μm/pixel and 25.5 μm/pixel discretely. The format of the camera is 2048 pixels x 2048 pixels. As a demonstration of the system, alkaline battery and a nodule from Bolivia were imaged. A detail of the structure of the battery and a female mold Trilobite were successfully imaged without breaking those fossils.

Enhancing spatial resolution of (18)F positron imaging with the Timepix detector by classification of primary fired pixels using support vector machine.

PubMed

Wang, Qian; Liu, Zhen; Ziegler, Sibylle I; Shi, Kuangyu

2015-07-07

Position-sensitive positron cameras using silicon pixel detectors have been applied for some preclinical and intraoperative clinical applications. However, the spatial resolution of a positron camera is limited by positron multiple scattering in the detector. An incident positron may fire a number of successive pixels on the imaging plane. It is still impossible to capture the primary fired pixel along a particle trajectory by hardware or to perceive the pixel firing sequence by direct observation. Here, we propose a novel data-driven method to improve the spatial resolution by classifying the primary pixels within the detector using support vector machine. A classification model is constructed by learning the features of positron trajectories based on Monte-Carlo simulations using Geant4. Topological and energy features of pixels fired by (18)F positrons were considered for the training and classification. After applying the classification model on measurements, the primary fired pixels of the positron tracks in the silicon detector were estimated. The method was tested and assessed for [(18)F]FDG imaging of an absorbing edge protocol and a leaf sample. The proposed method improved the spatial resolution from 154.6   ±   4.2 µm (energy weighted centroid approximation) to 132.3   ±   3.5 µm in the absorbing edge measurements. For the positron imaging of a leaf sample, the proposed method achieved lower root mean square error relative to phosphor plate imaging, and higher similarity with the reference optical image. The improvements of the preliminary results support further investigation of the proposed algorithm for the enhancement of positron imaging in clinical and preclinical applications.

Enhancing spatial resolution of 18F positron imaging with the Timepix detector by classification of primary fired pixels using support vector machine

NASA Astrophysics Data System (ADS)

Wang, Qian; Liu, Zhen; Ziegler, Sibylle I.; Shi, Kuangyu

2015-07-01

Position-sensitive positron cameras using silicon pixel detectors have been applied for some preclinical and intraoperative clinical applications. However, the spatial resolution of a positron camera is limited by positron multiple scattering in the detector. An incident positron may fire a number of successive pixels on the imaging plane. It is still impossible to capture the primary fired pixel along a particle trajectory by hardware or to perceive the pixel firing sequence by direct observation. Here, we propose a novel data-driven method to improve the spatial resolution by classifying the primary pixels within the detector using support vector machine. A classification model is constructed by learning the features of positron trajectories based on Monte-Carlo simulations using Geant4. Topological and energy features of pixels fired by 18F positrons were considered for the training and classification. After applying the classification model on measurements, the primary fired pixels of the positron tracks in the silicon detector were estimated. The method was tested and assessed for [18F]FDG imaging of an absorbing edge protocol and a leaf sample. The proposed method improved the spatial resolution from 154.6   ±   4.2 µm (energy weighted centroid approximation) to 132.3   ±   3.5 µm in the absorbing edge measurements. For the positron imaging of a leaf sample, the proposed method achieved lower root mean square error relative to phosphor plate imaging, and higher similarity with the reference optical image. The improvements of the preliminary results support further investigation of the proposed algorithm for the enhancement of positron imaging in clinical and preclinical applications.

Fifty Years of Mars Imaging: from Mariner 4 to HiRISE

NASA Image and Video Library

2017-11-20

This image from NASA's Mars Reconnaissance Orbiter (MRO) shows Mars' surface in detail. Mars has captured the imagination of astronomers for thousands of years, but it wasn't until the last half a century that we were able to capture images of its surface in detail. This particular site on Mars was first imaged in 1965 by the Mariner 4 spacecraft during the first successful fly-by mission to Mars. From an altitude of around 10,000 kilometers, this image (the ninth frame taken) achieved a resolution of approximately 1.25 kilometers per pixel. Since then, this location has been observed by six other visible cameras producing images with varying resolutions and sizes. This includes HiRISE (highlighted in yellow), which is the highest-resolution and has the smallest "footprint." This compilation, spanning Mariner 4 to HiRISE, shows each image at full-resolution. Beginning with Viking 1 and ending with our HiRISE image, this animation documents the historic imaging of a particular site on another world. In 1976, the Viking 1 orbiter began imaging Mars in unprecedented detail, and by 1980 had successfully mosaicked the planet at approximately 230 meters per pixel. In 1999, the Mars Orbiter Camera onboard the Mars Global Surveyor (1996) also imaged this site with its Wide Angle lens, at around 236 meters per pixel. This was followed by the Thermal Emission Imaging System on Mars Odyssey (2001), which also provided a visible camera producing the image we see here at 17 meters per pixel. Later in 2012, the High-Resolution Stereo Camera on the Mars Express orbiter (2003) captured this image of the surface at 25 meters per pixel. In 2010, the Context Camera on the Mars Reconnaissance Orbiter (2005) imaged this site at about 5 meters per pixel. Finally, in 2017, HiRISE acquired the highest resolution image of this location to date at 50 centimeters per pixel. When seen at this unprecedented scale, we can discern a crater floor strewn with small rocky deposits, boulders several meters across, and wind-blown deposits in the floors of small craters and depressions. This compilation of Mars images spanning over 50 years gives us a visual appreciation of the evolution of orbital Mars imaging over a single site. The map is projected here at a scale of 50 centimeters (19.7 inches) per pixel. [The original image scale is 52.2 centimeters (20.6 inches) per pixel (with 2 x 2 binning); objects on the order of 156 centimeters (61.4 inches) across are resolved.] North is up. https://photojournal.jpl.nasa.gov/catalog/PIA22115

Digital classification of Landsat data for vegetation and land-cover mapping in the Blackfoot River watershed, southeastern Idaho

USGS Publications Warehouse

Pettinger, L.R.

1982-01-01

This paper documents the procedures, results, and final products of a digital analysis of Landsat data used to produce a vegetation and landcover map of the Blackfoot River watershed in southeastern Idaho. Resource classes were identified at two levels of detail: generalized Level I classes (for example, forest land and wetland) and detailed Levels II and III classes (for example, conifer forest, aspen, wet meadow, and riparian hardwoods). Training set statistics were derived using a modified clustering approach. Environmental stratification that separated uplands from lowlands improved discrimination between resource classes having similar spectral signatures. Digital classification was performed using a maximum likelihood algorithm. Classification accuracy was determined on a single-pixel basis from a random sample of 25-pixel blocks. These blocks were transferred to small-scale color-infrared aerial photographs, and the image area corresponding to each pixel was interpreted. Classification accuracy, expressed as percent agreement of digital classification and photo-interpretation results, was 83.0:t 2.1 percent (0.95 probability level) for generalized (Level I) classes and 52.2:t 2.8 percent (0.95 probability level) for detailed (Levels II and III) classes. After the classified images were geometrically corrected, two types of maps were produced of Level I and Levels II and III resource classes: color-coded maps at a 1:250,000 scale, and flatbed-plotter overlays at a 1:24,000 scale. The overlays are more useful because of their larger scale, familiar format to users, and compatibility with other types of topographic and thematic maps of the same scale.

Graphics Processing Unit (GPU) implementation of image processing algorithms to improve system performance of the Control, Acquisition, Processing, and Image Display System (CAPIDS) of the Micro-Angiographic Fluoroscope (MAF).

PubMed

Vasan, S N Swetadri; Ionita, Ciprian N; Titus, A H; Cartwright, A N; Bednarek, D R; Rudin, S

2012-02-23

We present the image processing upgrades implemented on a Graphics Processing Unit (GPU) in the Control, Acquisition, Processing, and Image Display System (CAPIDS) for the custom Micro-Angiographic Fluoroscope (MAF) detector. Most of the image processing currently implemented in the CAPIDS system is pixel independent; that is, the operation on each pixel is the same and the operation on one does not depend upon the result from the operation on the other, allowing the entire image to be processed in parallel. GPU hardware was developed for this kind of massive parallel processing implementation. Thus for an algorithm which has a high amount of parallelism, a GPU implementation is much faster than a CPU implementation. The image processing algorithm upgrades implemented on the CAPIDS system include flat field correction, temporal filtering, image subtraction, roadmap mask generation and display window and leveling. A comparison between the previous and the upgraded version of CAPIDS has been presented, to demonstrate how the improvement is achieved. By performing the image processing on a GPU, significant improvements (with respect to timing or frame rate) have been achieved, including stable operation of the system at 30 fps during a fluoroscopy run, a DSA run, a roadmap procedure and automatic image windowing and leveling during each frame.

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Quattrochi, Dale A.

2000-01-01

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Structure-Preserving Smoothing of Biomedical Images

NASA Astrophysics Data System (ADS)

Gil, Debora; Hernàndez-Sabaté, Aura; Burnat, Mireia; Jansen, Steven; Martínez-Villalta, Jordi

Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood.

An Over 90 dB Intra-Scene Single-Exposure Dynamic Range CMOS Image Sensor Using a 3.0 μm Triple-Gain Pixel Fabricated in a Standard BSI Process.

PubMed

Takayanagi, Isao; Yoshimura, Norio; Mori, Kazuya; Matsuo, Shinichiro; Tanaka, Shunsuke; Abe, Hirofumi; Yasuda, Naoto; Ishikawa, Kenichiro; Okura, Shunsuke; Ohsawa, Shinji; Otaka, Toshinori

2018-01-12

To respond to the high demand for high dynamic range imaging suitable for moving objects with few artifacts, we have developed a single-exposure dynamic range image sensor by introducing a triple-gain pixel and a low noise dual-gain readout circuit. The developed 3 μm pixel is capable of having three conversion gains. Introducing a new split-pinned photodiode structure, linear full well reaches 40 ke - . Readout noise under the highest pixel gain condition is 1 e - with a low noise readout circuit. Merging two signals, one with high pixel gain and high analog gain, and the other with low pixel gain and low analog gain, a single exposure dynamic rage (SEHDR) signal is obtained. Using this technology, a 1/2.7", 2M-pixel CMOS image sensor has been developed and characterized. The image sensor also employs an on-chip linearization function, yielding a 16-bit linear signal at 60 fps, and an intra-scene dynamic range of higher than 90 dB was successfully demonstrated. This SEHDR approach inherently mitigates the artifacts from moving objects or time-varying light sources that can appear in the multiple exposure high dynamic range (MEHDR) approach.

An Over 90 dB Intra-Scene Single-Exposure Dynamic Range CMOS Image Sensor Using a 3.0 μm Triple-Gain Pixel Fabricated in a Standard BSI Process †

PubMed Central

Takayanagi, Isao; Yoshimura, Norio; Mori, Kazuya; Matsuo, Shinichiro; Tanaka, Shunsuke; Abe, Hirofumi; Yasuda, Naoto; Ishikawa, Kenichiro; Okura, Shunsuke; Ohsawa, Shinji; Otaka, Toshinori

2018-01-01

To respond to the high demand for high dynamic range imaging suitable for moving objects with few artifacts, we have developed a single-exposure dynamic range image sensor by introducing a triple-gain pixel and a low noise dual-gain readout circuit. The developed 3 μm pixel is capable of having three conversion gains. Introducing a new split-pinned photodiode structure, linear full well reaches 40 ke−. Readout noise under the highest pixel gain condition is 1 e− with a low noise readout circuit. Merging two signals, one with high pixel gain and high analog gain, and the other with low pixel gain and low analog gain, a single exposure dynamic rage (SEHDR) signal is obtained. Using this technology, a 1/2.7”, 2M-pixel CMOS image sensor has been developed and characterized. The image sensor also employs an on-chip linearization function, yielding a 16-bit linear signal at 60 fps, and an intra-scene dynamic range of higher than 90 dB was successfully demonstrated. This SEHDR approach inherently mitigates the artifacts from moving objects or time-varying light sources that can appear in the multiple exposure high dynamic range (MEHDR) approach. PMID:29329210

Dead pixel replacement in LWIR microgrid polarimeters.

PubMed

Ratliff, Bradley M; Tyo, J Scott; Boger, James K; Black, Wiley T; Bowers, David L; Fetrow, Matthew P

2007-06-11

LWIR imaging arrays are often affected by nonresponsive pixels, or "dead pixels." These dead pixels can severely degrade the quality of imagery and often have to be replaced before subsequent image processing and display of the imagery data. For LWIR arrays that are integrated with arrays of micropolarizers, the problem of dead pixels is amplified. Conventional dead pixel replacement (DPR) strategies cannot be employed since neighboring pixels are of different polarizations. In this paper we present two DPR schemes. The first is a modified nearest-neighbor replacement method. The second is a method based on redundancy in the polarization measurements.We find that the redundancy-based DPR scheme provides an order-of-magnitude better performance for typical LWIR polarimetric data.

Backside illuminated CMOS-TDI line scanner for space applications

NASA Astrophysics Data System (ADS)

Cohen, O.; Ben-Ari, N.; Nevo, I.; Shiloah, N.; Zohar, G.; Kahanov, E.; Brumer, M.; Gershon, G.; Ofer, O.

2017-09-01

A new multi-spectral line scanner CMOS image sensor is reported. The backside illuminated (BSI) image sensor was designed for continuous scanning Low Earth Orbit (LEO) space applications including A custom high quality CMOS Active Pixels, Time Delayed Integration (TDI) mechanism that increases the SNR, 2-phase exposure mechanism that increases the dynamic Modulation Transfer Function (MTF), very low power internal Analog to Digital Converters (ADC) with resolution of 12 bit per pixel and on chip controller. The sensor has 4 independent arrays of pixels where each array is arranged in 2600 TDI columns with controllable TDI depth from 8 up to 64 TDI levels. A multispectral optical filter with specific spectral response per array is assembled at the package level. In this paper we briefly describe the sensor design and present some electrical and electro-optical recent measurements of the first prototypes including high Quantum Efficiency (QE), high MTF, wide range selectable Full Well Capacity (FWC), excellent linearity of approximately 1.3% in a signal range of 5-85% and approximately 1.75% in a signal range of 2-95% out of the signal span, readout noise of approximately 95 electrons with 64 TDI levels, negligible dark current and power consumption of less than 1.5W total for 4 bands sensor at all operation conditions .

Simulation approach for the evaluation of tracking accuracy in radiotherapy: a preliminary study.

PubMed

Tanaka, Rie; Ichikawa, Katsuhiro; Mori, Shinichiro; Sanada, Sigeru

2013-01-01

Real-time tumor tracking in external radiotherapy can be achieved by diagnostic (kV) X-ray imaging with a dynamic flat-panel detector (FPD). It is important to keep the patient dose as low as possible while maintaining tracking accuracy. A simulation approach would be helpful to optimize the imaging conditions. This study was performed to develop a computer simulation platform based on a noise property of the imaging system for the evaluation of tracking accuracy at any noise level. Flat-field images were obtained using a direct-type dynamic FPD, and noise power spectrum (NPS) analysis was performed. The relationship between incident quantum number and pixel value was addressed, and a conversion function was created. The pixel values were converted into a map of quantum number using the conversion function, and the map was then input into the random number generator to simulate image noise. Simulation images were provided at different noise levels by changing the incident quantum numbers. Subsequently, an implanted marker was tracked automatically and the maximum tracking errors were calculated at different noise levels. The results indicated that the maximum tracking error increased with decreasing incident quantum number in flat-field images with an implanted marker. In addition, the range of errors increased with decreasing incident quantum number. The present method could be used to determine the relationship between image noise and tracking accuracy. The results indicated that the simulation approach would aid in determining exposure dose conditions according to the necessary tracking accuracy.

Variational optical flow estimation for images with spectral and photometric sensor diversity

NASA Astrophysics Data System (ADS)

Bengtsson, Tomas; McKelvey, Tomas; Lindström, Konstantin

2015-03-01

Motion estimation of objects in image sequences is an essential computer vision task. To this end, optical flow methods compute pixel-level motion, with the purpose of providing low-level input to higher-level algorithms and applications. Robust flow estimation is crucial for the success of applications, which in turn depends on the quality of the captured image data. This work explores the use of sensor diversity in the image data within a framework for variational optical flow. In particular, a custom image sensor setup intended for vehicle applications is tested. Experimental results demonstrate the improved flow estimation performance when IR sensitivity or flash illumination is added to the system.

A 20 Mfps high frame-depth CMOS burst-mode imager with low power in-pixel NMOS-only passive amplifier

NASA Astrophysics Data System (ADS)

Wu, L.; San Segundo Bello, D.; Coppejans, P.; Craninckx, J.; Wambacq, P.; Borremans, J.

2017-02-01

This paper presents a 20 Mfps 32 × 84 pixels CMOS burst-mode imager featuring high frame depth with a passive in-pixel amplifier. Compared to the CCD alternatives, CMOS burst-mode imagers are attractive for their low power consumption and integration of circuitry such as ADCs. Due to storage capacitor size and its noise limitations, CMOS burst-mode imagers usually suffer from a lower frame depth than CCD implementations. In order to capture fast transitions over a longer time span, an in-pixel CDS technique has been adopted to reduce the required memory cells for each frame by half. Moreover, integrated with in-pixel CDS, an in-pixel NMOS-only passive amplifier alleviates the kTC noise requirements of the memory bank allowing the usage of smaller capacitors. Specifically, a dense 108-cell MOS memory bank (10fF/cell) has been implemented inside a 30μm pitch pixel, with an area of 25 × 30μm2 occupied by the memory bank. There is an improvement of about 4x in terms of frame depth per pixel area by applying in-pixel CDS and amplification. With the amplifier's gain of 3.3, an FD input-referred RMS noise of 1mV is achieved at 20 Mfps operation. While the amplification is done without burning DC current, including the pixel source follower biasing, the full pixel consumes 10μA at 3.3V supply voltage at full speed. The chip has been fabricated in imec's 130nm CMOS CIS technology.

Characterization of a hybrid energy-resolving photon-counting detector

NASA Astrophysics Data System (ADS)

Zang, A.; Pelzer, G.; Anton, G.; Ballabriga Sune, R.; Bisello, F.; Campbell, M.; Fauler, A.; Fiederle, M.; Llopart Cudie, X.; Ritter, I.; Tennert, F.; Wölfel, S.; Wong, W. S.; Michel, T.

2014-03-01

Photon-counting detectors in medical x-ray imaging provide a higher dose efficiency than integrating detectors. Even further possibilities for imaging applications arise, if the energy of each photon counted is measured, as for example K-edge-imaging or optimizing image quality by applying energy weighting factors. In this contribution, we show results of the characterization of the Dosepix detector. This hybrid photon- counting pixel detector allows energy resolved measurements with a novel concept of energy binning included in the pixel electronics. Based on ideas of the Medipix detector family, it provides three different modes of operation: An integration mode, a photon-counting mode, and an energy-binning mode. In energy-binning mode, it is possible to set 16 energy thresholds in each pixel individually to derive a binned energy spectrum in every pixel in one acquisition. The hybrid setup allows using different sensor materials. For the measurements 300 μm Si and 1 mm CdTe were used. The detector matrix consists of 16 x 16 square pixels for CdTe (16 x 12 for Si) with a pixel pitch of 220 μm. The Dosepix was originally intended for applications in the field of radiation measurement. Therefore it is not optimized towards medical imaging. The detector concept itself still promises potential as an imaging detector. We present spectra measured in one single pixel as well as in the whole pixel matrix in energy-binning mode with a conventional x-ray tube. In addition, results concerning the count rate linearity for the different sensor materials are shown as well as measurements regarding energy resolution.

Camouflaging in Digital Image for Secure Communication

NASA Astrophysics Data System (ADS)

Jindal, B.; Singh, A. P.

2013-06-01

The present paper reports on a new type of camouflaging in digital image for hiding crypto-data using moderate bit alteration in the pixel. In the proposed method, cryptography is combined with steganography to provide a two layer security to the hidden data. The novelty of the algorithm proposed in the present work lies in the fact that the information about hidden bit is reflected by parity condition in one part of the image pixel. The remaining part of the image pixel is used to perform local pixel adjustment to improve the visual perception of the cover image. In order to examine the effectiveness of the proposed method, image quality measuring parameters are computed. In addition to this, security analysis is also carried by comparing the histograms of cover and stego images. This scheme provides a higher security as well as robustness to intentional as well as unintentional attacks.

Coloured computational imaging with single-pixel detectors based on a 2D discrete cosine transform

NASA Astrophysics Data System (ADS)

Liu, Bao-Lei; Yang, Zhao-Hua; Liu, Xia; Wu, Ling-An

2017-02-01

We propose and demonstrate a computational imaging technique that uses structured illumination based on a two-dimensional discrete cosine transform to perform imaging with a single-pixel detector. A scene is illuminated by a projector with two sets of orthogonal patterns, then by applying an inverse cosine transform to the spectra obtained from the single-pixel detector a full-colour image is retrieved. This technique can retrieve an image from sub-Nyquist measurements, and the background noise is easily cancelled to give excellent image quality. Moreover, the experimental set-up is very simple.

Some advances/results in monitoring road cracks from 2D pavement images within the scope of the collaborative FP7 TRIMM project

NASA Astrophysics Data System (ADS)

Baltazart, Vincent; Moliard, Jean-Marc; Amhaz, Rabih; Wright, Dean; Jethwa, Manish

2015-04-01

Monitoring road surface conditions is an important issue in many countries. Several projects have looked into this issue in recent years, including TRIMM 2011-2014. The objective of such projects has been to detect surface distresses, like cracking, raveling and water ponding, in order to plan effective road maintenance and to afford a better sustainability of the pavement. The monitoring of cracking conventionally focuses on open cracks on the surface of the pavement, as opposed to reflexive cracks embedded in the pavement materials. For monitoring surface condition, in situ human visual inspection has been gradually replaced by automatic image data collection at traffic speed. Off-line image processing techniques have been developed for monitoring surface condition in support of human visual control. Full automation of crack monitoring has been approached with caution, and depends on a proper manual assessment of the performance. This work firstly presents some aspects of the current state of monitoring that have been reported so far in the literature and in previous projects: imaging technology and image processing techniques. Then, the work presents the two image processing techniques that have been developed within the scope of the TRIMM project to automatically detect pavement cracking from images. The first technique is a heuristic approach (HA) based on the search for gradient within the image. It was originally developed to process pavement images from the French imaging device, Aigle-RN. The second technique, the Minimal Path Selection (MPS) method, has been developed within an ongoing PhD work at IFSTTAR. The proposed new technique provides a fine and accurate segmentation of the crack pattern along with the estimation of the crack width. HA has been assessed against the field data collection provided by Yotta and TRL with the imaging device Tempest 2. The performance assessment has been threefold: first it was performed against the reference data set including 130 km of pavement images over UK roads, second over a few selected short sections of contiguous pavement images, and finally over a few sample images as a case study. The performance of MPS has been assessed against an older image data base. Pixel-based PGT was available to provide the most sensitive performance assessment. MPS has shown its ability to provide a very accurate cracking pattern without reducing the image resolution on the segmented images. Thus, it allows measurement of the crack width; it is found to behave more robustly against the image texture and better matched for dealing with low contrast pavement images. The benchmarking of seven automatic segmentation techniques has been provided at both the pixel and the grid levels. The performance assessment includes three minimal path selection algorithms, namely MPS, Free Form Anisotropy (FFA), one geodesic contour with automatic selection of points of interests (GC-POI), HA, and two Markov-based methods. Among others, MPS approach reached the best performance at the pixel level while it is matched to the FFA approach at the grid level. Finally, the project has emphasized the need for a reliable ground truth data collection. Owing to its accuracy, MPS may serve as a reference benchmark for other methods to provide the automatic segmentation of pavement images at the pixel level and beyond. As a counterpart, MPS requires a reduction in the computing time. Keywords: cracking, automatic segmentation, image processing, pavement, surface distress, monitoring, DICE, performance

Anomaly clustering in hyperspectral images

NASA Astrophysics Data System (ADS)

Doster, Timothy J.; Ross, David S.; Messinger, David W.; Basener, William F.

2009-05-01

The topological anomaly detection algorithm (TAD) differs from other anomaly detection algorithms in that it uses a topological/graph-theoretic model for the image background instead of modeling the image with a Gaussian normal distribution. In the construction of the model, TAD produces a hard threshold separating anomalous pixels from background in the image. We build on this feature of TAD by extending the algorithm so that it gives a measure of the number of anomalous objects, rather than the number of anomalous pixels, in a hyperspectral image. This is done by identifying, and integrating, clusters of anomalous pixels via a graph theoretical method combining spatial and spectral information. The method is applied to a cluttered HyMap image and combines small groups of pixels containing like materials, such as those corresponding to rooftops and cars, into individual clusters. This improves visualization and interpretation of objects.

A new algorithm to reduce noise in microscopy images implemented with a simple program in python.

PubMed

Papini, Alessio

2012-03-01

All microscopical images contain noise, increasing when (e.g., transmission electron microscope or light microscope) approaching the resolution limit. Many methods are available to reduce noise. One of the most commonly used is image averaging. We propose here to use the mode of pixel values. Simple Python programs process a given number of images, recorded consecutively from the same subject. The programs calculate the mode of the pixel values in a given position (a, b). The result is a new image containing in (a, b) the mode of the values. Therefore, the final pixel value corresponds to that read in at least two of the pixels in position (a, b). The application of the program on a set of images obtained by applying salt and pepper noise and GIMP hurl noise with 10-90% standard deviation showed that the mode performs better than averaging with three-eight images. The data suggest that the mode would be more efficient (in the sense of a lower number of recorded images to process to reduce noise below a given limit) for lower number of total noisy pixels and high standard deviation (as impulse noise and salt and pepper noise), while averaging would be more efficient when the number of varying pixels is high, and the standard deviation is low, as in many cases of Gaussian noise affected images. The two methods may be used serially. Copyright © 2011 Wiley Periodicals, Inc.

Image analysis methods for assessing levels of image plane nonuniformity and stochastic noise in a magnetic resonance image of a homogeneous phantom.

PubMed

Magnusson, P; Olsson, L E

2000-08-01

Magnetic response image plane nonuniformity and stochastic noise are properties that greatly influence the outcome of quantitative magnetic resonance imaging (MRI) evaluations such as gel dosimetry measurements using MRI. To study these properties, robust and accurate image analysis methods are required. New nonuniformity level assessment methods were designed, since previous methods were found to be insufficiently robust and accurate. The new and previously reported nonuniformity level assessment methods were analyzed with respect to, for example, insensitivity to stochastic noise; and previously reported stochastic noise level assessment methods with respect to insensitivity to nonuniformity. Using the same image data, different methods were found to assess significantly different levels of nonuniformity. Nonuniformity levels obtained using methods that count pixels in an intensity interval, and obtained using methods that use only intensity values, were found not to be comparable. The latter were found preferable, since they assess the quantity intrinsically sought. A new method which calculates a deviation image, with every pixel representing the deviation from a reference intensity, was least sensitive to stochastic noise. Furthermore, unlike any other analyzed method, it includes all intensity variations across the phantom area and allows for studies of nonuniformity shapes. This new method was designed for accurate studies of nonuniformities in gel dosimetry measurements, but could also be used with benefit in quality assurance and acceptance testing of MRI, scintillation camera, and computer tomography systems. The stochastic noise level was found to be greatly method dependent. Two methods were found to be insensitive to nonuniformity and also simple to use in practice. One method assesses the stochastic noise level as the average of the levels at five different positions within the phantom area, and the other assesses the stochastic noise in a region outside the phantom area.

Megapixel mythology and photospace: estimating photospace for camera phones from large image sets

NASA Astrophysics Data System (ADS)

Hultgren, Bror O.; Hertel, Dirk W.

2008-01-01

It is a myth that more pixels alone result in better images. The marketing of camera phones in particular has focused on their pixel numbers. However, their performance varies considerably according to the conditions of image capture. Camera phones are often used in low-light situations where the lack of a flash and limited exposure time will produce underexposed, noisy and blurred images. Camera utilization can be quantitatively described by photospace distributions, a statistical description of the frequency of pictures taken at varying light levels and camera-subject distances. If the photospace distribution is known, the user-experienced distribution of quality can be determined either directly by direct measurement of subjective quality, or by photospace-weighting of objective attributes. The population of a photospace distribution requires examining large numbers of images taken under typical camera phone usage conditions. ImagePhi was developed as a user-friendly software tool to interactively estimate the primary photospace variables, subject illumination and subject distance, from individual images. Additionally, subjective evaluations of image quality and failure modes for low quality images can be entered into ImagePhi. ImagePhi has been applied to sets of images taken by typical users with a selection of popular camera phones varying in resolution. The estimated photospace distribution of camera phone usage has been correlated with the distributions of failure modes. The subjective and objective data show that photospace conditions have a much bigger impact on image quality of a camera phone than the pixel count of its imager. The 'megapixel myth' is thus seen to be less a myth than an ill framed conditional assertion, whose conditions are to a large extent specified by the camera's operational state in photospace.

A low-noise wide-dynamic-range event-driven detector using SOI pixel technology for high-energy particle imaging

NASA Astrophysics Data System (ADS)

Shrestha, Sumeet; Kamehama, Hiroki; Kawahito, Shoji; Yasutomi, Keita; Kagawa, Keiichiro; Takeda, Ayaki; Tsuru, Takeshi Go; Arai, Yasuo

2015-08-01

This paper presents a low-noise wide-dynamic-range pixel design for a high-energy particle detector in astronomical applications. A silicon on insulator (SOI) based detector is used for the detection of wide energy range of high energy particles (mainly for X-ray). The sensor has a thin layer of SOI CMOS readout circuitry and a thick layer of high-resistivity detector vertically stacked in a single chip. Pixel circuits are divided into two parts; signal sensing circuit and event detection circuit. The event detection circuit consisting of a comparator and logic circuits which detect the incidence of high energy particle categorizes the incident photon it into two energy groups using an appropriate energy threshold and generate a two-bit code for an event and energy level. The code for energy level is then used for selection of the gain of the in-pixel amplifier for the detected signal, providing a function of high-dynamic-range signal measurement. The two-bit code for the event and energy level is scanned in the event scanning block and the signals from the hit pixels only are read out. The variable-gain in-pixel amplifier uses a continuous integrator and integration-time control for the variable gain. The proposed design allows the small signal detection and wide dynamic range due to the adaptive gain technique and capability of correlated double sampling (CDS) technique of kTC noise canceling of the charge detector.

The Effects of Radiation on Imagery Sensors in Space

NASA Technical Reports Server (NTRS)

Mathis, Dylan

2007-01-01

Recent experience using high definition video on the International Space Station reveals camera pixel degradation due to particle radiation to be a much more significant problem with high definition cameras than with standard definition video. Although it may at first appear that increased pixel density on the imager is the logical explanation for this, the ISS implementations of high definition suggest a more complex causal and mediating factor mix. The degree of damage seems to vary from one type of camera to another, and this variation prompts a reconsideration of the possible factors in pixel loss, such as imager size, number of pixels, pixel aperture ratio, imager type (CCD or CMOS), method of error correction/concealment, and the method of compression used for recording or transmission. The problem of imager pixel loss due to particle radiation is not limited to out-of-atmosphere applications. Since particle radiation increases with altitude, it is not surprising to find anecdotal evidence that video cameras subject to many hours of airline travel show an increased incidence of pixel loss. This is even evident in some standard definition video applications, and pixel loss due to particle radiation only stands to become a more salient issue considering the continued diffusion of high definition video cameras in the marketplace.

320 x 240 uncooled IRFPA with pixel wise thin film vacuum packaging

NASA Astrophysics Data System (ADS)

Yon, J.-J.; Dumont, G.; Rabaud, W.; Becker, S.; Carle, L.; Goudon, V.; Vialle, C.; Hamelin, A.; Arnaud, A.

2012-10-01

Silicon based vacuum packaging is a key enabling technology for achieving affordable uncooled Infrared Focal Plane Arrays (IRFPA) as required by the promising mass market for very low cost IR applications, such as automotive driving assistance, energy loss monitoring in buildings, motion sensors… Among the various approaches studied worldwide, the CEA, LETI is developing a unique technology where each bolometer pixel is sealed under vacuum at the wafer level, using an IR transparent thin film deposition. This technology referred to as PLP (Pixel Level Packaging), leads to an array of hermetic micro-caps each containing a single microbolometer. Since the successful demonstration that the PLP technology, when applied on a single microbolometer pixel, can provide the required vacuum < 10-3 mbar, the authors have pushed forward the development of the technology on fully operational QVGA readout circuits CMOS base wafers (320 x 240 pixels). In this outlook, the article reports on the electro optical performance obtained from this preliminary PLP based QVGA demonstrator. Apart from the response, noise and NETD distributions, the paper also puts emphasis on additional key features such as thermal time constant, image quality, and ageing properties.

Segmentation via fusion of edge and needle map

NASA Astrophysics Data System (ADS)

Ahn, Hong-Young; Tou, Julius T.

1991-03-01

This paper presents an integrated image segmentation method using edge and needle map which compensates deficiencies of using either edge-based approach or region-based approach. Segmentation of an image is the first and most difficult step toward symbolic transformation of a raw image, which is essential in image understanding. In industrial applications, the task is further complicated by the ubiquitous presence of specularity in most industrial parts. Three images taken from three different illumination directions were used to separate specular and Lambertian components in the images. Needle map is generated from Lambertian component images using photometric stereo technique. In one channel, edges are extracted and linked from the averaged Lambertian images providing one source of segmentation. The other channel, Gaussian curvature and mean curvature values are estimated at each pixel from least square local surface fit of needle map. Labeled surface type image is then generated using the signs of Gaussian and mean curvatures, where one of ten surface types is assigned to each pixel. Connected regions of identical surface type pixels provide the first level grouping, a rough initial segmentation. Edge information and initial segmentation of surface type are fed to an integration module which interprets the edges and regions in a consistent way. During interpretation regions are merged or split, edges are discarded or generated depending upon global surface fit error and consistency with neighboring regions. The output of integrated segmentation is an explicit description of surface type and contours of each region which facilitates recognition, localization and attitude determination of objects in the image.

Image reconstruction of dynamic infrared single-pixel imaging system

NASA Astrophysics Data System (ADS)

Tong, Qi; Jiang, Yilin; Wang, Haiyan; Guo, Limin

2018-03-01

Single-pixel imaging technique has recently received much attention. Most of the current single-pixel imaging is aimed at relatively static targets or the imaging system is fixed, which is limited by the number of measurements received through the single detector. In this paper, we proposed a novel dynamic compressive imaging method to solve the imaging problem, where exists imaging system motion behavior, for the infrared (IR) rosette scanning system. The relationship between adjacent target images and scene is analyzed under different system movement scenarios. These relationships are used to build dynamic compressive imaging models. Simulation results demonstrate that the proposed method can improve the reconstruction quality of IR image and enhance the contrast between the target and the background in the presence of system movement.

The progress of sub-pixel imaging methods

NASA Astrophysics Data System (ADS)

Wang, Hu; Wen, Desheng

2014-02-01

This paper reviews the Sub-pixel imaging technology principles, characteristics, the current development status at home and abroad and the latest research developments. As Sub-pixel imaging technology has achieved the advantages of high resolution of optical remote sensor, flexible working ways and being miniaturized with no moving parts. The imaging system is suitable for the application of space remote sensor. Its application prospect is very extensive. It is quite possible to be the research development direction of future space optical remote sensing technology.

Optimal Compression of Floating-Point Astronomical Images Without Significant Loss of Information

NASA Technical Reports Server (NTRS)

Pence, William D.; White, R. L.; Seaman, R.

2010-01-01

We describe a compression method for floating-point astronomical images that gives compression ratios of 6 - 10 while still preserving the scientifically important information in the image. The pixel values are first preprocessed by quantizing them into scaled integer intensity levels, which removes some of the uncompressible noise in the image. The integers are then losslessly compressed using the fast and efficient Rice algorithm and stored in a portable FITS format file. Quantizing an image more coarsely gives greater image compression, but it also increases the noise and degrades the precision of the photometric and astrometric measurements in the quantized image. Dithering the pixel values during the quantization process greatly improves the precision of measurements in the more coarsely quantized images. We perform a series of experiments on both synthetic and real astronomical CCD images to quantitatively demonstrate that the magnitudes and positions of stars in the quantized images can be measured with the predicted amount of precision. In order to encourage wider use of these image compression methods, we have made available a pair of general-purpose image compression programs, called fpack and funpack, which can be used to compress any FITS format image.

Model of Image Artifacts from Dust Particles

NASA Technical Reports Server (NTRS)

Willson, Reg

2008-01-01

A mathematical model of image artifacts produced by dust particles on lenses has been derived. Machine-vision systems often have to work with camera lenses that become dusty during use. Dust particles on the front surface of a lens produce image artifacts that can potentially affect the performance of a machine-vision algorithm. The present model satisfies a need for a means of synthesizing dust image artifacts for testing machine-vision algorithms for robustness (or the lack thereof) in the presence of dust on lenses. A dust particle can absorb light or scatter light out of some pixels, thereby giving rise to a dark dust artifact. It can also scatter light into other pixels, thereby giving rise to a bright dust artifact. For the sake of simplicity, this model deals only with dark dust artifacts. The model effectively represents dark dust artifacts as an attenuation image consisting of an array of diffuse darkened spots centered at image locations corresponding to the locations of dust particles. The dust artifacts are computationally incorporated into a given test image by simply multiplying the brightness value of each pixel by a transmission factor that incorporates the factor of attenuation, by dust particles, of the light incident on that pixel. With respect to computation of the attenuation and transmission factors, the model is based on a first-order geometric (ray)-optics treatment of the shadows cast by dust particles on the image detector. In this model, the light collected by a pixel is deemed to be confined to a pair of cones defined by the location of the pixel s image in object space, the entrance pupil of the lens, and the location of the pixel in the image plane (see Figure 1). For simplicity, it is assumed that the size of a dust particle is somewhat less than the diameter, at the front surface of the lens, of any collection cone containing all or part of that dust particle. Under this assumption, the shape of any individual dust particle artifact is the shape (typically, circular) of the aperture, and the contribution of the particle to the attenuation factor for a given pixel is the fraction of the cross-sectional area of the collection cone occupied by the particle. Assuming that dust particles do not overlap, the net transmission factor for a given pixel is calculated as one minus the sum of attenuation factors contributed by all dust particles affecting that pixel. In a test, the model was used to synthesize attenuation images for random distributions of dust particles on the front surface of a lens at various relative aperture (F-number) settings. As shown in Figure 2, the attenuation images resembled dust artifacts in real test images recorded while the lens was aimed at a white target.

A New Framework of Removing Salt and Pepper Impulse Noise for the Noisy Image Including Many Noise-Free White and Black Pixels

NASA Astrophysics Data System (ADS)

Li, Song; Wang, Caizhu; Li, Yeqiu; Wang, Ling; Sakata, Shiro; Sekiya, Hiroo; Kuroiwa, Shingo

In this paper, we propose a new framework of removing salt and pepper impulse noise. In our proposed framework, the most important point is that the number of noise-free white and black pixels in a noisy image can be determined by using the noise rates estimated by Fuzzy Impulse Noise Detection and Reduction Method (FINDRM) and Efficient Detail-Preserving Approach (EDPA). For the noisy image includes many noise-free white and black pixels, the detected noisy pixel from the FINDRM is re-checked by using the alpha-trimmed mean. Finally, the impulse noise filtering phase of the FINDRM is used to restore the image. Simulation results show that for the noisy image including many noise-free white and black pixels, the proposed framework can decrease the False Hit Rate (FHR) efficiently compared with the FINDRM. Therefore, the proposed framework can be used more widely than the FINDRM.

High Dynamic Range Imaging at the Quantum Limit with Single Photon Avalanche Diode-Based Image Sensors †

PubMed Central

Mattioli Della Rocca, Francescopaolo

2018-01-01

This paper examines methods to best exploit the High Dynamic Range (HDR) of the single photon avalanche diode (SPAD) in a high fill-factor HDR photon counting pixel that is scalable to megapixel arrays. The proposed method combines multi-exposure HDR with temporal oversampling in-pixel. We present a silicon demonstration IC with 96 × 40 array of 8.25 µm pitch 66% fill-factor SPAD-based pixels achieving >100 dB dynamic range with 3 back-to-back exposures (short, mid, long). Each pixel sums 15 bit-planes or binary field images internally to constitute one frame providing 3.75× data compression, hence the 1k frames per second (FPS) output off-chip represents 45,000 individual field images per second on chip. Two future projections of this work are described: scaling SPAD-based image sensors to HDR 1 MPixel formats and shrinking the pixel pitch to 1–3 µm. PMID:29641479

Quantitative Ultrasound Imaging Using Acoustic Backscatter Coefficients.

NASA Astrophysics Data System (ADS)

Boote, Evan Jeffery

Current clinical ultrasound scanners render images which have brightness levels related to the degree of backscattered energy from the tissue being imaged. These images offer the interpreter a qualitative impression of the scattering characteristics of the tissue being examined, but due to the complex factors which affect the amplitude and character of the echoed acoustic energy, it is difficult to make quantitative assessments of scattering nature of the tissue, and thus, difficult to make precise diagnosis when subtle disease effects are present. In this dissertation, a method of data reduction for determining acoustic backscatter coefficients is adapted for use in forming quantitative ultrasound images of this parameter. In these images, the brightness level of an individual pixel corresponds to the backscatter coefficient determined for the spatial position represented by that pixel. The data reduction method utilized rigorously accounts for extraneous factors which affect the scattered echo waveform and has been demonstrated to accurately determine backscatter coefficients under a wide range of conditions. The algorithms and procedures used to form backscatter coefficient images are described. These were tested using tissue-mimicking phantoms which have regions of varying scattering levels. Another phantom has a fat-mimicking layer for testing these techniques under more clinically relevant conditions. Backscatter coefficient images were also formed of in vitro human liver tissue. A clinical ultrasound scanner has been adapted for use as a backscatter coefficient imaging platform. The digital interface between the scanner and the computer used for data reduction are described. Initial tests, using phantoms are presented. A study of backscatter coefficient imaging of in vivo liver was performed using several normal, healthy human subjects.

Facial recognition using enhanced pixelized image for simulated visual prosthesis.

PubMed

Li, Ruonan; Zhhang, Xudong; Zhang, Hui; Hu, Guanshu

2005-01-01

A simulated face recognition experiment using enhanced pixelized images is designed and performed for the artificial visual prosthesis. The results of the simulation reveal new characteristics of visual performance in an enhanced pixelization condition, and then new suggestions on the future design of visual prosthesis are provided.

An approach to integrate the human vision psychology and perception knowledge into image enhancement

NASA Astrophysics Data System (ADS)

Wang, Hui; Huang, Xifeng; Ping, Jiang

2009-07-01

Image enhancement is very important image preprocessing technology especially when the image is captured in the poor imaging condition or dealing with the high bits image. The benefactor of image enhancement either may be a human observer or a computer vision process performing some kind of higher-level image analysis, such as target detection or scene understanding. One of the main objects of the image enhancement is getting a high dynamic range image and a high contrast degree image for human perception or interpretation. So, it is very necessary to integrate either empirical or statistical human vision psychology and perception knowledge into image enhancement. The human vision psychology and perception claims that humans' perception and response to the intensity fluctuation δu of visual signals are weighted by the background stimulus u, instead of being plainly uniform. There are three main laws: Weber's law, Weber- Fechner's law and Stevens's Law that describe this phenomenon in the psychology and psychophysics. This paper will integrate these three laws of the human vision psychology and perception into a very popular image enhancement algorithm named Adaptive Plateau Equalization (APE). The experiments were done on the high bits star image captured in night scene and the infrared-red image both the static image and the video stream. For the jitter problem in the video stream, this algorithm reduces this problem using the difference between the current frame's plateau value and the previous frame's plateau value to correct the current frame's plateau value. Considering the random noise impacts, the pixel value mapping process is not only depending on the current pixel but the pixels in the window surround the current pixel. The window size is usually 3×3. The process results of this improved algorithms is evaluated by the entropy analysis and visual perception analysis. The experiments' result showed the improved APE algorithms improved the quality of the image, the target and the surrounding assistant targets could be identified easily, and the noise was not amplified much. For the low quality image, these improved algorithms augment the information entropy and improve the image and the video stream aesthetic quality, while for the high quality image they will not debase the quality of the image.

SU-E-I-09: The Impact of X-Ray Scattering On Image Noise for Dedicated Breast CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, K; Gazi, P; Boone, J

2015-06-15

Purpose: To quantify the impact of detected x-ray scatter on image noise in flat panel based dedicated breast CT systems and to determine the optimal scanning geometry given practical trade-offs between radiation dose and scatter reduction. Methods: Four different uniform polyethylene cylinders (104, 131, 156, and 184 mm in diameter) were scanned as the phantoms on a dedicated breast CT scanner developed in our laboratory. Both stationary projection imaging and rotational cone-beam CT imaging was performed. For each acquisition type, three different x-ray beam collimations were used (12, 24, and 109 mm measured at isocenter). The aim was to quantifymore » image noise properties (pixel variance, SNR, and image NPS) under different levels of x-ray scatter, in order to optimize the scanning geometry. For both projection images and reconstructed CT images, individual pixel variance and NPS were determined and compared. Noise measurement from the CT images were also performed with different detector binning modes and reconstruction matrix sizes. Noise propagation was also tracked throughout the intermediate steps of cone-beam CT reconstruction, including the inverse-logarithmic process, Fourier-filtering before backprojection. Results: Image noise was lower in the presence of higher scatter levels. For the 184 mm polyethylene phantom, the image noise (measured in pixel variance) was ∼30% lower with full cone-beam acquisition compared to a narrow (12 mm) fan-beam acquisition. This trend is consistent across all phantom sizes and throughout all steps of CT image reconstruction. Conclusion: From purely a noise perspective, the cone-beam geometry (i.e. the full cone-angle acquisition) produces lower image noise compared to the lower-scatter fan-beam acquisition for breast CT. While these results are relevant in homogeneous phantoms, the full impact of scatter on noise in bCT should involve contrast-to-noise-ratio measurements in heterogeneous phantoms if the goal is to optimize the scanning geometry for dedicated breast CT. This work was supported by a grant from the National Institute for Biomedical Imaging and Bioengineering (R01 EB002138)« less

Pixel Stability in the Hubble Space Telescope WFC3/UVIS Detector

NASA Astrophysics Data System (ADS)

Bourque, Matthew; Baggett, Sylvia M.; Borncamp, David; Desjardins, Tyler D.; Grogin, Norman A.; Wide Field Camera 3 Team

2018-06-01

The Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) Ultraviolet-Visible (UVIS) detector has acquired roughly 12,000 dark images since the installation of WFC3 in 2009, as part of a daily monitoring program to measure the instrinsic dark current of the detector. These images have been reconfigured into 'pixel history' images in which detector columns are extracted from each dark and placed into a new time-ordered array, allowing for efficient analysis of a given pixel's behavior over time. We discuss how we measure each pixel's stability, as well as plans for a new Data Quality (DQ) flag to be introduced in a future release of the WFC3 calibration pipeline (CALWF3) for flagging pixels that are deemed unstable.

Implementation of a watershed algorithm on FPGAs

NASA Astrophysics Data System (ADS)

Zahirazami, Shahram; Akil, Mohamed

1998-10-01

In this article we present an implementation of a watershed algorithm on a multi-FPGA architecture. This implementation is based on an hierarchical FIFO. A separate FIFO for each gray level. The gray scale value of a pixel is taken for the altitude of the point. In this way we look at the image as a relief. We proceed by a flooding step. It's like as we immerse the relief in a lake. The water begins to come up and when the water of two different catchment basins reach each other, we will construct a separator or a `Watershed'. This approach is data dependent, hence the process time is different for different images. The H-FIFO is used to guarantee the nature of immersion, it means that we need two types of priority. All the points of an altitude `n' are processed before any point of altitude `n + 1'. And inside an altitude water propagates with a constant velocity in all directions from the source. This operator needs two images as input. An original image or it's gradient and the marker image. A classic way to construct the marker image is to build an image of minimal regions. Each minimal region has it's unique label. This label is the color of the water and will be used to see whether two different water touch each other. The algorithm at first fill the hierarchy FIFO with neighbors of all the regions who are not colored. Next it fetches the first pixel from the first non-empty FIFO and treats this pixel. This pixel will take the color of its neighbor, and all the neighbors who are not already in the H-FIFO are put in their correspondent FIFO. The process is over when the H-FIFO is empty. The result is a segmented and labeled image.

Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

NASA Astrophysics Data System (ADS)

Champion, Nicolas

2016-06-01

Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pléiades-HR images and our first experiments show the feasibility to automate the detection of shadows and clouds in satellite image sequences.

Lagrange constraint neural networks for massive pixel parallel image demixing

NASA Astrophysics Data System (ADS)

Szu, Harold H.; Hsu, Charles C.

2002-03-01

We have shown that the remote sensing optical imaging to achieve detailed sub-pixel decomposition is a unique application of blind source separation (BSS) that is truly linear of far away weak signal, instantaneous speed of light without delay, and along the line of sight without multiple paths. In early papers, we have presented a direct application of statistical mechanical de-mixing method called Lagrange Constraint Neural Network (LCNN). While the BSAO algorithm (using a posteriori MaxEnt ANN and neighborhood pixel average) is not acceptable for remote sensing, a mirror symmetric LCNN approach is all right assuming a priori MaxEnt for unknown sources to be averaged over the source statistics (not neighborhood pixel data) in a pixel-by-pixel independent fashion. LCNN reduces the computation complexity, save a great number of memory devices, and cut the cost of implementation. The Landsat system is designed to measure the radiation to deduce surface conditions and materials. For any given material, the amount of emitted and reflected radiation varies by the wavelength. In practice, a single pixel of a Landsat image has seven channels receiving 0.1 to 12 microns of radiation from the ground within a 20x20 meter footprint containing a variety of radiation materials. A-priori LCNN algorithm provides the spatial-temporal variation of mixture that is hardly de-mixable by other a-posteriori BSS or ICA methods. We have already compared the Landsat remote sensing using both methods in WCCI 2002 Hawaii. Unfortunately the absolute benchmark is not possible because of lacking of the ground truth. We will arbitrarily mix two incoherent sampled images as the ground truth. However, the constant total probability of co-located sources within the pixel footprint is necessary for the remote sensing constraint (since on a clear day the total reflecting energy is constant in neighborhood receiving pixel sensors), we have to normalized two image pixel-by-pixel as well. Then, the result is indeed as expected.

An ultra-low power CMOS image sensor with on-chip energy harvesting and power management capability.

PubMed

Cevik, Ismail; Huang, Xiwei; Yu, Hao; Yan, Mei; Ay, Suat U

2015-03-06

An ultra-low power CMOS image sensor with on-chip energy harvesting and power management capability is introduced in this paper. The photodiode pixel array can not only capture images but also harvest solar energy. As such, the CMOS image sensor chip is able to switch between imaging and harvesting modes towards self-power operation. Moreover, an on-chip maximum power point tracking (MPPT)-based power management system (PMS) is designed for the dual-mode image sensor to further improve the energy efficiency. A new isolated P-well energy harvesting and imaging (EHI) pixel with very high fill factor is introduced. Several ultra-low power design techniques such as reset and select boosting techniques have been utilized to maintain a wide pixel dynamic range. The chip was designed and fabricated in a 1.8 V, 1P6M 0.18 µm CMOS process. Total power consumption of the imager is 6.53 µW for a 96 × 96 pixel array with 1 V supply and 5 fps frame rate. Up to 30 μW of power could be generated by the new EHI pixels. The PMS is capable of providing 3× the power required during imaging mode with 50% efficiency allowing energy autonomous operation with a 72.5% duty cycle.

An Ultra-Low Power CMOS Image Sensor with On-Chip Energy Harvesting and Power Management Capability

PubMed Central

Cevik, Ismail; Huang, Xiwei; Yu, Hao; Yan, Mei; Ay, Suat U.

2015-01-01

An ultra-low power CMOS image sensor with on-chip energy harvesting and power management capability is introduced in this paper. The photodiode pixel array can not only capture images but also harvest solar energy. As such, the CMOS image sensor chip is able to switch between imaging and harvesting modes towards self-power operation. Moreover, an on-chip maximum power point tracking (MPPT)-based power management system (PMS) is designed for the dual-mode image sensor to further improve the energy efficiency. A new isolated P-well energy harvesting and imaging (EHI) pixel with very high fill factor is introduced. Several ultra-low power design techniques such as reset and select boosting techniques have been utilized to maintain a wide pixel dynamic range. The chip was designed and fabricated in a 1.8 V, 1P6M 0.18 µm CMOS process. Total power consumption of the imager is 6.53 µW for a 96 × 96 pixel array with 1 V supply and 5 fps frame rate. Up to 30 μW of power could be generated by the new EHI pixels. The PMS is capable of providing 3× the power required during imaging mode with 50% efficiency allowing energy autonomous operation with a 72.5% duty cycle. PMID:25756863

Sub-pixel localisation of passive micro-coil fiducial markers in interventional MRI.

PubMed

Rea, Marc; McRobbie, Donald; Elhawary, Haytham; Tse, Zion T H; Lamperth, Michael; Young, Ian

2009-04-01

Electromechanical devices enable increased accuracy in surgical procedures, and the recent development of MRI-compatible mechatronics permits the use of MRI for real-time image guidance. Integrated imaging of resonant micro-coil fiducials provides an accurate method of tracking devices in a scanner with increased flexibility compared to gradient tracking. Here we report on the ability of ten different image-processing algorithms to track micro-coil fiducials with sub-pixel accuracy. Five algorithms: maximum pixel, barycentric weighting, linear interpolation, quadratic fitting and Gaussian fitting were applied both directly to the pixel intensity matrix and to the cross-correlation matrix obtained by 2D convolution with a reference image. Using images of a 3 mm fiducial marker and a pixel size of 1.1 mm, intensity linear interpolation, which calculates the position of the fiducial centre by interpolating the pixel data to find the fiducial edges, was found to give the best performance for minimal computing power; a maximum error of 0.22 mm was observed in fiducial localisation for displacements up to 40 mm. The inherent standard deviation of fiducial localisation was 0.04 mm. This work enables greater accuracy to be achieved in passive fiducial tracking.

Convolving optically addressed VLSI liquid crystal SLM

NASA Astrophysics Data System (ADS)

Jared, David A.; Stirk, Charles W.

1994-03-01

We designed, fabricated, and tested an optically addressed spatial light modulator (SLM) that performs a 3 X 3 kernel image convolution using ferroelectric liquid crystal on VLSI technology. The chip contains a 16 X 16 array of current-mirror-based convolvers with a fixed kernel for finding edges. The pixels are located on 75 micron centers, and the modulators are 20 microns on a side. The array successfully enhanced edges in illumination patterns. We developed a high-level simulation tool (CON) for analyzing the performance of convolving SLM designs. CON has a graphical interface and simulates SLM functions using SPICE-like device models. The user specifies the pixel function along with the device parameters and nonuniformities. We discovered through analysis, simulation and experiment that the operation of current-mirror-based convolver pixels is degraded at low light levels by the variation of transistor threshold voltages inherent to CMOS chips. To function acceptable, the test SLM required the input image to have an minimum irradiance of 10 (mu) W/cm2. The minimum required irradiance can be further reduced by adding a photodarlington near the photodetector or by increasing the size of the transistors used to calculate the convolution.

An intelligent support system for automatic detection of cerebral vascular accidents from brain CT images.

PubMed

Hajimani, Elmira; Ruano, M G; Ruano, A E

2017-07-01

This paper presents a Radial Basis Functions Neural Network (RBFNN) based detection system, for automatic identification of Cerebral Vascular Accidents (CVA) through analysis of Computed Tomographic (CT) images. For the design of a neural network classifier, a Multi Objective Genetic Algorithm (MOGA) framework is used to determine the architecture of the classifier, its corresponding parameters and input features by maximizing the classification precision, while ensuring generalization. This approach considers a large number of input features, comprising first and second order pixel intensity statistics, as well as symmetry/asymmetry information with respect to the ideal mid-sagittal line. Values of specificity of 98% and sensitivity of 98% were obtained, at pixel level, by an ensemble of non-dominated models generated by MOGA, in a set of 150 CT slices (1,867,602pixels), marked by a NeuroRadiologist. This approach also compares favorably at a lesion level with three other published solutions, in terms of specificity (86% compared with 84%), degree of coincidence of marked lesions (89% compared with 77%) and classification accuracy rate (96% compared with 88%). Copyright © 2017. Published by Elsevier B.V.

Contrast-guided image interpolation.

PubMed

Wei, Zhe; Ma, Kai-Kuang

2013-11-01

In this paper a contrast-guided image interpolation method is proposed that incorporates contrast information into the image interpolation process. Given the image under interpolation, four binary contrast-guided decision maps (CDMs) are generated and used to guide the interpolation filtering through two sequential stages: 1) the 45(°) and 135(°) CDMs for interpolating the diagonal pixels and 2) the 0(°) and 90(°) CDMs for interpolating the row and column pixels. After applying edge detection to the input image, the generation of a CDM lies in evaluating those nearby non-edge pixels of each detected edge for re-classifying them possibly as edge pixels. This decision is realized by solving two generalized diffusion equations over the computed directional variation (DV) fields using a derived numerical approach to diffuse or spread the contrast boundaries or edges, respectively. The amount of diffusion or spreading is proportional to the amount of local contrast measured at each detected edge. The diffused DV fields are then thresholded for yielding the binary CDMs, respectively. Therefore, the decision bands with variable widths will be created on each CDM. The two CDMs generated in each stage will be exploited as the guidance maps to conduct the interpolation process: for each declared edge pixel on the CDM, a 1-D directional filtering will be applied to estimate its associated to-be-interpolated pixel along the direction as indicated by the respective CDM; otherwise, a 2-D directionless or isotropic filtering will be used instead to estimate the associated missing pixels for each declared non-edge pixel. Extensive simulation results have clearly shown that the proposed contrast-guided image interpolation is superior to other state-of-the-art edge-guided image interpolation methods. In addition, the computational complexity is relatively low when compared with existing methods; hence, it is fairly attractive for real-time image applications.

Colorization-Based RGB-White Color Interpolation using Color Filter Array with Randomly Sampled Pattern

PubMed Central

Oh, Paul; Lee, Sukho; Kang, Moon Gi

2017-01-01

Recently, several RGB-White (RGBW) color filter arrays (CFAs) have been proposed, which have extra white (W) pixels in the filter array that are highly sensitive. Due to the high sensitivity, the W pixels have better SNR (Signal to Noise Ratio) characteristics than other color pixels in the filter array, especially, in low light conditions. However, most of the RGBW CFAs are designed so that the acquired RGBW pattern image can be converted into the conventional Bayer pattern image, which is then again converted into the final color image by using conventional demosaicing methods, i.e., color interpolation techniques. In this paper, we propose a new RGBW color filter array based on a totally different color interpolation technique, the colorization algorithm. The colorization algorithm was initially proposed for colorizing a gray image into a color image using a small number of color seeds. Here, we adopt this algorithm as a color interpolation technique, so that the RGBW color filter array can be designed with a very large number of W pixels to make the most of the highly sensitive characteristics of the W channel. The resulting RGBW color filter array has a pattern with a large proportion of W pixels, while the small-numbered RGB pixels are randomly distributed over the array. The colorization algorithm makes it possible to reconstruct the colors from such a small number of RGB values. Due to the large proportion of W pixels, the reconstructed color image has a high SNR value, especially higher than those of conventional CFAs in low light condition. Experimental results show that many important information which are not perceived in color images reconstructed with conventional CFAs are perceived in the images reconstructed with the proposed method. PMID:28657602

Colorization-Based RGB-White Color Interpolation using Color Filter Array with Randomly Sampled Pattern.

PubMed

Oh, Paul; Lee, Sukho; Kang, Moon Gi

2017-06-28

Recently, several RGB-White (RGBW) color filter arrays (CFAs) have been proposed, which have extra white (W) pixels in the filter array that are highly sensitive. Due to the high sensitivity, the W pixels have better SNR (Signal to Noise Ratio) characteristics than other color pixels in the filter array, especially, in low light conditions. However, most of the RGBW CFAs are designed so that the acquired RGBW pattern image can be converted into the conventional Bayer pattern image, which is then again converted into the final color image by using conventional demosaicing methods, i.e., color interpolation techniques. In this paper, we propose a new RGBW color filter array based on a totally different color interpolation technique, the colorization algorithm. The colorization algorithm was initially proposed for colorizing a gray image into a color image using a small number of color seeds. Here, we adopt this algorithm as a color interpolation technique, so that the RGBW color filter array can be designed with a very large number of W pixels to make the most of the highly sensitive characteristics of the W channel. The resulting RGBW color filter array has a pattern with a large proportion of W pixels, while the small-numbered RGB pixels are randomly distributed over the array. The colorization algorithm makes it possible to reconstruct the colors from such a small number of RGB values. Due to the large proportion of W pixels, the reconstructed color image has a high SNR value, especially higher than those of conventional CFAs in low light condition. Experimental results show that many important information which are not perceived in color images reconstructed with conventional CFAs are perceived in the images reconstructed with the proposed method.

Dual-band QWIP MWIR/LWIR focal plane array test results

NASA Astrophysics Data System (ADS)

Goldberg, Arnold C.; Fischer, Theodore; Kennerly, Stephen; Wang, Samuel C.; Sundaram, Mani; Uppal, Parvez; Winn, Michael L.; Milne, Gregory L.; Stevens, Mark A.

2000-07-01

We report on the results of laboratory and field tests on a pixel-registered, 2-color MWIR/LWIR 256 X 256 QWIP FPA with simultaneous integrating capability. The FPA studied contained stacked QWIP structures with spectral peaks at 5.1 micrometer and 9.0 micrometer. Normally incident radiation was coupled into the devices using a diffraction grating designed to operate in both spectral bands. Each pixel is connected to the read-out integrated circuit by three bumps to permit the application of separate bias levels to each QWIP stack and allow simultaneous integration of the signal current in each band. We found the FPA to have high pixel operability, well balanced response, good imaging performance, high optical fill factor, and low spectral crosstalk. We present data on measurements of the noise-equivalent temperature difference of the FPA in both bands as functions of temperature and bias. The FPA data are compared to single-pixel data taken on devices from the same wafer. We also present data on the sensitivity of this FPA to polarized light. It is found that the LWIR portion of the device is very sensitive to the direction of polarization of the incident light. The MWIR part of the device is relatively insensitive to the polarization. In addition, imagery was taken with this FPA of military targets in the field. Image fusion techniques were applied to the resulting images.

A Compact Polarization Imager

NASA Technical Reports Server (NTRS)

Thompson, Karl E.; Rust, David M.; Chen, Hua

1995-01-01

A new type of image detector has been designed to analyze the polarization of light simultaneously at all picture elements (pixels) in a scene. The Integrated Dual Imaging Detector (IDID) consists of a polarizing beamsplitter bonded to a custom-designed charge-coupled device with signal-analysis circuitry, all integrated on a silicon chip. The IDID should simplify the design and operation of imaging polarimeters and spectroscopic imagers used, for example, in atmospheric and solar research. Other applications include environmental monitoring and robot vision. Innovations in the IDID include two interleaved 512 x 1024 pixel imaging arrays (one for each polarization plane), large dynamic range (well depth of 10(exp 6) electrons per pixel), simultaneous readout and display of both images at 10(exp 6) pixels per second, and on-chip analog signal processing to produce polarization maps in real time. When used with a lithium niobate Fabry-Perot etalon or other color filter that can encode spectral information as polarization, the IDID can reveal tiny differences between simultaneous images at two wavelengths.

Precise color images a high-speed color video camera system with three intensified sensors

NASA Astrophysics Data System (ADS)

Oki, Sachio; Yamakawa, Masafumi; Gohda, Susumu; Etoh, Takeharu G.

1999-06-01

High speed imaging systems have been used in a large field of science and engineering. Although the high speed camera systems have been improved to high performance, most of their applications are only to get high speed motion pictures. However, in some fields of science and technology, it is useful to get some other information, such as temperature of combustion flame, thermal plasma and molten materials. Recent digital high speed video imaging technology should be able to get such information from those objects. For this purpose, we have already developed a high speed video camera system with three-intensified-sensors and cubic prism image splitter. The maximum frame rate is 40,500 pps (picture per second) at 64 X 64 pixels and 4,500 pps at 256 X 256 pixels with 256 (8 bit) intensity resolution for each pixel. The camera system can store more than 1,000 pictures continuously in solid state memory. In order to get the precise color images from this camera system, we need to develop a digital technique, which consists of a computer program and ancillary instruments, to adjust displacement of images taken from two or three image sensors and to calibrate relationship between incident light intensity and corresponding digital output signals. In this paper, the digital technique for pixel-based displacement adjustment are proposed. Although the displacement of the corresponding circle was more than 8 pixels in original image, the displacement was adjusted within 0.2 pixels at most by this method.

Sparsely-sampled hyperspectral stimulated Raman scattering microscopy: a theoretical investigation

NASA Astrophysics Data System (ADS)

Lin, Haonan; Liao, Chien-Sheng; Wang, Pu; Huang, Kai-Chih; Bouman, Charles A.; Kong, Nan; Cheng, Ji-Xin

2017-02-01

A hyperspectral image corresponds to a data cube with two spatial dimensions and one spectral dimension. Through linear un-mixing, hyperspectral images can be decomposed into spectral signatures of pure components as well as their concentration maps. Due to this distinct advantage on component identification, hyperspectral imaging becomes a rapidly emerging platform for engineering better medicine and expediting scientific discovery. Among various hyperspectral imaging techniques, hyperspectral stimulated Raman scattering (HSRS) microscopy acquires data in a pixel-by-pixel scanning manner. Nevertheless, current image acquisition speed for HSRS is insufficient to capture the dynamics of freely moving subjects. Instead of reducing the pixel dwell time to achieve speed-up, which would inevitably decrease signal-to-noise ratio (SNR), we propose to reduce the total number of sampled pixels. Location of sampled pixels are carefully engineered with triangular wave Lissajous trajectory. Followed by a model-based image in-painting algorithm, the complete data is recovered for linear unmixing. Simulation results show that by careful selection of trajectory, a fill rate as low as 10% is sufficient to generate accurate linear unmixing results. The proposed framework applies to any hyperspectral beam-scanning imaging platform which demands high acquisition speed.

Imaging During MESSENGER's Second Flyby of Mercury

NASA Astrophysics Data System (ADS)

Chabot, N. L.; Prockter, L. M.; Murchie, S. L.; Robinson, M. S.; Laslo, N. R.; Kang, H. K.; Hawkins, S. E.; Vaughan, R. M.; Head, J. W.; Solomon, S. C.; MESSENGER Team

2008-12-01

During MESSENGER's second flyby of Mercury on October 6, 2008, the Mercury Dual Imaging System (MDIS) will acquire 1287 images. The images will include coverage of about 30% of Mercury's surface not previously seen by spacecraft. A portion of the newly imaged terrain will be viewed during the inbound portion of the flyby. On the outbound leg, MDIS will image additional previously unseen terrain as well as regions imaged under different illumination geometry by Mariner 10. These new images, when combined with images from Mariner 10 and from MESSENGER's first Mercury flyby, will enable the first regional- resolution global view of Mercury constituting a combined total coverage of about 96% of the planet's surface. MDIS consists of both a Wide Angle Camera (WAC) and a Narrow Angle Camera (NAC). During MESSENGER's second Mercury flyby, the following imaging activities are planned: about 86 minutes before the spacecraft's closest pass by the planet, the WAC will acquire images through 11 different narrow-band color filters of the approaching crescent planet at a resolution of about 5 km/pixel. At slightly less than 1 hour to closest approach, the NAC will acquire a 4-column x 11-row mosaic with an approximate resolution of 450 m/pixel. At 8 minutes after closest approach, the WAC will obtain the highest-resolution multispectral images to date of Mercury's surface, imaging a portion of the surface through 11 color filters at resolutions of about 250-600 m/pixel. A strip of high-resolution NAC images, with a resolution of approximately 100 m/pixel, will follow these WAC observations. The NAC will next acquire a 15-column x 13- row high-resolution mosaic of the northern hemisphere of the departing planet, beginning approximately 21 minutes after closest approach, with resolutions of 140-300 m/pixel; this mosaic will fill a large gore in the Mariner 10 data. At about 42 minutes following closest approach, the WAC will acquire a 3x3, 11-filter, full- planet mosaic with an average resolution of 2.5 km/pixel. Two NAC mosaics of the entire departing planet will be acquired beginning about 66 minutes after closest approach, with resolutions of 500-700 m/pixel. About 89 minutes following closest approach, the WAC will acquire a multispectral image set with a resolution of about 5 km/pixel. Following this WAC image set, MDIS will continue to acquire occasional images with both the WAC and NAC until 20 hours after closest approach, at which time the flyby data will begin being transmitted to Earth.

A 10MHz Fiber-Coupled Photodiode Imaging Array for Plasma Diagnostics

NASA Astrophysics Data System (ADS)

Brockington, Samuel; Case, Andrew; Witherspoon, F. Douglas

2013-10-01

HyperV Technologies has been developing an imaging diagnostic comprised of arrays of fast, low-cost, long-record-length, fiber-optically-coupled photodiode channels to investigate plasma dynamics and other fast, bright events. By coupling an imaging fiber bundle to a bank of amplified photodiode channels, imagers and streak imagers of 100 to 10,000 pixels can be constructed. By interfacing analog photodiode systems directly to commercial analog to digital convertors and modern memory chips, a prototype pixel with an extremely deep record length (128 k points at 40 Msamples/s) has been achieved for a 10 bit resolution system with signal bandwidths of at least 10 MHz. Progress on a prototype 100 Pixel streak camera employing this technique is discussed along with preliminary experimental results and plans for a 10,000 pixel imager. Work supported by USDOE Phase 1 SBIR Grant DE-SC0009492.

A 3D image sensor with adaptable charge subtraction scheme for background light suppression

NASA Astrophysics Data System (ADS)

Shin, Jungsoon; Kang, Byongmin; Lee, Keechang; Kim, James D. K.

2013-02-01

We present a 3D ToF (Time-of-Flight) image sensor with adaptive charge subtraction scheme for background light suppression. The proposed sensor can alternately capture high resolution color image and high quality depth map in each frame. In depth-mode, the sensor requires enough integration time for accurate depth acquisition, but saturation will occur in high background light illumination. We propose to divide the integration time into N sub-integration times adaptively. In each sub-integration time, our sensor captures an image without saturation and subtracts the charge to prevent the pixel from the saturation. In addition, the subtraction results are cumulated N times obtaining a final result image without background illumination at full integration time. Experimental results with our own ToF sensor show high background suppression performance. We also propose in-pixel storage and column-level subtraction circuit for chiplevel implementation of the proposed method. We believe the proposed scheme will enable 3D sensors to be used in out-door environment.

Early Validation of Sentinel-2 L2A Processor and Products

NASA Astrophysics Data System (ADS)

Pflug, Bringfried; Main-Knorn, Magdalena; Bieniarz, Jakub; Debaecker, Vincent; Louis, Jerome

2016-08-01

Sentinel-2 is a constellation of two polar orbiting satellite units each one equipped with an optical imaging sensor MSI (Multi-Spectral Instrument). Sentinel-2A was launched on June 23, 2015 and Sentinel-2B will follow in 2017.The Level-2A (L2A) processor Sen2Cor implemented for Sentinel-2 data provides a scene classification image, aerosol optical thickness (AOT) and water vapour (WV) maps and the Bottom-Of-Atmosphere (BOA) corrected reflectance product. First validation results of Sen2Cor scene classification showed an overall accuracy of 81%. AOT at 550 nm is estimated by Sen2Cor with uncertainty of 0.035 for cloudless images and locations with dense dark vegetation (DDV) pixels present in the image. Aerosol estimation fails if the image contains no DDV-pixels. Mean difference between Sen2Cor WV and ground-truth is 0.29 cm. Uncertainty of up to 0.04 was found for the BOA- reflectance product.

Airborne Hyperspectral Imagery for the Detection of Agricultural Crop Stress

NASA Technical Reports Server (NTRS)

Cassady, Philip E.; Perry, Eileen M.; Gardner, Margaret E.; Roberts, Dar A.

2001-01-01

Multispectral digital imagery from aircraft or satellite is presently being used to derive basic assessments of crop health for growers and others involved in the agricultural industry. Research indicates that narrow band stress indices derived from hyperspectral imagery should have improved sensitivity to provide more specific information on the type and cause of crop stress, Under funding from the NASA Earth Observation Commercial Applications Program (EOCAP) we are identifying and evaluating scientific and commercial applications of hyperspectral imagery for the remote characterization of agricultural crop stress. During the summer of 1999 a field experiment was conducted with varying nitrogen treatments on a production corn-field in eastern Nebraska. The AVIRIS (Airborne Visible-Infrared Imaging Spectrometer) hyperspectral imager was flown at two critical dates during crop development, at two different altitudes, providing images with approximately 18m pixels and 3m pixels. Simultaneous supporting soil and crop characterization included spectral reflectance measurements above the canopy, biomass characterization, soil sampling, and aerial photography. In this paper we describe the experiment and results, and examine the following three issues relative to the utility of hyperspectral imagery for scientific study and commercial crop stress products: (1) Accuracy of reflectance derived stress indices relative to conventional measures of stress. We compare reflectance-derived indices (both field radiometer and AVIRIS) with applied nitrogen and with leaf level measurement of nitrogen availability and chlorophyll concentrations over the experimental plots (4 replications of 5 different nitrogen levels); (2) Ability of the hyperspectral sensors to detect sub-pixel areas under crop stress. We applied the stress indices to both the 3m and 18m AVIRIS imagery for the entire production corn field using several sub-pixel areas within the field to compare the relative sensitivity of each stress index; and (3) Comparative sensitivity of stress indices to realistic measurement uncertainties. We compare the stress indices calculated with several levels of spectral uncertainty (by shifting the wavelengths) and reflectance uncertainty (by systematically varying the reflectance retrieval code initialization).

Terahertz imaging with compressed sensing and phase retrieval.

PubMed

Chan, Wai Lam; Moravec, Matthew L; Baraniuk, Richard G; Mittleman, Daniel M

2008-05-01

We describe a novel, high-speed pulsed terahertz (THz) Fourier imaging system based on compressed sensing (CS), a new signal processing theory, which allows image reconstruction with fewer samples than traditionally required. Using CS, we successfully reconstruct a 64 x 64 image of an object with pixel size 1.4 mm using a randomly chosen subset of the 4096 pixels, which defines the image in the Fourier plane, and observe improved reconstruction quality when we apply phase correction. For our chosen image, only about 12% of the pixels are required for reassembling the image. In combination with phase retrieval, our system has the capability to reconstruct images with only a small subset of Fourier amplitude measurements and thus has potential application in THz imaging with cw sources.

A fast and efficient segmentation scheme for cell microscopic image.

PubMed

Lebrun, G; Charrier, C; Lezoray, O; Meurie, C; Cardot, H

2007-04-27

Microscopic cellular image segmentation schemes must be efficient for reliable analysis and fast to process huge quantity of images. Recent studies have focused on improving segmentation quality. Several segmentation schemes have good quality but processing time is too expensive to deal with a great number of images per day. For segmentation schemes based on pixel classification, the classifier design is crucial since it is the one which requires most of the processing time necessary to segment an image. The main contribution of this work is focused on how to reduce the complexity of decision functions produced by support vector machines (SVM) while preserving recognition rate. Vector quantization is used in order to reduce the inherent redundancy present in huge pixel databases (i.e. images with expert pixel segmentation). Hybrid color space design is also used in order to improve data set size reduction rate and recognition rate. A new decision function quality criterion is defined to select good trade-off between recognition rate and processing time of pixel decision function. The first results of this study show that fast and efficient pixel classification with SVM is possible. Moreover posterior class pixel probability estimation is easy to compute with Platt method. Then a new segmentation scheme using probabilistic pixel classification has been developed. This one has several free parameters and an automatic selection must dealt with, but criteria for evaluate segmentation quality are not well adapted for cell segmentation, especially when comparison with expert pixel segmentation must be achieved. Another important contribution in this paper is the definition of a new quality criterion for evaluation of cell segmentation. The results presented here show that the selection of free parameters of the segmentation scheme by optimisation of the new quality cell segmentation criterion produces efficient cell segmentation.

Image Segmentation Analysis for NASA Earth Science Applications

NASA Technical Reports Server (NTRS)

Tilton, James C.

2010-01-01

NASA collects large volumes of imagery data from satellite-based Earth remote sensing sensors. Nearly all of the computerized image analysis of this data is performed pixel-by-pixel, in which an algorithm is applied directly to individual image pixels. While this analysis approach is satisfactory in many cases, it is usually not fully effective in extracting the full information content from the high spatial resolution image data that s now becoming increasingly available from these sensors. The field of object-based image analysis (OBIA) has arisen in recent years to address the need to move beyond pixel-based analysis. The Recursive Hierarchical Segmentation (RHSEG) software developed by the author is being used to facilitate moving from pixel-based image analysis to OBIA. The key unique aspect of RHSEG is that it tightly intertwines region growing segmentation, which produces spatially connected region objects, with region object classification, which groups sets of region objects together into region classes. No other practical, operational image segmentation approach has this tight integration of region growing object finding with region classification This integration is made possible by the recursive, divide-and-conquer implementation utilized by RHSEG, in which the input image data is recursively subdivided until the image data sections are small enough to successfully mitigat the combinatorial explosion caused by the need to compute the dissimilarity between each pair of image pixels. RHSEG's tight integration of region growing object finding and region classification is what enables the high spatial fidelity of the image segmentations produced by RHSEG. This presentation will provide an overview of the RHSEG algorithm and describe how it is currently being used to support OBIA or Earth Science applications such as snow/ice mapping and finding archaeological sites from remotely sensed data.

Geometric registration of images by similarity transformation using two reference points

NASA Technical Reports Server (NTRS)

Kang, Yong Q. (Inventor); Jo, Young-Heon (Inventor); Yan, Xiao-Hai (Inventor)

2011-01-01

A method for registering a first image to a second image using a similarity transformation. The each image includes a plurality of pixels. The first image pixels are mapped to a set of first image coordinates and the second image pixels are mapped to a set of second image coordinates. The first image coordinates of two reference points in the first image are determined. The second image coordinates of these reference points in the second image are determined. A Cartesian translation of the set of second image coordinates is performed such that the second image coordinates of the first reference point match its first image coordinates. A similarity transformation of the translated set of second image coordinates is performed. This transformation scales and rotates the second image coordinates about the first reference point such that the second image coordinates of the second reference point match its first image coordinates.

High performance digital read out integrated circuit (DROIC) for infrared imaging

NASA Astrophysics Data System (ADS)

Mizuno, Genki; Olah, Robert; Oduor, Patrick; Dutta, Achyut K.; Dhar, Nibir K.

2016-05-01

Banpil Photonics has developed a high-performance Digital Read-Out Integrated Circuit (DROIC) for image sensors and camera systems targeting various military, industrial and commercial Infrared (IR) imaging applications. The on-chip digitization of the pixel output eliminates the necessity for an external analog-to-digital converter (ADC), which not only cuts costs, but also enables miniaturization of packaging to achieve SWaP-C camera systems. In addition, the DROIC offers new opportunities for greater on-chip processing intelligence that are not possible in conventional analog ROICs prevalent today. Conventional ROICs, which typically can enhance only one high performance attribute such as frame rate, power consumption or noise level, fail when simultaneously targeting the most aggressive performance requirements demanded in imaging applications today. Additionally, scaling analog readout circuits to meet such requirements leads to expensive, high-power consumption with large and complex systems that are untenable in the trend towards SWaP-C. We present the implementation of a VGA format (640x512 pixels 15μm pitch) capacitivetransimpedance amplifier (CTIA) DROIC architecture that incorporates a 12-bit ADC at the pixel level. The CTIA pixel input circuitry has two gain modes with programmable full-well capacity values of 100K e- and 500K e-. The DROIC has been developed with a system-on-chip architecture in mind, where all the timing and biasing are generated internally without requiring any critical external inputs. The chip is configurable with many parameters programmable through a serial programmable interface (SPI). It features a global shutter, low power, and high frame rates programmable from 30 up 500 frames per second in full VGA format supported through 24 LVDS outputs. This DROIC, suitable for hybridization with focal plane arrays (FPA) is ideal for high-performance uncooled camera applications ranging from near IR (NIR) and shortwave IR (SWIR) to mid-wave IR (MWIR) and long-wave IR (LWIR) spectral bands.

A Chip and Pixel Qualification Methodology on Imaging Sensors

NASA Technical Reports Server (NTRS)

Chen, Yuan; Guertin, Steven M.; Petkov, Mihail; Nguyen, Duc N.; Novak, Frank

2004-01-01

This paper presents a qualification methodology on imaging sensors. In addition to overall chip reliability characterization based on sensor s overall figure of merit, such as Dark Rate, Linearity, Dark Current Non-Uniformity, Fixed Pattern Noise and Photon Response Non-Uniformity, a simulation technique is proposed and used to project pixel reliability. The projected pixel reliability is directly related to imaging quality and provides additional sensor reliability information and performance control.

The analysis and rationale behind the upgrading of existing standard definition thermal imagers to high definition

NASA Astrophysics Data System (ADS)

Goss, Tristan M.

2016-05-01

With 640x512 pixel format IR detector arrays having been on the market for the past decade, Standard Definition (SD) thermal imaging sensors have been developed and deployed across the world. Now with 1280x1024 pixel format IR detector arrays becoming readily available designers of thermal imager systems face new challenges as pixel sizes reduce and the demand and applications for High Definition (HD) thermal imaging sensors increases. In many instances the upgrading of existing under-sampled SD thermal imaging sensors into more optimally sampled or oversampled HD thermal imaging sensors provides a more cost effective and reduced time to market option than to design and develop a completely new sensor. This paper presents the analysis and rationale behind the selection of the best suited HD pixel format MWIR detector for the upgrade of an existing SD thermal imaging sensor to a higher performing HD thermal imaging sensor. Several commercially available and "soon to be" commercially available HD small pixel IR detector options are included as part of the analysis and are considered for this upgrade. The impact the proposed detectors have on the sensor's overall sensitivity, noise and resolution is analyzed, and the improved range performance is predicted. Furthermore with reduced dark currents due to the smaller pixel sizes, the candidate HD MWIR detectors are operated at higher temperatures when compared to their SD predecessors. Therefore, as an additional constraint and as a design goal, the feasibility of achieving upgraded performance without any increase in the size, weight and power consumption of the thermal imager is discussed herein.

Adaptive single-pixel imaging with aggregated sampling and continuous differential measurements

NASA Astrophysics Data System (ADS)

Huo, Yaoran; He, Hongjie; Chen, Fan; Tai, Heng-Ming

2018-06-01

This paper proposes an adaptive compressive imaging technique with one single-pixel detector and single arm. The aggregated sampling (AS) method enables the reduction of resolutions of the reconstructed images. It aims to reduce the time and space consumption. The target image with a resolution up to 1024 × 1024 can be reconstructed successfully at the 20% sampling rate. The continuous differential measurement (CDM) method combined with a ratio factor of significant coefficient (RFSC) improves the imaging quality. Moreover, RFSC reduces the human intervention in parameter setting. This technique enhances the practicability of single-pixel imaging with the benefits from less time and space consumption, better imaging quality and less human intervention.

Image Accumulation in Pixel Detector Gated by Late External Trigger Signal and its Application in Imaging Activation Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jakubek, J.; Cejnarova, A.; Platkevic, M.

Single quantum counting pixel detectors of Medipix type are starting to be used in various radiographic applications. Compared to standard devices for digital imaging (such as CCDs or CMOS sensors) they present significant advantages: direct conversion of radiation to electric signal, energy sensitivity, noiseless image integration, unlimited dynamic range, absolute linearity. In this article we describe usage of the pixel device TimePix for image accumulation gated by late trigger signal. Demonstration of the technique is given on imaging coincidence instrumental neutron activation analysis (Imaging CINAA). This method allows one to determine concentration and distribution of certain preselected element in anmore » inspected sample.« less

Evaluate depth of field limits of fixed focus lens arrangements in thermal infrared

NASA Astrophysics Data System (ADS)

Schuster, Norbert

2016-05-01

More and more modern thermal imaging systems use uncooled detectors. High volume applications work with detectors that have a reduced pixel count (typically between 200x150 and 640x480). This reduces the usefulness of modern image treatment procedures such as wave front coding. On the other hand, uncooled detectors demand lenses with fast fnumbers, near f/1.0, which reduces the expected Depth of Field (DoF). What are the limits on resolution if the target changes distance to the camera system? The desire to implement lens arrangements without a focusing mechanism demands a deeper quantification of the DoF problem. A new approach avoids the classic "accepted image blur circle" and quantifies the expected DoF by the Through Focus MTF of the lens. This function is defined for a certain spatial frequency that provides a straightforward relation to the pixel pitch of imaging device. A certain minimum MTF-level is necessary so that the complete thermal imaging system can realize its basic functions, such as recognition or detection of specified targets. Very often, this technical tradeoff is approved with a certain lens. But what is the impact of changing the lens for one with a different focal length? Narrow field lenses, which give more details of targets in longer distances, tighten the DoF problem. A first orientation is given by the hyperfocal distance. It depends in a square relation on the focal length and in a linear relation on the through focus MTF of the lens. The analysis of these relations shows the contradicting requirements between higher thermal and spatial resolution, faster f-number and desired DoF. Furthermore, the hyperfocal distance defines the DoF-borders. Their relation between is such as the first order imaging formulas. A calculation methodology will be presented to transfer DoF-results from an approved combination lens and camera to another lens in combination with the initial camera. Necessary input for this prediction is the accepted DoF of the initial combination and the through focus MTFs of both lenses. The accepted DoF of the initial combination defines an application and camera related MTF-level, which must be provided also by the new lens. Examples are provided. The formula of the Diffraction-Limited-Through-Focus-MTF (DLTF) quantifies the physical limit and works without any ray trace. This relation respects the pixel pitch, the waveband and the aperture based f-number, but is independent of detector size. The DLTF has a steeper slope than the ray traced Through-Focus-MTF; its maximum is the diffraction limit. The DLTF predicts the DoF-relations quite precisely. Differences to ray trace results are discussed. Last calculations with modern detectors show that a static chosen MTF-level doesn't reflect the reality for the DoFproblem. The MTF-level to respect depends on application, pixel pitch, IR-camera and image treatment. A value of 0.250 at the detector Nyquist frequency seems to be a reasonable starting point for uncooled FPAs with 17μm pixel pitch.

Salient object detection based on multi-scale contrast.

PubMed

Wang, Hai; Dai, Lei; Cai, Yingfeng; Sun, Xiaoqiang; Chen, Long

2018-05-01

Due to the development of deep learning networks, a salient object detection based on deep learning networks, which are used to extract the features, has made a great breakthrough compared to the traditional methods. At present, the salient object detection mainly relies on very deep convolutional network, which is used to extract the features. In deep learning networks, an dramatic increase of network depth may cause more training errors instead. In this paper, we use the residual network to increase network depth and to mitigate the errors caused by depth increase simultaneously. Inspired by image simplification, we use color and texture features to obtain simplified image with multiple scales by means of region assimilation on the basis of super-pixels in order to reduce the complexity of images and to improve the accuracy of salient target detection. We refine the feature on pixel level by the multi-scale feature correction method to avoid the feature error when the image is simplified at the above-mentioned region level. The final full connection layer not only integrates features of multi-scale and multi-level but also works as classifier of salient targets. The experimental results show that proposed model achieves better results than other salient object detection models based on original deep learning networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Enhancing the image resolution in a single-pixel sub-THz imaging system based on compressed sensing

NASA Astrophysics Data System (ADS)

Alkus, Umit; Ermeydan, Esra Sengun; Sahin, Asaf Behzat; Cankaya, Ilyas; Altan, Hakan

2018-04-01

Compressed sensing (CS) techniques allow for faster imaging when combined with scan architectures, which typically suffer from speed. This technique when implemented with a subterahertz (sub-THz) single detector scan imaging system provides images whose resolution is only limited by the pixel size of the pattern used to scan the image plane. To overcome this limitation, the image of the target can be oversampled; however, this results in slower imaging rates especially if this is done in two-dimensional across the image plane. We show that by implementing a one-dimensional (1-D) scan of the image plane, a modified approach to CS theory applied with an appropriate reconstruction algorithm allows for successful reconstruction of the reflected oversampled image of a target placed in standoff configuration from the source. The experiments are done in reflection mode configuration where the operating frequency is 93 GHz and the corresponding wavelength is λ = 3.2 mm. To reconstruct the image with fewer samples, CS theory is applied using masks where the pixel size is 5 mm × 5 mm, and each mask covers an image area of 5 cm × 5 cm, meaning that the basic image is resolved as 10 × 10 pixels. To enhance the resolution, the information between two consecutive pixels is used, and oversampling along 1-D coupled with a modification of the masks in CS theory allowed for oversampled images to be reconstructed rapidly in 20 × 20 and 40 × 40 pixel formats. These are then compared using two different reconstruction algorithms, TVAL3 and ℓ1-MAGIC. The performance of these methods is compared for both simulated signals and real signals. It is found that the modified CS theory approach coupled with the TVAL3 reconstruction process, even when scanning along only 1-D, allows for rapid precise reconstruction of the oversampled target.

The Effect Of Pixel Size On The Detection Rate Of Early Pulmonary Sarcoidosis In Digital Chest Radiographic Systems

NASA Astrophysics Data System (ADS)

MacMahon, Heber; Vyborny, Carl; Powell, Gregory; Doi, Kunio; Metz, Charles E.

1984-08-01

In digital radiography the pixel size used determines the potential spatial resolution of the system. The need for spatial resolution varies depending on the subject matter imaged. In many areas, including the chest, the minimum spatial resolution requirements have not been determined. Sarcoidosis is a disease which frequently causes subtle interstitial infiltrates in the lungs. As the initial step in an investigation designed to determine the minimum pixel size required in digital chest radiographic systems, we have studied 1 mm pixel digitized images on patients with early pulmonary sarcoidosis. The results of this preliminary study suggest that neither mild interstitial pulmonary infiltrates nor other abnormalities such as pneumothoraces may be detected reliably with 1 mm pixel digital images.

ACE: Automatic Centroid Extractor for real time target tracking

NASA Technical Reports Server (NTRS)

Cameron, K.; Whitaker, S.; Canaris, J.

1990-01-01

A high performance video image processor has been implemented which is capable of grouping contiguous pixels from a raster scan image into groups and then calculating centroid information for each object in a frame. The algorithm employed to group pixels is very efficient and is guaranteed to work properly for all convex shapes as well as most concave shapes. Processing speeds are adequate for real time processing of video images having a pixel rate of up to 20 million pixels per second. Pixels may be up to 8 bits wide. The processor is designed to interface directly to a transputer serial link communications channel with no additional hardware. The full custom VLSI processor was implemented in a 1.6 mu m CMOS process and measures 7200 mu m on a side.

3-D Spatial Resolution of 350 μm Pitch Pixelated CdZnTe Detectors for Imaging Applications.

PubMed

Yin, Yongzhi; Chen, Ximeng; Wu, Heyu; Komarov, Sergey; Garson, Alfred; Li, Qiang; Guo, Qingzhen; Krawczynski, Henric; Meng, Ling-Jian; Tai, Yuan-Chuan

2013-02-01

We are currently investigating the feasibility of using highly pixelated Cadmium Zinc Telluride (CdZnTe) detectors for sub-500 μ m resolution PET imaging applications. A 20 mm × 20 mm × 5 mm CdZnTe substrate was fabricated with 350 μ m pitch pixels (250 μ m anode pixels with 100 μ m gap) and coplanar cathode. Charge sharing among the pixels of a 350 μ m pitch detector was studied using collimated 122 keV and 511 keV gamma ray sources. For a 350 μ m pitch CdZnTe detector, scatter plots of the charge signal of two neighboring pixels clearly show more charge sharing when the collimated beam hits the gap between adjacent pixels. Using collimated Co-57 and Ge-68 sources, we measured the count profiles and estimated the intrinsic spatial resolution of 350 μ m pitch detector biased at -1000 V. Depth of interaction was analyzed based on two methods, i.e., cathode/anode ratio and electron drift time, in both 122 keV and 511 keV measurements. For single-pixel photopeak events, a linear correlation between cathode/anode ratio and electron drift time was shown, which would be useful for estimating the DOI information and preserving image resolution in CdZnTe PET imaging applications.

3-D Spatial Resolution of 350 μm Pitch Pixelated CdZnTe Detectors for Imaging Applications

PubMed Central

Yin, Yongzhi; Chen, Ximeng; Wu, Heyu; Komarov, Sergey; Garson, Alfred; Li, Qiang; Guo, Qingzhen; Krawczynski, Henric; Meng, Ling-Jian; Tai, Yuan-Chuan

2016-01-01

We are currently investigating the feasibility of using highly pixelated Cadmium Zinc Telluride (CdZnTe) detectors for sub-500 μm resolution PET imaging applications. A 20 mm × 20 mm × 5 mm CdZnTe substrate was fabricated with 350 μm pitch pixels (250 μm anode pixels with 100 μm gap) and coplanar cathode. Charge sharing among the pixels of a 350 μm pitch detector was studied using collimated 122 keV and 511 keV gamma ray sources. For a 350 μm pitch CdZnTe detector, scatter plots of the charge signal of two neighboring pixels clearly show more charge sharing when the collimated beam hits the gap between adjacent pixels. Using collimated Co-57 and Ge-68 sources, we measured the count profiles and estimated the intrinsic spatial resolution of 350 μm pitch detector biased at −1000 V. Depth of interaction was analyzed based on two methods, i.e., cathode/anode ratio and electron drift time, in both 122 keV and 511 keV measurements. For single-pixel photopeak events, a linear correlation between cathode/anode ratio and electron drift time was shown, which would be useful for estimating the DOI information and preserving image resolution in CdZnTe PET imaging applications. PMID:28250476

Pixel Statistical Analysis of Diabetic vs. Non-diabetic Foot-Sole Spectral Terahertz Reflection Images

NASA Astrophysics Data System (ADS)

Hernandez-Cardoso, G. G.; Alfaro-Gomez, M.; Rojas-Landeros, S. C.; Salas-Gutierrez, I.; Castro-Camus, E.

2018-03-01

In this article, we present a series of hydration mapping images of the foot soles of diabetic and non-diabetic subjects measured by terahertz reflectance. In addition to the hydration images, we present a series of RYG-color-coded (red yellow green) images where pixels are assigned one of the three colors in order to easily identify areas in risk of ulceration. We also present the statistics of the number of pixels with each color as a potential quantitative indicator for diabetic foot-syndrome deterioration.

Microradiography with Semiconductor Pixel Detectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jakubek, Jan; Cejnarova, Andrea; Dammer, Jiri

High resolution radiography (with X-rays, neutrons, heavy charged particles, ...) often exploited also in tomographic mode to provide 3D images stands as a powerful imaging technique for instant and nondestructive visualization of fine internal structure of objects. Novel types of semiconductor single particle counting pixel detectors offer many advantages for radiation imaging: high detection efficiency, energy discrimination or direct energy measurement, noiseless digital integration (counting), high frame rate and virtually unlimited dynamic range. This article shows the application and potential of pixel detectors (such as Medipix2 or TimePix) in different fields of radiation imaging.

Wire Detection Algorithms for Navigation

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar; Camps, Octavia I.

2002-01-01

In this research we addressed the problem of obstacle detection for low altitude rotorcraft flight. In particular, the problem of detecting thin wires in the presence of image clutter and noise was studied. Wires present a serious hazard to rotorcrafts. Since they are very thin, their detection early enough so that the pilot has enough time to take evasive action is difficult, as their images can be less than one or two pixels wide. Two approaches were explored for this purpose. The first approach involved a technique for sub-pixel edge detection and subsequent post processing, in order to reduce the false alarms. After reviewing the line detection literature, an algorithm for sub-pixel edge detection proposed by Steger was identified as having good potential to solve the considered task. The algorithm was tested using a set of images synthetically generated by combining real outdoor images with computer generated wire images. The performance of the algorithm was evaluated both, at the pixel and the wire levels. It was observed that the algorithm performs well, provided that the wires are not too thin (or distant) and that some post processing is performed to remove false alarms due to clutter. The second approach involved the use of an example-based learning scheme namely, Support Vector Machines. The purpose of this approach was to explore the feasibility of an example-based learning based approach for the task of detecting wires from their images. Support Vector Machines (SVMs) have emerged as a promising pattern classification tool and have been used in various applications. It was found that this approach is not suitable for very thin wires and of course, not suitable at all for sub-pixel thick wires. High dimensionality of the data as such does not present a major problem for SVMs. However it is desirable to have a large number of training examples especially for high dimensional data. The main difficulty in using SVMs (or any other example-based learning method) is the need for a very good set of positive and negative examples since the performance depends on the quality of the training set.

Simultaneous measurement of cerebral blood flow and mRNA signals: pixel-based inter-modality correlational analysis.

PubMed

Zhao, W; Busto, R; Truettner, J; Ginsberg, M D

2001-07-30

The analysis of pixel-based relationships between local cerebral blood flow (LCBF) and mRNA expression can reveal important insights into brain function. Traditionally, LCBF and in situ hybridization studies for genes of interest have been analyzed in separate series. To overcome this limitation and to increase the power of statistical analysis, this study focused on developing a double-label method to measure local cerebral blood flow (LCBF) and gene expressions simultaneously by means of a dual-autoradiography procedure. A 14C-iodoantipyrine autoradiographic LCBF study was first performed. Serial brain sections (12 in this study) were obtained at multiple coronal levels and were processed in the conventional manner to yield quantitative LCBF images. Two replicate sections at each bregma level were then used for in situ hybridization. To eliminate the 14C-iodoantipyrine from these sections, a chloroform-washout procedure was first performed. The sections were then processed for in situ hybridization autoradiography for the probes of interest. This method was tested in Wistar rats subjected to 12 min of global forebrain ischemia by two-vessel occlusion plus hypotension, followed by 2 or 6 h of reperfusion (n=4-6 per group). LCBF and in situ hybridization images for heat shock protein 70 (HSP70) were generated for each rat, aligned by disparity analysis, and analyzed on a pixel-by-pixel basis. This method yielded detailed inter-modality correlation between LCBF and HSP70 mRNA expressions. The advantages of this method include reducing the number of experimental animals by one-half; and providing accurate pixel-based correlations between different modalities in the same animals, thus enabling paired statistical analyses. This method can be extended to permit correlation of LCBF with the expression of multiple genes of interest.

Modulation transfer function measurement technique for small-pixel detectors

NASA Technical Reports Server (NTRS)

Marchywka, Mike; Socker, Dennis G.

1992-01-01

A modulation transfer function (MTF) measurement technique suitable for large-format, small-pixel detector characterization has been investigated. A volume interference grating is used as a test image instead of the bar or sine wave target images normally used. This technique permits a high-contrast, large-area, sinusoidal intensity distribution to illuminate the device being tested, avoiding the need to deconvolve raw data with imaging system characteristics. A high-confidence MTF result at spatial frequencies near 200 cycles/mm is obtained. We present results at several visible light wavelengths with a 6.8-micron-pixel CCD. Pixel response functions are derived from the MTF results.

HST/WFC3: understanding and mitigating radiation damage effects in the CCD detectors

NASA Astrophysics Data System (ADS)

Baggett, S. M.; Anderson, J.; Sosey, M.; Gosmeyer, C.; Bourque, M.; Bajaj, V.; Khandrika, H.; Martlin, C.

2016-07-01

At the heart of the Hubble Space Telescope Wide Field Camera 3 (HST/WFC3) UVIS channel is a 4096x4096 pixel e2v CCD array. While these detectors continue to perform extremely well after more than 7 years in low-earth orbit, the cumulative effects of radiation damage are becoming increasingly evident. The result is a continual increase of the hotpixel population and the progressive loss in charge-transfer efficiency (CTE) over time. The decline in CTE has two effects: (1) it reduces the detected source flux as the defects trap charge during readout and (2) it systematically shifts source centroids as the trapped charge is later released. The flux losses can be significant, particularly for faint sources in low background images. In this report, we summarize the radiation damage effects seen in WFC3/UVIS and the evolution of the CTE losses as a function of time, source brightness, and image-background level. In addition, we discuss the available mitigation options, including target placement within the field of view, empirical stellar photometric corrections, post-flash mode and an empirical pixel-based CTE correction. The application of a post-flash has been remarkably effective in WFC3 at reducing CTE losses in low-background images for a relatively small noise penalty. Currently, all WFC3 observers are encouraged to consider post-flash for images with low backgrounds. Finally, a pixel-based CTE correction is available for use after the images have been acquired. Similar to the software in use in the HST Advanced Camera for Surveys (ACS) pipeline, the algorithm employs an observationally-defined model of how much charge is captured and released in order to reconstruct the image. As of Feb 2016, the pixel-based CTE correction is part of the automated WFC3 calibration pipeline. Observers with pre-existing data may request their images from MAST (Mikulski Archive for Space Telescopes) to obtain the improved products.

Position and time resolution measurements with a microchannel plate image intensifier: A comparison of monolithic and pixelated CeBr3 scintillators

NASA Astrophysics Data System (ADS)

Ackermann, Ulrich; Eschbaumer, Stephan; Bergmaier, Andreas; Egger, Werner; Sperr, Peter; Greubel, Christoph; Löwe, Benjamin; Schotanus, Paul; Dollinger, Günther

2016-07-01

To perform Four Dimensional Age Momentum Correlation measurements in the near future, where one obtains the positron lifetime in coincidence with the three dimensional momentum of the electron annihilating with the positron, we have investigated the time and position resolution of two CeBr3 scintillators (monolithic and an array of pixels) using a Photek IPD340/Q/BI/RS microchannel plate image intensifier. The microchannel plate image intensifier has an active diameter of 40 mm and a stack of two microchannel plates in chevron configuration. The monolithic CeBr3 scintillator was cylindrically shaped with a diameter of 40 mm and a height of 5 mm. The pixelated scintillator array covered the whole active area of the microchannel plate image intensifier and the shape of each pixel was 2.5·2.5·8 mm3 with a pixel pitch of 3.3 mm. For the monolithic setup the measured mean single time resolution was 330 ps (FWHM) at a gamma energy of 511 keV. No significant dependence on the position was detected. The position resolution at the center of the monolithic scintillator was about 2.5 mm (FWHM) at a gamma energy of 662 keV. The single time resolution of the pixelated crystal setup reached 320 ps (FWHM) in the region of the center of the active area of the microchannel plate image intensifier. The position resolution was limited by the cross-section of the pixels. The gamma energy for the pixel setup measurements was 511 keV.

Impulsive noise suppression in color images based on the geodesic digital paths

NASA Astrophysics Data System (ADS)

Smolka, Bogdan; Cyganek, Boguslaw

2015-02-01

In the paper a novel filtering design based on the concept of exploration of the pixel neighborhood by digital paths is presented. The paths start from the boundary of a filtering window and reach its center. The cost of transitions between adjacent pixels is defined in the hybrid spatial-color space. Then, an optimal path of minimum total cost, leading from pixels of the window's boundary to its center is determined. The cost of an optimal path serves as a degree of similarity of the central pixel to the samples from the local processing window. If a pixel is an outlier, then all the paths starting from the window's boundary will have high costs and the minimum one will also be high. The filter output is calculated as a weighted mean of the central pixel and an estimate constructed using the information on the minimum cost assigned to each image pixel. So, first the costs of optimal paths are used to build a smoothed image and in the second step the minimum cost of the central pixel is utilized for construction of the weights of a soft-switching scheme. The experiments performed on a set of standard color images, revealed that the efficiency of the proposed algorithm is superior to the state-of-the-art filtering techniques in terms of the objective restoration quality measures, especially for high noise contamination ratios. The proposed filter, due to its low computational complexity, can be applied for real time image denoising and also for the enhancement of video streams.

Automatic Sub-Pixel Co-Registration of LandSat-8 OLI and Sentinel-2A MSI Images Using Phase Correlation and Machine Learning Based Mapping

NASA Technical Reports Server (NTRS)

Skakun, Sergii; Roger, Jean-Claude; Vermote, Eric F.; Masek, Jeffrey G.; Justice, Christopher O.

2017-01-01

This study investigates misregistration issues between Landsat-8/OLI and Sentinel-2A/MSI at 30 m resolution, and between multi-temporal Sentinel-2A images at 10 m resolution using a phase correlation approach and multiple transformation functions. Co-registration of 45 Landsat-8 to Sentinel-2A pairs and 37 Sentinel-2A to Sentinel-2A pairs were analyzed. Phase correlation proved to be a robust approach that allowed us to identify hundreds and thousands of control points on images acquired more than 100 days apart. Overall, misregistration of up to 1.6 pixels at 30 m resolution between Landsat-8 and Sentinel-2A images, and 1.2 pixels and 2.8 pixels at 10 m resolution between multi-temporal Sentinel-2A images from the same and different orbits, respectively, were observed. The non-linear Random Forest regression used for constructing the mapping function showed best results in terms of root mean square error (RMSE), yielding an average RMSE error of 0.07+/-0.02 pixels at 30 m resolution, and 0.09+/-0.05 and 0.15+/-0.06 pixels at 10 m resolution for the same and adjacent Sentinel-2A orbits, respectively, for multiple tiles and multiple conditions. A simpler 1st order polynomial function (affine transformation) yielded RMSE of 0.08+/-0.02 pixels at 30 m resolution and 0.12+/-0.06 (same Sentinel-2A orbits) and 0.20+/-0.09 (adjacent orbits) pixels at 10 m resolution.

Highly Reflective Multi-stable Electrofluidic Display Pixels

NASA Astrophysics Data System (ADS)

Yang, Shu

Electronic papers (E-papers) refer to the displays that mimic the appearance of printed papers, but still owning the features of conventional electronic displays, such as the abilities of browsing websites and playing videos. The motivation of creating paper-like displays is inspired by the truths that reading on a paper caused least eye fatigue due to the paper's reflective and light diffusive nature, and, unlike the existing commercial displays, there is no cost of any form of energy for sustaining the displayed image. To achieve the equivalent visual effect of a paper print, an ideal E-paper has to be a highly reflective with good contrast ratio and full-color capability. To sustain the image with zero power consumption, the display pixels need to be bistable, which means the "on" and "off" states are both lowest energy states. Pixel can change its state only when sufficient external energy is given. There are many emerging technologies competing to demonstrate the first ideal E-paper device. However, none is able to achieve satisfactory visual effect, bistability and video speed at the same time. Challenges come from either the inherent physical/chemical properties or the fabrication process. Electrofluidic display is one of the most promising E-paper technologies. It has successfully demonstrated high reflectivity, brilliant color and video speed operation by moving colored pigment dispersion between visible and invisible places with electrowetting force. However, the pixel design did not allow the image bistability. Presented in this dissertation are the multi-stable electrofluidic display pixels that are able to sustain grayscale levels without any power consumption, while keeping the favorable features of the previous generation electrofluidic display. The pixel design, fabrication method using multiple layer dry film photoresist lamination, and physical/optical characterizations are discussed in details. Based on the pixel structure, the preliminary results of a simplified design and fabrication method are demonstrated. As advanced research topics regarding the device optical performance, firstly an optical model for evaluating reflective displays' light out-coupling efficiency is established to guide the pixel design; Furthermore, Aluminum surface diffusers are analytically modeled and then fabricated onto multi-stable electrofluidic display pixels to demonstrate truly "white" multi-stable electrofluidic display modules. The achieved results successfully promoted multi-stable electrofluidic display as excellent candidate for the ultimate E-paper device especially for larger scale signage applications.

Analysis of identification of digital images from a map of cosmic microwaves

NASA Astrophysics Data System (ADS)

Skeivalas, J.; Turla, V.; Jurevicius, M.; Viselga, G.

2018-04-01

This paper discusses identification of digital images from the cosmic microwave background radiation map formed according to the data of the European Space Agency "Planck" telescope by applying covariance functions and wavelet theory. The estimates of covariance functions of two digital images or single images are calculated according to the random functions formed of the digital images in the form of pixel vectors. The estimates of pixel vectors are formed on expansion of the pixel arrays of the digital images by a single vector. When the scale of a digital image is varied, the frequencies of single-pixel color waves remain constant and the procedure for calculation of covariance functions is not affected. For identification of the images, the RGB format spectrum has been applied. The impact of RGB spectrum components and the color tensor on the estimates of covariance functions was analyzed. The identity of digital images is assessed according to the changes in the values of the correlation coefficients in a certain range of values by applying the developed computer program.

Extracting Maximum Total Water Levels from Video "Brightest" Images

NASA Astrophysics Data System (ADS)

Brown, J. A.; Holman, R. A.; Stockdon, H. F.; Plant, N. G.; Long, J.; Brodie, K.

2016-02-01

An important parameter for predicting storm-induced coastal change is the maximum total water level (TWL). Most studies estimate the TWL as the sum of slowly varying water levels, including tides and storm surge, and the extreme runup parameter R2%, which includes wave setup and swash motions over minutes to seconds. Typically, R2% is measured using video remote sensing data, where cross-shore timestacks of pixel intensity are digitized to extract the horizontal runup timeseries. However, this technique must be repeated at multiple alongshore locations to resolve alongshore variability, and can be tedious and time consuming. We seek an efficient, video-based approach that yields a synoptic estimate of TWL that accounts for alongshore variability and can be applied during storms. In this work, the use of a video product termed the "brightest" image is tested; this represents the highest intensity of each pixel captured during a 10-minute collection period. Image filtering and edge detection techniques are applied to automatically determine the shoreward edge of the brightest region (i.e., the swash zone) at each alongshore pixel. The edge represents the horizontal position of the maximum TWL along the beach during the collection period, and is converted to vertical elevations using measured beach topography. This technique is evaluated using video and topographic data collected every half-hour at Duck, NC, during differing hydrodynamic conditions. Relationships between the maximum TWL estimates from the brightest images and various runup statistics computed using concurrent runup timestacks are examined, and errors associated with mapping the horizontal results to elevations are discussed. This technique is invaluable, as it can be used to routinely estimate maximum TWLs along a coastline from a single brightest image product, and provides a means for examining alongshore variability of TWLs at high alongshore resolution. These advantages will be useful in validating numerical hydrodynamic models and improving coastal change predictions.

Multi-Aperture-Based Probabilistic Noise Reduction of Random Telegraph Signal Noise and Photon Shot Noise in Semi-Photon-Counting Complementary-Metal-Oxide-Semiconductor Image Sensor

PubMed Central

Ishida, Haruki; Kagawa, Keiichiro; Komuro, Takashi; Zhang, Bo; Seo, Min-Woong; Takasawa, Taishi; Yasutomi, Keita; Kawahito, Shoji

2018-01-01

A probabilistic method to remove the random telegraph signal (RTS) noise and to increase the signal level is proposed, and was verified by simulation based on measured real sensor noise. Although semi-photon-counting-level (SPCL) ultra-low noise complementary-metal-oxide-semiconductor (CMOS) image sensors (CISs) with high conversion gain pixels have emerged, they still suffer from huge RTS noise, which is inherent to the CISs. The proposed method utilizes a multi-aperture (MA) camera that is composed of multiple sets of an SPCL CIS and a moderately fast and compact imaging lens to emulate a very fast single lens. Due to the redundancy of the MA camera, the RTS noise is removed by the maximum likelihood estimation where noise characteristics are modeled by the probability density distribution. In the proposed method, the photon shot noise is also relatively reduced because of the averaging effect, where the pixel values of all the multiple apertures are considered. An extremely low-light condition that the maximum number of electrons per aperture was the only 2e− was simulated. PSNRs of a test image for simple averaging, selective averaging (our previous method), and the proposed method were 11.92 dB, 11.61 dB, and 13.14 dB, respectively. The selective averaging, which can remove RTS noise, was worse than the simple averaging because it ignores the pixels with RTS noise and photon shot noise was less improved. The simulation results showed that the proposed method provided the best noise reduction performance. PMID:29587424

Facial recognition using simulated prosthetic pixelized vision.

PubMed

Thompson, Robert W; Barnett, G David; Humayun, Mark S; Dagnelie, Gislin

2003-11-01

To evaluate a model of simulated pixelized prosthetic vision using noncontiguous circular phosphenes, to test the effects of phosphene and grid parameters on facial recognition. A video headset was used to view a reference set of four faces, followed by a partially averted image of one of those faces viewed through a square pixelizing grid that contained 10x10 to 32x32 dots separated by gaps. The grid size, dot size, gap width, dot dropout rate, and gray-scale resolution were varied separately about a standard test condition, for a total of 16 conditions. All tests were first performed at 99% contrast and then repeated at 12.5% contrast. Discrimination speed and performance were influenced by all stimulus parameters. The subjects achieved highly significant facial recognition accuracy for all high-contrast tests except for grids with 70% random dot dropout and two gray levels. In low-contrast tests, significant facial recognition accuracy was achieved for all but the most adverse grid parameters: total grid area less than 17% of the target image, 70% dropout, four or fewer gray levels, and a gap of 40.5 arcmin. For difficult test conditions, a pronounced learning effect was noticed during high-contrast trials, and a more subtle practice effect on timing was evident during subsequent low-contrast trials. These findings suggest that reliable face recognition with crude pixelized grids can be learned and may be possible, even with a crude visual prosthesis.

Dual-gate photo thin-film transistor: a “smart” pixel for high- resolution and low-dose X-ray imaging

NASA Astrophysics Data System (ADS)

Wang, Kai; Ou, Hai; Chen, Jun

2015-06-01

Since its emergence a decade ago, amorphous silicon flat panel X-ray detector has established itself as a ubiquitous platform for an array of digital radiography modalities. The fundamental building block of a flat panel detector is called a pixel. In all current pixel architectures, sensing, storage, and readout are unanimously kept separate, inevitably compromising resolution by increasing pixel size. To address this issue, we hereby propose a “smart” pixel architecture where the aforementioned three components are combined in a single dual-gate photo thin-film transistor (TFT). In other words, the dual-gate photo TFT itself functions as a sensor, a storage capacitor, and a switch concurrently. Additionally, by harnessing the amplification effect of such a thin-film transistor, we for the first time created a single-transistor active pixel sensor. The proof-of-concept device had a W/L ratio of 250μm/20μm and was fabricated using a simple five-mask photolithography process, where a 130nm transparent ITO was used as the top photo gate, and a 200nm amorphous silicon as the absorbing channel layer. The preliminary results demonstrated that the photocurrent had been increased by four orders of magnitude due to light-induced threshold voltage shift in the sub-threshold region. The device sensitivity could be simply tuned by photo gate bias to specifically target low-level light detection. The dependence of threshold voltage on light illumination indicated that a dynamic range of at least 80dB could be achieved. The "smart" pixel technology holds tremendous promise for developing high-resolution and low-dose X-ray imaging and may potentially lower the cancer risk imposed by radiation, especially among paediatric patients.

It's not the pixel count, you fool

NASA Astrophysics Data System (ADS)

Kriss, Michael A.

2012-01-01

The first thing a "marketing guy" asks the digital camera engineer is "how many pixels does it have, for we need as many mega pixels as possible since the other guys are killing us with their "umpteen" mega pixel pocket sized digital cameras. And so it goes until the pixels get smaller and smaller in order to inflate the pixel count in the never-ending pixel-wars. These small pixels just are not very good. The truth of the matter is that the most important feature of digital cameras in the last five years is the automatic motion control to stabilize the image on the sensor along with some very sophisticated image processing. All the rest has been hype and some "cool" design. What is the future for digital imaging and what will drive growth of camera sales (not counting the cell phone cameras which totally dominate the market in terms of camera sales) and more importantly after sales profits? Well sit in on the Dark Side of Color and find out what is being done to increase the after sales profits and don't be surprised if has been done long ago in some basement lab of a photographic company and of course, before its time.

SU-C-206-03: Metal Artifact Reduction in X-Ray Computed Tomography Based On Local Anatomical Similarity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, X; Yang, X; Rosenfield, J

Purpose: Metal implants such as orthopedic hardware and dental fillings cause severe bright and dark streaking in reconstructed CT images. These artifacts decrease image contrast and degrade HU accuracy, leading to inaccuracies in target delineation and dose calculation. Additionally, such artifacts negatively impact patient set-up in image guided radiation therapy (IGRT). In this work, we propose a novel method for metal artifact reduction which utilizes the anatomical similarity between neighboring CT slices. Methods: Neighboring CT slices show similar anatomy. Based on this anatomical similarity, the proposed method replaces corrupted CT pixels with pixels from adjacent, artifact-free slices. A gamma map,more » which is the weighted summation of relative HU error and distance error, is calculated for each pixel in the artifact-corrupted CT image. The minimum value in each pixel’s gamma map is used to identify a pixel from the adjacent CT slice to replace the corresponding artifact-corrupted pixel. This replacement only occurs if the minimum value in a particular pixel’s gamma map is larger than a threshold. The proposed method was evaluated with clinical images. Results: Highly attenuating dental fillings and hip implants cause severe streaking artifacts on CT images. The proposed method eliminates the dark and bright streaking and improves the implant delineation and visibility. In particular, the image non-uniformity in the central region of interest was reduced from 1.88 and 1.01 to 0.28 and 0.35, respectively. Further, the mean CT HU error was reduced from 328 HU and 460 HU to 60 HU and 36 HU, respectively. Conclusions: The proposed metal artifact reduction method replaces corrupted image pixels with pixels from neighboring slices that are free of metal artifacts. This method proved capable of suppressing streaking artifacts, improving HU accuracy and image detectability.« less

Photon-counting hexagonal pixel array CdTe detector: Spatial resolution characteristics for image-guided interventional applications

PubMed Central

Shrestha, Suman; Karellas, Andrew; Shi, Linxi; Gounis, Matthew J.; Bellazzini, Ronaldo; Spandre, Gloria; Brez, Alessandro; Minuti, Massimo

2016-01-01

Purpose: High-resolution, photon-counting, energy-resolved detector with fast-framing capability can facilitate simultaneous acquisition of precontrast and postcontrast images for subtraction angiography without pixel registration artifacts and can facilitate high-resolution real-time imaging during image-guided interventions. Hence, this study was conducted to determine the spatial resolution characteristics of a hexagonal pixel array photon-counting cadmium telluride (CdTe) detector. Methods: A 650 μm thick CdTe Schottky photon-counting detector capable of concurrently acquiring up to two energy-windowed images was operated in a single energy-window mode to include photons of 10 keV or higher. The detector had hexagonal pixels with apothem of 30 μm resulting in pixel pitch of 60 and 51.96 μm along the two orthogonal directions. The detector was characterized at IEC-RQA5 spectral conditions. Linear response of the detector was determined over the air kerma rate relevant to image-guided interventional procedures ranging from 1.3 nGy/frame to 91.4 μGy/frame. Presampled modulation transfer was determined using a tungsten edge test device. The edge-spread function and the finely sampled line spread function accounted for hexagonal sampling, from which the presampled modulation transfer function (MTF) was determined. Since detectors with hexagonal pixels require resampling to square pixels for distortion-free display, the optimal square pixel size was determined by minimizing the root-mean-squared-error of the aperture functions for the square and hexagonal pixels up to the Nyquist limit. Results: At Nyquist frequencies of 8.33 and 9.62 cycles/mm along the apothem and orthogonal to the apothem directions, the modulation factors were 0.397 and 0.228, respectively. For the corresponding axis, the limiting resolution defined as 10% MTF occurred at 13.3 and 12 cycles/mm, respectively. Evaluation of the aperture functions yielded an optimal square pixel size of 54 μm. After resampling to 54 μm square pixels using trilinear interpolation, the presampled MTF at Nyquist frequency of 9.26 cycles/mm was 0.29 and 0.24 along the orthogonal directions and the limiting resolution (10% MTF) occurred at approximately 12 cycles/mm. Visual analysis of a bar pattern image showed the ability to resolve close to 12 line-pairs/mm and qualitative evaluation of a neurovascular nitinol-stent showed the ability to visualize its struts at clinically relevant conditions. Conclusions: Hexagonal pixel array photon-counting CdTe detector provides high spatial resolution in single-photon counting mode. After resampling to optimal square pixel size for distortion-free display, the spatial resolution is preserved. The dual-energy capabilities of the detector could allow for artifact-free subtraction angiography and basis material decomposition. The proposed high-resolution photon-counting detector with energy-resolving capability can be of importance for several image-guided interventional procedures as well as for pediatric applications. PMID:27147324

Photon-counting hexagonal pixel array CdTe detector: Spatial resolution characteristics for image-guided interventional applications.

PubMed

Vedantham, Srinivasan; Shrestha, Suman; Karellas, Andrew; Shi, Linxi; Gounis, Matthew J; Bellazzini, Ronaldo; Spandre, Gloria; Brez, Alessandro; Minuti, Massimo

2016-05-01

High-resolution, photon-counting, energy-resolved detector with fast-framing capability can facilitate simultaneous acquisition of precontrast and postcontrast images for subtraction angiography without pixel registration artifacts and can facilitate high-resolution real-time imaging during image-guided interventions. Hence, this study was conducted to determine the spatial resolution characteristics of a hexagonal pixel array photon-counting cadmium telluride (CdTe) detector. A 650 μm thick CdTe Schottky photon-counting detector capable of concurrently acquiring up to two energy-windowed images was operated in a single energy-window mode to include photons of 10 keV or higher. The detector had hexagonal pixels with apothem of 30 μm resulting in pixel pitch of 60 and 51.96 μm along the two orthogonal directions. The detector was characterized at IEC-RQA5 spectral conditions. Linear response of the detector was determined over the air kerma rate relevant to image-guided interventional procedures ranging from 1.3 nGy/frame to 91.4 μGy/frame. Presampled modulation transfer was determined using a tungsten edge test device. The edge-spread function and the finely sampled line spread function accounted for hexagonal sampling, from which the presampled modulation transfer function (MTF) was determined. Since detectors with hexagonal pixels require resampling to square pixels for distortion-free display, the optimal square pixel size was determined by minimizing the root-mean-squared-error of the aperture functions for the square and hexagonal pixels up to the Nyquist limit. At Nyquist frequencies of 8.33 and 9.62 cycles/mm along the apothem and orthogonal to the apothem directions, the modulation factors were 0.397 and 0.228, respectively. For the corresponding axis, the limiting resolution defined as 10% MTF occurred at 13.3 and 12 cycles/mm, respectively. Evaluation of the aperture functions yielded an optimal square pixel size of 54 μm. After resampling to 54 μm square pixels using trilinear interpolation, the presampled MTF at Nyquist frequency of 9.26 cycles/mm was 0.29 and 0.24 along the orthogonal directions and the limiting resolution (10% MTF) occurred at approximately 12 cycles/mm. Visual analysis of a bar pattern image showed the ability to resolve close to 12 line-pairs/mm and qualitative evaluation of a neurovascular nitinol-stent showed the ability to visualize its struts at clinically relevant conditions. Hexagonal pixel array photon-counting CdTe detector provides high spatial resolution in single-photon counting mode. After resampling to optimal square pixel size for distortion-free display, the spatial resolution is preserved. The dual-energy capabilities of the detector could allow for artifact-free subtraction angiography and basis material decomposition. The proposed high-resolution photon-counting detector with energy-resolving capability can be of importance for several image-guided interventional procedures as well as for pediatric applications.

CMOS Active-Pixel Image Sensor With Simple Floating Gates

NASA Technical Reports Server (NTRS)

Fossum, Eric R.; Nakamura, Junichi; Kemeny, Sabrina E.

1996-01-01

Experimental complementary metal-oxide/semiconductor (CMOS) active-pixel image sensor integrated circuit features simple floating-gate structure, with metal-oxide/semiconductor field-effect transistor (MOSFET) as active circuit element in each pixel. Provides flexibility of readout modes, no kTC noise, and relatively simple structure suitable for high-density arrays. Features desirable for "smart sensor" applications.

Polarization-Analyzing CMOS Image Sensor With Monolithically Embedded Polarizer for Microchemistry Systems.

PubMed

Tokuda, T; Yamada, H; Sasagawa, K; Ohta, J

2009-10-01

This paper proposes and demonstrates a polarization-analyzing CMOS sensor based on image sensor architecture. The sensor was designed targeting applications for chiral analysis in a microchemistry system. The sensor features a monolithically embedded polarizer. Embedded polarizers with different angles were implemented to realize a real-time absolute measurement of the incident polarization angle. Although the pixel-level performance was confirmed to be limited, estimation schemes based on the variation of the polarizer angle provided a promising performance for real-time polarization measurements. An estimation scheme using 180 pixels in a 1deg step provided an estimation accuracy of 0.04deg. Polarimetric measurements of chiral solutions were also successfully performed to demonstrate the applicability of the sensor to optical chiral analysis.

Providing integrity, authenticity, and confidentiality for header and pixel data of DICOM images.

PubMed

Al-Haj, Ali

2015-04-01

Exchange of medical images over public networks is subjected to different types of security threats. This has triggered persisting demands for secured telemedicine implementations that will provide confidentiality, authenticity, and integrity for the transmitted images. The medical image exchange standard (DICOM) offers mechanisms to provide confidentiality for the header data of the image but not for the pixel data. On the other hand, it offers mechanisms to achieve authenticity and integrity for the pixel data but not for the header data. In this paper, we propose a crypto-based algorithm that provides confidentially, authenticity, and integrity for the pixel data, as well as for the header data. This is achieved by applying strong cryptographic primitives utilizing internally generated security data, such as encryption keys, hashing codes, and digital signatures. The security data are generated internally from the header and the pixel data, thus a strong bond is established between the DICOM data and the corresponding security data. The proposed algorithm has been evaluated extensively using DICOM images of different modalities. Simulation experiments show that confidentiality, authenticity, and integrity have been achieved as reflected by the results we obtained for normalized correlation, entropy, PSNR, histogram analysis, and robustness.

Pixel-super-resolved lensfree holography using adaptive relaxation factor and positional error correction

NASA Astrophysics Data System (ADS)

Zhang, Jialin; Chen, Qian; Sun, Jiasong; Li, Jiaji; Zuo, Chao

2018-01-01

Lensfree holography provides a new way to effectively bypass the intrinsical trade-off between the spatial resolution and field-of-view (FOV) of conventional lens-based microscopes. Unfortunately, due to the limited sensor pixel-size, unpredictable disturbance during image acquisition, and sub-optimum solution to the phase retrieval problem, typical lensfree microscopes only produce compromised imaging quality in terms of lateral resolution and signal-to-noise ratio (SNR). In this paper, we propose an adaptive pixel-super-resolved lensfree imaging (APLI) method to address the pixel aliasing problem by Z-scanning only, without resorting to subpixel shifting or beam-angle manipulation. Furthermore, an automatic positional error correction algorithm and adaptive relaxation strategy are introduced to enhance the robustness and SNR of reconstruction significantly. Based on APLI, we perform full-FOV reconstruction of a USAF resolution target across a wide imaging area of {29.85 mm2 and achieve half-pitch lateral resolution of 770 nm, surpassing 2.17 times of the theoretical Nyquist-Shannon sampling resolution limit imposed by the sensor pixel-size (1.67 μm). Full-FOV imaging result of a typical dicot root is also provided to demonstrate its promising potential applications in biologic imaging.

Object-based classification of earthquake damage from high-resolution optical imagery using machine learning

NASA Astrophysics Data System (ADS)

Bialas, James; Oommen, Thomas; Rebbapragada, Umaa; Levin, Eugene

2016-07-01

Object-based approaches in the segmentation and classification of remotely sensed images yield more promising results compared to pixel-based approaches. However, the development of an object-based approach presents challenges in terms of algorithm selection and parameter tuning. Subjective methods are often used, but yield less than optimal results. Objective methods are warranted, especially for rapid deployment in time-sensitive applications, such as earthquake damage assessment. Herein, we used a systematic approach in evaluating object-based image segmentation and machine learning algorithms for the classification of earthquake damage in remotely sensed imagery. We tested a variety of algorithms and parameters on post-event aerial imagery for the 2011 earthquake in Christchurch, New Zealand. Results were compared against manually selected test cases representing different classes. In doing so, we can evaluate the effectiveness of the segmentation and classification of different classes and compare different levels of multistep image segmentations. Our classifier is compared against recent pixel-based and object-based classification studies for postevent imagery of earthquake damage. Our results show an improvement against both pixel-based and object-based methods for classifying earthquake damage in high resolution, post-event imagery.

IMDISP - INTERACTIVE IMAGE DISPLAY PROGRAM

NASA Technical Reports Server (NTRS)

Martin, M. D.

1994-01-01

The Interactive Image Display Program (IMDISP) is an interactive image display utility for the IBM Personal Computer (PC, XT and AT) and compatibles. Until recently, efforts to utilize small computer systems for display and analysis of scientific data have been hampered by the lack of sufficient data storage capacity to accomodate large image arrays. Most planetary images, for example, require nearly a megabyte of storage. The recent development of the "CDROM" (Compact Disk Read-Only Memory) storage technology makes possible the storage of up to 680 megabytes of data on a single 4.72-inch disk. IMDISP was developed for use with the CDROM storage system which is currently being evaluated by the Planetary Data System. The latest disks to be produced by the Planetary Data System are a set of three disks containing all of the images of Uranus acquired by the Voyager spacecraft. The images are in both compressed and uncompressed format. IMDISP can read the uncompressed images directly, but special software is provided to decompress the compressed images, which can not be processed directly. IMDISP can also display images stored on floppy or hard disks. A digital image is a picture converted to numerical form so that it can be stored and used in a computer. The image is divided into a matrix of small regions called picture elements, or pixels. The rows and columns of pixels are called "lines" and "samples", respectively. Each pixel has a numerical value, or DN (data number) value, quantifying the darkness or brightness of the image at that spot. In total, each pixel has an address (line number, sample number) and a DN value, which is all that the computer needs for processing. DISPLAY commands allow the IMDISP user to display all or part of an image at various positions on the display screen. The user may also zoom in and out from a point on the image defined by the cursor, and may pan around the image. To enable more or all of the original image to be displayed on the screen at once, the image can be "subsampled." For example, if the image were subsampled by a factor of 2, every other pixel from every other line would be displayed, starting from the upper left corner of the image. Any positive integer may be used for subsampling. The user may produce a histogram of an image file, which is a graph showing the number of pixels per DN value, or per range of DN values, for the entire image. IMDISP can also plot the DN value versus pixels along a line between two points on the image. The user can "stretch" or increase the contrast of an image by specifying low and high DN values; all pixels with values lower than the specified "low" will then become black, and all pixels higher than the specified "high" value will become white. Pixels between the low and high values will be evenly shaded between black and white. IMDISP is written in a modular form to make it easy to change it to work with different display devices or on other computers. The code can also be adapted for use in other application programs. There are device dependent image display modules, general image display subroutines, image I/O routines, and image label and command line parsing routines. The IMDISP system is written in C-language (94%) and Assembler (6%). It was implemented on an IBM PC with the MS DOS 3.21 operating system. IMDISP has a memory requirement of about 142k bytes. IMDISP was developed in 1989 and is a copyrighted work with all copyright vested in NASA. Additional planetary images can be obtained from the National Space Science Data Center at (301) 286-6695.

Image-based metal artifact reduction in x-ray computed tomography utilizing local anatomical similarity

NASA Astrophysics Data System (ADS)

Dong, Xue; Yang, Xiaofeng; Rosenfield, Jonathan; Elder, Eric; Dhabaan, Anees

2017-03-01

X-ray computed tomography (CT) is widely used in radiation therapy treatment planning in recent years. However, metal implants such as dental fillings and hip prostheses can cause severe bright and dark streaking artifacts in reconstructed CT images. These artifacts decrease image contrast and degrade HU accuracy, leading to inaccuracies in target delineation and dose calculation. In this work, a metal artifact reduction method is proposed based on the intrinsic anatomical similarity between neighboring CT slices. Neighboring CT slices from the same patient exhibit similar anatomical features. Exploiting this anatomical similarity, a gamma map is calculated as a weighted summation of relative HU error and distance error for each pixel in an artifact-corrupted CT image relative to a neighboring, artifactfree image. The minimum value in the gamma map for each pixel is used to identify an appropriate pixel from the artifact-free CT slice to replace the corresponding artifact-corrupted pixel. With the proposed method, the mean CT HU error was reduced from 360 HU and 460 HU to 24 HU and 34 HU on head and pelvis CT images, respectively. Dose calculation accuracy also improved, as the dose difference was reduced from greater than 20% to less than 4%. Using 3%/3mm criteria, the gamma analysis failure rate was reduced from 23.25% to 0.02%. An image-based metal artifact reduction method is proposed that replaces corrupted image pixels with pixels from neighboring CT slices free of metal artifacts. This method is shown to be capable of suppressing streaking artifacts, thereby improving HU and dose calculation accuracy.

A comparison of FIA plot data derived from image pixels and image objects

Treesearch

Charles E. Werstak

2012-01-01

The use of Forest Inventory and Analysis (FIA) plot data for producing continuous and thematic maps of forest attributes (e.g., forest type, canopy cover, volume, and biomass) at the regional level from satellite imagery can be challenging due to differences in scale. Specifically, classification errors that may result from assumptions made between what the field data...

Automatic sub-pixel coastline extraction based on spectral mixture analysis using EO-1 Hyperion data

NASA Astrophysics Data System (ADS)

Hong, Zhonghua; Li, Xuesu; Han, Yanling; Zhang, Yun; Wang, Jing; Zhou, Ruyan; Hu, Kening

2018-06-01

Many megacities (such as Shanghai) are located in coastal areas, therefore, coastline monitoring is critical for urban security and urban development sustainability. A shoreline is defined as the intersection between coastal land and a water surface and features seawater edge movements as tides rise and fall. Remote sensing techniques have increasingly been used for coastline extraction; however, traditional hard classification methods are performed only at the pixel-level and extracting subpixel accuracy using soft classification methods is both challenging and time consuming due to the complex features in coastal regions. This paper presents an automatic sub-pixel coastline extraction method (ASPCE) from high-spectral satellite imaging that performs coastline extraction based on spectral mixture analysis and, thus, achieves higher accuracy. The ASPCE method consists of three main components: 1) A Water- Vegetation-Impervious-Soil (W-V-I-S) model is first presented to detect mixed W-V-I-S pixels and determine the endmember spectra in coastal regions; 2) The linear spectral mixture unmixing technique based on Fully Constrained Least Squares (FCLS) is applied to the mixed W-V-I-S pixels to estimate seawater abundance; and 3) The spatial attraction model is used to extract the coastline. We tested this new method using EO-1 images from three coastal regions in China: the South China Sea, the East China Sea, and the Bohai Sea. The results showed that the method is accurate and robust. Root mean square error (RMSE) was utilized to evaluate the accuracy by calculating the distance differences between the extracted coastline and the digitized coastline. The classifier's performance was compared with that of the Multiple Endmember Spectral Mixture Analysis (MESMA), Mixture Tuned Matched Filtering (MTMF), Sequential Maximum Angle Convex Cone (SMACC), Constrained Energy Minimization (CEM), and one classical Normalized Difference Water Index (NDWI). The results from the three test sites indicated that the proposed ASPCE method extracted coastlines more efficiently than did the compared methods, and its coastline extraction accuracy corresponded closely to the digitized coastline, with 0.39 pixels, 0.40 pixels, and 0.35 pixels in the three test regions, showing that the ASPCE method achieves an accuracy below 12.0 m (0.40 pixels). Moreover, in the quantitative accuracy assessment for the three test sites, the ASPCE method shows the best performance in coastline extraction, achieving a 0.35 pixel-level at the Bohai Sea, China test site. Therefore, the proposed ASPCE method can extract coastline more accurately than can the hard classification methods or other spectral unmixing methods.

Sub-pixel spatial resolution wavefront phase imaging

NASA Technical Reports Server (NTRS)

Stahl, H. Philip (Inventor); Mooney, James T. (Inventor)

2012-01-01

A phase imaging method for an optical wavefront acquires a plurality of phase images of the optical wavefront using a phase imager. Each phase image is unique and is shifted with respect to another of the phase images by a known/controlled amount that is less than the size of the phase imager's pixels. The phase images are then combined to generate a single high-spatial resolution phase image of the optical wavefront.

Using the Standard Deviation of a Region of Interest in an Image to Estimate Camera to Emitter Distance

PubMed Central

Cano-García, Angel E.; Lazaro, José Luis; Infante, Arturo; Fernández, Pedro; Pompa-Chacón, Yamilet; Espinoza, Felipe

2012-01-01

In this study, a camera to infrared diode (IRED) distance estimation problem was analyzed. The main objective was to define an alternative to measures depth only using the information extracted from pixel grey levels of the IRED image to estimate the distance between the camera and the IRED. In this paper, the standard deviation of the pixel grey level in the region of interest containing the IRED image is proposed as an empirical parameter to define a model for estimating camera to emitter distance. This model includes the camera exposure time, IRED radiant intensity and the distance between the camera and the IRED. An expression for the standard deviation model related to these magnitudes was also derived and calibrated using different images taken under different conditions. From this analysis, we determined the optimum parameters to ensure the best accuracy provided by this alternative. Once the model calibration had been carried out, a differential method to estimate the distance between the camera and the IRED was defined and applied, considering that the camera was aligned with the IRED. The results indicate that this method represents a useful alternative for determining the depth information. PMID:22778608

Using the standard deviation of a region of interest in an image to estimate camera to emitter distance.

PubMed

Cano-García, Angel E; Lazaro, José Luis; Infante, Arturo; Fernández, Pedro; Pompa-Chacón, Yamilet; Espinoza, Felipe

2012-01-01

In this study, a camera to infrared diode (IRED) distance estimation problem was analyzed. The main objective was to define an alternative to measures depth only using the information extracted from pixel grey levels of the IRED image to estimate the distance between the camera and the IRED. In this paper, the standard deviation of the pixel grey level in the region of interest containing the IRED image is proposed as an empirical parameter to define a model for estimating camera to emitter distance. This model includes the camera exposure time, IRED radiant intensity and the distance between the camera and the IRED. An expression for the standard deviation model related to these magnitudes was also derived and calibrated using different images taken under different conditions. From this analysis, we determined the optimum parameters to ensure the best accuracy provided by this alternative. Once the model calibration had been carried out, a differential method to estimate the distance between the camera and the IRED was defined and applied, considering that the camera was aligned with the IRED. The results indicate that this method represents a useful alternative for determining the depth information.

Level set segmentation of medical images based on local region statistics and maximum a posteriori probability.

PubMed

Cui, Wenchao; Wang, Yi; Lei, Tao; Fan, Yangyu; Feng, Yan

2013-01-01

This paper presents a variational level set method for simultaneous segmentation and bias field estimation of medical images with intensity inhomogeneity. In our model, the statistics of image intensities belonging to each different tissue in local regions are characterized by Gaussian distributions with different means and variances. According to maximum a posteriori probability (MAP) and Bayes' rule, we first derive a local objective function for image intensities in a neighborhood around each pixel. Then this local objective function is integrated with respect to the neighborhood center over the entire image domain to give a global criterion. In level set framework, this global criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, image segmentation and bias field estimation are simultaneously achieved via a level set evolution process. Experimental results for synthetic and real images show desirable performances of our method.

Crack image segmentation based on improved DBC method

NASA Astrophysics Data System (ADS)

Cao, Ting; Yang, Nan; Wang, Fengping; Gao, Ting; Wang, Weixing

2017-11-01

With the development of computer vision technology, crack detection based on digital image segmentation method arouses global attentions among researchers and transportation ministries. Since the crack always exhibits the random shape and complex texture, it is still a challenge to accomplish reliable crack detection results. Therefore, a novel crack image segmentation method based on fractal DBC (differential box counting) is introduced in this paper. The proposed method can estimate every pixel fractal feature based on neighborhood information which can consider the contribution from all possible direction in the related block. The block moves just one pixel every time so that it could cover all the pixels in the crack image. Unlike the classic DBC method which only describes fractal feature for the related region, this novel method can effectively achieve crack image segmentation according to the fractal feature of every pixel. The experiment proves the proposed method can achieve satisfactory results in crack detection.

Fast, Deep-Record-Length, Fiber-Coupled Photodiode Imaging Array for Plasma Diagnostics

NASA Astrophysics Data System (ADS)

Brockington, Samuel; Case, Andrew; Witherspoon, F. Douglas

2014-10-01

HyperV Technologies has been developing an imaging diagnostic comprised of an array of fast, low-cost, long-record-length, fiber-optically-coupled photodiode channels to investigate plasma dynamics and other fast, bright events. By coupling an imaging fiber bundle to a bank of amplified photodiode channels, imagers and streak imagers of 100 to 1000 pixels can be constructed. By interfacing analog photodiode systems directly to commercial analog-to-digital converters and modern memory chips, a prototype 100 pixel array with an extremely deep record length (128 k points at 20 Msamples/s) and 10 bit pixel resolution has already been achieved. HyperV now seeks to extend these techniques to construct a prototype 1000 Pixel framing camera with up to 100 Msamples/sec rate and 10 to 12 bit depth. Preliminary experimental results as well as Phase 2 plans will be discussed. Work supported by USDOE Phase 2 SBIR Grant DE-SC0009492.

Active Pixel Sensors: Are CCD's Dinosaurs?

NASA Technical Reports Server (NTRS)

Fossum, Eric R.

1993-01-01

Charge-coupled devices (CCD's) are presently the technology of choice for most imaging applications. In the 23 years since their invention in 1970, they have evolved to a sophisticated level of performance. However, as with all technologies, we can be certain that they will be supplanted someday. In this paper, the Active Pixel Sensor (APS) technology is explored as a possible successor to the CCD. An active pixel is defined as a detector array technology that has at least one active transistor within the pixel unit cell. The APS eliminates the need for nearly perfect charge transfer -- the Achilles' heel of CCDs. This perfect charge transfer makes CCD's radiation 'soft,' difficult to use under low light conditions, difficult to manufacture in large array sizes, difficult to integrate with on-chip electronics, difficult to use at low temperatures, difficult to use at high frame rates, and difficult to manufacture in non-silicon materials that extend wavelength response.

Controlled power delivery for super-resolution imaging of biological samples using digital micromirror device

NASA Astrophysics Data System (ADS)

Valiya Peedikakkal, Liyana; Cadby, Ashley

2017-02-01

Localization based super resolution images of a biological sample is generally achieved by using high power laser illumination with long exposure time which unfortunately increases photo-toxicity of a sample, making super resolution microscopy, in general, incompatible with live cell imaging. Furthermore, the limitation of photobleaching reduces the ability to acquire time lapse images of live biological cells using fluorescence microscopy. Digital Light Processing (DLP) technology can deliver light at grey scale levels by flickering digital micromirrors at around 290 Hz enabling highly controlled power delivery to samples. In this work, Digital Micromirror Device (DMD) is implemented in an inverse Schiefspiegler telescope setup to control the power and pattern of illumination for super resolution microscopy. We can achieve spatial and temporal patterning of illumination by controlling the DMD pixel by pixel. The DMD allows us to control the power and spatial extent of the laser illumination. We have used this to show that we can reduce the power delivered to the sample to allow for longer time imaging in one area while achieving sub-diffraction STORM imaging in another using higher power densities.

Vehicle counting system using real-time video processing

NASA Astrophysics Data System (ADS)

Crisóstomo-Romero, Pedro M.

2006-02-01

Transit studies are important for planning a road network with optimal vehicular flow. A vehicular count is essential. This article presents a vehicle counting system based on video processing. An advantage of such system is the greater detail than is possible to obtain, like shape, size and speed of vehicles. The system uses a video camera placed above the street to image transit in real-time. The video camera must be placed at least 6 meters above the street level to achieve proper acquisition quality. Fast image processing algorithms and small image dimensions are used to allow real-time processing. Digital filters, mathematical morphology, segmentation and other techniques allow identifying and counting all vehicles in the image sequences. The system was implemented under Linux in a 1.8 GHz Pentium 4 computer. A successful count was obtained with frame rates of 15 frames per second for images of size 240x180 pixels and 24 frames per second for images of size 180x120 pixels, thus being able to count vehicles whose speeds do not exceed 150 km/h.

Programmable remapper for image processing

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Inventor); Sampsell, Jeffrey B. (Inventor)

1991-01-01

A video-rate coordinate remapper includes a memory for storing a plurality of transformations on look-up tables for remapping input images from one coordinate system to another. Such transformations are operator selectable. The remapper includes a collective processor by which certain input pixels of an input image are transformed to a portion of the output image in a many-to-one relationship. The remapper includes an interpolative processor by which the remaining input pixels of the input image are transformed to another portion of the output image in a one-to-many relationship. The invention includes certain specific transforms for creating output images useful for certain defects of visually impaired people. The invention also includes means for shifting input pixels and means for scrolling the output matrix.

Novel spectral imaging system combining spectroscopy with imaging applications for biology

NASA Astrophysics Data System (ADS)

Malik, Zvi; Cabib, Dario; Buckwald, Robert A.; Garini, Yuval; Soenksen, Dirk G.

1995-02-01

A novel analytical spectral-imaging system and its results in the examination of biological specimens are presented. The SpectraCube 1000 system measures the transmission, absorbance, or fluorescence spectra of images studied by light microscopy. The system is based on an interferometer combined with a CCD camera, enabling measurement of the interferogram for each pixel constructing the image. Fourier transformation of the interferograms derives pixel by pixel spectra for 170 X 170 pixels of the image. A special `similarity mapping' program has been developed, enabling comparisons of spectral algorithms of all the spatial and spectral information measured by the system in the image. By comparing the spectrum of each pixel in the specimen with a selected reference spectrum (similarity mapping), there is a depiction of the spatial distribution of macromolecules possessing the characteristics of the reference spectrum. The system has been applied to analyses of bone marrow blood cells as well as fluorescent specimens, and has revealed information which could not be unveiled by other techniques. Similarity mapping has enabled visualization of fine details of chromatin packing in the nucleus of cells and other cytoplasmic compartments. Fluorescence analysis by the system has enabled the determination of porphyrin concentrations and distribution in cytoplasmic organelles of living cells.

Single Pixel Black Phosphorus Photodetector for Near-Infrared Imaging.

PubMed

Miao, Jinshui; Song, Bo; Xu, Zhihao; Cai, Le; Zhang, Suoming; Dong, Lixin; Wang, Chuan

2018-01-01

Infrared imaging systems have wide range of military or civil applications and 2D nanomaterials have recently emerged as potential sensing materials that may outperform conventional ones such as HgCdTe, InGaAs, and InSb. As an example, 2D black phosphorus (BP) thin film has a thickness-dependent direct bandgap with low shot noise and noncryogenic operation for visible to mid-infrared photodetection. In this paper, the use of a single-pixel photodetector made with few-layer BP thin film for near-infrared imaging applications is demonstrated. The imaging is achieved by combining the photodetector with a digital micromirror device to encode and subsequently reconstruct the image based on compressive sensing algorithm. Stationary images of a near-infrared laser spot (λ = 830 nm) with up to 64 × 64 pixels are captured using this single-pixel BP camera with 2000 times of measurements, which is only half of the total number of pixels. The imaging platform demonstrated in this work circumvents the grand challenges of scalable BP material growth for photodetector array fabrication and shows the efficacy of utilizing the outstanding performance of BP photodetector for future high-speed infrared camera applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Sub-pixel mapping of hyperspectral imagery using super-resolution

NASA Astrophysics Data System (ADS)

Sharma, Shreya; Sharma, Shakti; Buddhiraju, Krishna M.

2016-04-01

With the development of remote sensing technologies, it has become possible to obtain an overview of landscape elements which helps in studying the changes on earth's surface due to climate, geological, geomorphological and human activities. Remote sensing measures the electromagnetic radiations from the earth's surface and match the spectral similarity between the observed signature and the known standard signatures of the various targets. However, problem lies when image classification techniques assume pixels to be pure. In hyperspectral imagery, images have high spectral resolution but poor spatial resolution. Therefore, the spectra obtained is often contaminated due to the presence of mixed pixels and causes misclassification. To utilise this high spectral information, spatial resolution has to be enhanced. Many factors make the spatial resolution one of the most expensive and hardest to improve in imaging systems. To solve this problem, post-processing of hyperspectral images is done to retrieve more information from the already acquired images. The algorithm to enhance spatial resolution of the images by dividing them into sub-pixels is known as super-resolution and several researches have been done in this domain.In this paper, we propose a new method for super-resolution based on ant colony optimization and review the popular methods of sub-pixel mapping of hyperspectral images along with their comparative analysis.

Cascaded image analysis for dynamic crack detection in material testing

NASA Astrophysics Data System (ADS)

Hampel, U.; Maas, H.-G.

Concrete probes in civil engineering material testing often show fissures or hairline-cracks. These cracks develop dynamically. Starting at a width of a few microns, they usually cannot be detected visually or in an image of a camera imaging the whole probe. Conventional image analysis techniques will detect fissures only if they show a width in the order of one pixel. To be able to detect and measure fissures with a width of a fraction of a pixel at an early stage of their development, a cascaded image analysis approach has been developed, implemented and tested. The basic idea of the approach is to detect discontinuities in dense surface deformation vector fields. These deformation vector fields between consecutive stereo image pairs, which are generated by cross correlation or least squares matching, show a precision in the order of 1/50 pixel. Hairline-cracks can be detected and measured by applying edge detection techniques such as a Sobel operator to the results of the image matching process. Cracks will show up as linear discontinuities in the deformation vector field and can be vectorized by edge chaining. In practical tests of the method, cracks with a width of 1/20 pixel could be detected, and their width could be determined at a precision of 1/50 pixel.

Deep image mining for diabetic retinopathy screening.

PubMed

Quellec, Gwenolé; Charrière, Katia; Boudi, Yassine; Cochener, Béatrice; Lamard, Mathieu

2017-07-01

Deep learning is quickly becoming the leading methodology for medical image analysis. Given a large medical archive, where each image is associated with a diagnosis, efficient pathology detectors or classifiers can be trained with virtually no expert knowledge about the target pathologies. However, deep learning algorithms, including the popular ConvNets, are black boxes: little is known about the local patterns analyzed by ConvNets to make a decision at the image level. A solution is proposed in this paper to create heatmaps showing which pixels in images play a role in the image-level predictions. In other words, a ConvNet trained for image-level classification can be used to detect lesions as well. A generalization of the backpropagation method is proposed in order to train ConvNets that produce high-quality heatmaps. The proposed solution is applied to diabetic retinopathy (DR) screening in a dataset of almost 90,000 fundus photographs from the 2015 Kaggle Diabetic Retinopathy competition and a private dataset of almost 110,000 photographs (e-ophtha). For the task of detecting referable DR, very good detection performance was achieved: A z =0.954 in Kaggle's dataset and A z =0.949 in e-ophtha. Performance was also evaluated at the image level and at the lesion level in the DiaretDB1 dataset, where four types of lesions are manually segmented: microaneurysms, hemorrhages, exudates and cotton-wool spots. For the task of detecting images containing these four lesion types, the proposed detector, which was trained to detect referable DR, outperforms recent algorithms trained to detect those lesions specifically, with pixel-level supervision. At the lesion level, the proposed detector outperforms heatmap generation algorithms for ConvNets. This detector is part of the Messidor® system for mobile eye pathology screening. Because it does not rely on expert knowledge or manual segmentation for detecting relevant patterns, the proposed solution is a promising image mining tool, which has the potential to discover new biomarkers in images. Copyright © 2017 Elsevier B.V. All rights reserved.

Software-based high-level synthesis design of FPGA beamformers for synthetic aperture imaging.

PubMed

Amaro, Joao; Yiu, Billy Y S; Falcao, Gabriel; Gomes, Marco A C; Yu, Alfred C H

2015-05-01

Field-programmable gate arrays (FPGAs) can potentially be configured as beamforming platforms for ultrasound imaging, but a long design time and skilled expertise in hardware programming are typically required. In this article, we present a novel approach to the efficient design of FPGA beamformers for synthetic aperture (SA) imaging via the use of software-based high-level synthesis techniques. Software kernels (coded in OpenCL) were first developed to stage-wise handle SA beamforming operations, and their corresponding FPGA logic circuitry was emulated through a high-level synthesis framework. After design space analysis, the fine-tuned OpenCL kernels were compiled into register transfer level descriptions to configure an FPGA as a beamformer module. The processing performance of this beamformer was assessed through a series of offline emulation experiments that sought to derive beamformed images from SA channel-domain raw data (40-MHz sampling rate, 12 bit resolution). With 128 channels, our FPGA-based SA beamformer can achieve 41 frames per second (fps) processing throughput (3.44 × 10(8) pixels per second for frame size of 256 × 256 pixels) at 31.5 W power consumption (1.30 fps/W power efficiency). It utilized 86.9% of the FPGA fabric and operated at a 196.5 MHz clock frequency (after optimization). Based on these findings, we anticipate that FPGA and high-level synthesis can together foster rapid prototyping of real-time ultrasound processor modules at low power consumption budgets.

Point spread function based classification of regions for linear digital tomosynthesis

NASA Astrophysics Data System (ADS)

Israni, Kenny; Avinash, Gopal; Li, Baojun

2007-03-01

In digital tomosynthesis, one of the limitations is the presence of out-of-plane blur due to the limited angle acquisition. The point spread function (PSF) characterizes blur in the imaging volume, and is shift-variant in tomosynthesis. The purpose of this research is to classify the tomosynthesis imaging volume into four different categories based on PSF-driven focus criteria. We considered linear tomosynthesis geometry and simple back projection algorithm for reconstruction. The three-dimensional PSF at every pixel in the imaging volume was determined. Intensity profiles were computed for every pixel by integrating the PSF-weighted intensities contained within the line segment defined by the PSF, at each slice. Classification rules based on these intensity profiles were used to categorize image regions. At background and low-frequency pixels, the derived intensity profiles were flat curves with relatively low and high maximum intensities respectively. At in-focus pixels, the maximum intensity of the profiles coincided with the PSF-weighted intensity of the pixel. At out-of-focus pixels, the PSF-weighted intensity of the pixel was always less than the maximum intensity of the profile. We validated our method using human observer classified regions as gold standard. Based on the computed and manual classifications, the mean sensitivity and specificity of the algorithm were 77+/-8.44% and 91+/-4.13% respectively (t=-0.64, p=0.56, DF=4). Such a classification algorithm may assist in mitigating out-of-focus blur from tomosynthesis image slices.

High-speed massively parallel scanning

DOEpatents

Decker, Derek E [Byron, CA

2010-07-06

A new technique for recording a series of images of a high-speed event (such as, but not limited to: ballistics, explosives, laser induced changes in materials, etc.) is presented. Such technique(s) makes use of a lenslet array to take image picture elements (pixels) and concentrate light from each pixel into a spot that is much smaller than the pixel. This array of spots illuminates a detector region (e.g., film, as one embodiment) which is scanned transverse to the light, creating tracks of exposed regions. Each track is a time history of the light intensity for a single pixel. By appropriately configuring the array of concentrated spots with respect to the scanning direction of the detection material, different tracks fit between pixels and sufficient lengths are possible which can be of interest in several high-speed imaging applications.

CMOS Active-Pixel Image Sensor With Intensity-Driven Readout

NASA Technical Reports Server (NTRS)

Langenbacher, Harry T.; Fossum, Eric R.; Kemeny, Sabrina

1996-01-01

Proposed complementary metal oxide/semiconductor (CMOS) integrated-circuit image sensor automatically provides readouts from pixels in order of decreasing illumination intensity. Sensor operated in integration mode. Particularly useful in number of image-sensing tasks, including diffractive laser range-finding, three-dimensional imaging, event-driven readout of sparse sensor arrays, and star tracking.

Building Change Detection in Very High Resolution Satellite Stereo Image Time Series

NASA Astrophysics Data System (ADS)

Tian, J.; Qin, R.; Cerra, D.; Reinartz, P.

2016-06-01

There is an increasing demand for robust methods on urban sprawl monitoring. The steadily increasing number of high resolution and multi-view sensors allows producing datasets with high temporal and spatial resolution; however, less effort has been dedicated to employ very high resolution (VHR) satellite image time series (SITS) to monitor the changes in buildings with higher accuracy. In addition, these VHR data are often acquired from different sensors. The objective of this research is to propose a robust time-series data analysis method for VHR stereo imagery. Firstly, the spatial-temporal information of the stereo imagery and the Digital Surface Models (DSMs) generated from them are combined, and building probability maps (BPM) are calculated for all acquisition dates. In the second step, an object-based change analysis is performed based on the derivative features of the BPM sets. The change consistence between object-level and pixel-level are checked to remove any outlier pixels. Results are assessed on six pairs of VHR satellite images acquired within a time span of 7 years. The evaluation results have proved the efficiency of the proposed method.

Characterization study of an intensified complementary metal-oxide-semiconductor active pixel sensor.

PubMed

Griffiths, J A; Chen, D; Turchetta, R; Royle, G J

2011-03-01

An intensified CMOS active pixel sensor (APS) has been constructed for operation in low-light-level applications: a high-gain, fast-light decay image intensifier has been coupled via a fiber optic stud to a prototype "VANILLA" APS, developed by the UK based MI3 consortium. The sensor is capable of high frame rates and sparse readout. This paper presents a study of the performance parameters of the intensified VANILLA APS system over a range of image intensifier gain levels when uniformly illuminated with 520 nm green light. Mean-variance analysis shows the APS saturating around 3050 Digital Units (DU), with the maximum variance increasing with increasing image intensifier gain. The system's quantum efficiency varies in an exponential manner from 260 at an intensifier gain of 7.45 × 10(3) to 1.6 at a gain of 3.93 × 10(1). The usable dynamic range of the system is 60 dB for intensifier gains below 1.8 × 10(3), dropping to around 40 dB at high gains. The conclusion is that the system shows suitability for the desired application.

Characterization study of an intensified complementary metal-oxide-semiconductor active pixel sensor

NASA Astrophysics Data System (ADS)

Griffiths, J. A.; Chen, D.; Turchetta, R.; Royle, G. J.

2011-03-01

An intensified CMOS active pixel sensor (APS) has been constructed for operation in low-light-level applications: a high-gain, fast-light decay image intensifier has been coupled via a fiber optic stud to a prototype "VANILLA" APS, developed by the UK based MI3 consortium. The sensor is capable of high frame rates and sparse readout. This paper presents a study of the performance parameters of the intensified VANILLA APS system over a range of image intensifier gain levels when uniformly illuminated with 520 nm green light. Mean-variance analysis shows the APS saturating around 3050 Digital Units (DU), with the maximum variance increasing with increasing image intensifier gain. The system's quantum efficiency varies in an exponential manner from 260 at an intensifier gain of 7.45 × 103 to 1.6 at a gain of 3.93 × 101. The usable dynamic range of the system is 60 dB for intensifier gains below 1.8 × 103, dropping to around 40 dB at high gains. The conclusion is that the system shows suitability for the desired application.

Biological tissue imaging with a position and time sensitive pixelated detector.

PubMed

Jungmann, Julia H; Smith, Donald F; MacAleese, Luke; Klinkert, Ivo; Visser, Jan; Heeren, Ron M A

2012-10-01

We demonstrate the capabilities of a highly parallel, active pixel detector for large-area, mass spectrometric imaging of biological tissue sections. A bare Timepix assembly (512 × 512 pixels) is combined with chevron microchannel plates on an ion microscope matrix-assisted laser desorption time-of-flight mass spectrometer (MALDI TOF-MS). The detector assembly registers position- and time-resolved images of multiple m/z species in every measurement frame. We prove the applicability of the detection system to biomolecular mass spectrometry imaging on biologically relevant samples by mass-resolved images from Timepix measurements of a peptide-grid benchmark sample and mouse testis tissue slices. Mass-spectral and localization information of analytes at physiologic concentrations are measured in MALDI-TOF-MS imaging experiments. We show a high spatial resolution (pixel size down to 740 × 740 nm(2) on the sample surface) and a spatial resolving power of 6 μm with a microscope mode laser field of view of 100-335 μm. Automated, large-area imaging is demonstrated and the Timepix' potential for fast, large-area image acquisition is highlighted.

Hardware Implementation of a Bilateral Subtraction Filter

NASA Technical Reports Server (NTRS)

Huertas, Andres; Watson, Robert; Villalpando, Carlos; Goldberg, Steven

2009-01-01

A bilateral subtraction filter has been implemented as a hardware module in the form of a field-programmable gate array (FPGA). In general, a bilateral subtraction filter is a key subsystem of a high-quality stereoscopic machine vision system that utilizes images that are large and/or dense. Bilateral subtraction filters have been implemented in software on general-purpose computers, but the processing speeds attainable in this way even on computers containing the fastest processors are insufficient for real-time applications. The present FPGA bilateral subtraction filter is intended to accelerate processing to real-time speed and to be a prototype of a link in a stereoscopic-machine- vision processing chain, now under development, that would process large and/or dense images in real time and would be implemented in an FPGA. In terms that are necessarily oversimplified for the sake of brevity, a bilateral subtraction filter is a smoothing, edge-preserving filter for suppressing low-frequency noise. The filter operation amounts to replacing the value for each pixel with a weighted average of the values of that pixel and the neighboring pixels in a predefined neighborhood or window (e.g., a 9 9 window). The filter weights depend partly on pixel values and partly on the window size. The present FPGA implementation of a bilateral subtraction filter utilizes a 9 9 window. This implementation was designed to take advantage of the ability to do many of the component computations in parallel pipelines to enable processing of image data at the rate at which they are generated. The filter can be considered to be divided into the following parts (see figure): a) An image pixel pipeline with a 9 9- pixel window generator, b) An array of processing elements; c) An adder tree; d) A smoothing-and-delaying unit; and e) A subtraction unit. After each 9 9 window is created, the affected pixel data are fed to the processing elements. Each processing element is fed the pixel value for its position in the window as well as the pixel value for the central pixel of the window. The absolute difference between these two pixel values is calculated and used as an address in a lookup table. Each processing element has a lookup table, unique for its position in the window, containing the weight coefficients for the Gaussian function for that position. The pixel value is multiplied by the weight, and the outputs of the processing element are the weight and pixel-value weight product. The products and weights are fed to the adder tree. The sum of the products and the sum of the weights are fed to the divider, which computes the sum of products the sum of weights. The output of the divider is denoted the bilateral smoothed image. The smoothing function is a simple weighted average computed over a 3 3 subwindow centered in the 9 9 window. After smoothing, the image is delayed by an additional amount of time needed to match the processing time for computing the bilateral smoothed image. The bilateral smoothed image is then subtracted from the 3 3 smoothed image to produce the final output. The prototype filter as implemented in a commercially available FPGA processes one pixel per clock cycle. Operation at a clock speed of 66 MHz has been demonstrated, and results of a static timing analysis have been interpreted as suggesting that the clock speed could be increased to as much as 100 MHz.

A 7 ke-SD-FWC 1.2 e-RMS Temporal Random Noise 128×256 Time-Resolved CMOS Image Sensor With Two In-Pixel SDs for Biomedical Applications.

PubMed

Seo, Min-Woong; Kawahito, Shoji

2017-12-01

A large full well capacity (FWC) for wide signal detection range and low temporal random noise for high sensitivity lock-in pixel CMOS image sensor (CIS) embedded with two in-pixel storage diodes (SDs) has been developed and presented in this paper. For fast charge transfer from photodiode to SDs, a lateral electric field charge modulator (LEFM) is used for the developed lock-in pixel. As a result, the time-resolved CIS achieves a very large SD-FWC of approximately 7ke-, low temporal random noise of 1.2e-rms at 20 fps with true correlated double sampling operation and fast intrinsic response less than 500 ps at 635 nm. The proposed imager has an effective pixel array of and a pixel size of . The sensor chip is fabricated by Dongbu HiTek 1P4M 0.11 CIS process.

Angular sensitivity of modeled scientific silicon charge-coupled devices to initial electron direction

NASA Astrophysics Data System (ADS)

Plimley, Brian; Coffer, Amy; Zhang, Yigong; Vetter, Kai

2016-08-01

Previously, scientific silicon charge-coupled devices (CCDs) with 10.5-μm pixel pitch and a thick (650 μm), fully depleted bulk have been used to measure gamma-ray-induced fast electrons and demonstrate electron track Compton imaging. A model of the response of this CCD was also developed and benchmarked to experiment using Monte Carlo electron tracks. We now examine the trade-off in pixel pitch and electronic noise. We extend our CCD response model to different pixel pitch and readout noise per pixel, including pixel pitch of 2.5 μm, 5 μm, 10.5 μm, 20 μm, and 40 μm, and readout noise from 0 eV/pixel to 2 keV/pixel for 10.5 μm pixel pitch. The CCD images generated by this model using simulated electron tracks are processed by our trajectory reconstruction algorithm. The performance of the reconstruction algorithm defines the expected angular sensitivity as a function of electron energy, CCD pixel pitch, and readout noise per pixel. Results show that our existing pixel pitch of 10.5 μm is near optimal for our approach, because smaller pixels add little new information but are subject to greater statistical noise. In addition, we measured the readout noise per pixel for two different device temperatures in order to estimate the effect of temperature on the reconstruction algorithm performance, although the readout is not optimized for higher temperatures. The noise in our device at 240 K increases the FWHM of angular measurement error by no more than a factor of 2, from 26° to 49° FWHM for electrons between 425 keV and 480 keV. Therefore, a CCD could be used for electron-track-based imaging in a Peltier-cooled device.