Imaging photorefractive optical vibration measurement method and device

DOEpatents

Telschow, Kenneth L.; Deason, Vance A.; Hale, Thomas C.

2000-01-01

A method and apparatus are disclosed for characterizing a vibrating image of an object of interest. The method includes providing a sensing media having a detection resolution within a limited bandwidth and providing an object of interest having a vibrating medium. Two or more wavefronts are provided, with at least one of the wavefronts being modulated by interacting the one wavefront with the vibrating medium of the object of interest. The another wavefront is modulated such that the difference frequency between the one wavefront and the another wavefront is within a response range of the sensing media. The modulated one wavefront and another wavefront are combined in association with the sensing media to interfere and produce simultaneous vibration measurements that are distributed over the object so as to provide an image of the vibrating medium. The image has an output intensity that is substantially linear with small physical variations within the vibrating medium. Furthermore, the method includes detecting the image. In one implementation, the apparatus comprises a vibration spectrum analyzer having an emitter, a modulator, sensing media and a detector configured so as to realize such method. According to another implementation, the apparatus comprises a vibration imaging device.

The use of multisensor images for Earth Science applications

NASA Technical Reports Server (NTRS)

Evans, D.; Stromberg, B.

1983-01-01

The use of more than one remote sensing technique is particularly important for Earth Science applications because of the compositional and textural information derivable from the images. The ability to simultaneously analyze images acquired by different sensors requires coregistration of the multisensor image data sets. In order to insure pixel to pixel registration in areas of high relief, images must be rectified to eliminate topographic distortions. Coregistered images can be analyzed using a variety of multidimensional techniques and the acquired knowledge of topographic effects in the images can be used in photogeologic interpretations.

Fast Acquisition and Reconstruction of Optical Coherence Tomography Images via Sparse Representation

PubMed Central

Li, Shutao; McNabb, Ryan P.; Nie, Qing; Kuo, Anthony N.; Toth, Cynthia A.; Izatt, Joseph A.; Farsiu, Sina

2014-01-01

In this paper, we present a novel technique, based on compressive sensing principles, for reconstruction and enhancement of multi-dimensional image data. Our method is a major improvement and generalization of the multi-scale sparsity based tomographic denoising (MSBTD) algorithm we recently introduced for reducing speckle noise. Our new technique exhibits several advantages over MSBTD, including its capability to simultaneously reduce noise and interpolate missing data. Unlike MSBTD, our new method does not require an a priori high-quality image from the target imaging subject and thus offers the potential to shorten clinical imaging sessions. This novel image restoration method, which we termed sparsity based simultaneous denoising and interpolation (SBSDI), utilizes sparse representation dictionaries constructed from previously collected datasets. We tested the SBSDI algorithm on retinal spectral domain optical coherence tomography images captured in the clinic. Experiments showed that the SBSDI algorithm qualitatively and quantitatively outperforms other state-of-the-art methods. PMID:23846467

A multi-signal fluorescent probe for simultaneously distinguishing and sequentially sensing cysteine/homocysteine, glutathione, and hydrogen sulfide in living cells† †Electronic supplementary information (ESI) available: Experimental details for chemical synthesis of all compounds, chemical structure characterization, supplementary spectra of probe, and fluorescence imaging methods and data. See DOI: 10.1039/c7sc00423k Click here for additional data file.

PubMed Central

He, Longwei; Yang, Xueling; Xu, Kaixin; Kong, Xiuqi

2017-01-01

Biothiols, which have a close network of generation and metabolic pathways among them, are essential reactive sulfur species (RSS) in the cells and play vital roles in human physiology. However, biothiols possess highly similar chemical structures and properties, resulting in it being an enormous challenge to simultaneously discriminate them from each other. Herein, we develop a unique fluorescent probe (HMN) for not only simultaneously distinguishing Cys/Hcy, GSH, and H2S from each other, but also sequentially sensing Cys/Hcy/GSH and H2S using a multi-channel fluorescence mode for the first time. When responding to the respective biothiols, the robust probe exhibits multiple sets of fluorescence signals at three distinct emission bands (blue-green-red). The new probe can also sense H2S at different concentration levels with changes of fluorescence at the blue and red emission bands. In addition, the novel probe HMN is able to discriminate and sequentially sense biothiols in biological environments via three-color fluorescence imaging. We expect that the development of the robust probe HMN will provide a powerful strategy to design fluorescent probes for the discrimination and sequential detection of biothiols, and offer a promising tool for exploring the interrelated roles of biothiols in various physiological and pathological conditions. PMID:28989659

Time-jittered marine seismic data acquisition via compressed sensing and sparsity-promoting wavefield reconstruction

NASA Astrophysics Data System (ADS)

Wason, H.; Herrmann, F. J.; Kumar, R.

2016-12-01

Current efforts towards dense shot (or receiver) sampling and full azimuthal coverage to produce high resolution images have led to the deployment of multiple source vessels (or streamers) across marine survey areas. Densely sampled marine seismic data acquisition, however, is expensive, and hence necessitates the adoption of sampling schemes that save acquisition costs and time. Compressed sensing is a sampling paradigm that aims to reconstruct a signal--that is sparse or compressible in some transform domain--from relatively fewer measurements than required by the Nyquist sampling criteria. Leveraging ideas from the field of compressed sensing, we show how marine seismic acquisition can be setup as a compressed sensing problem. A step ahead from multi-source seismic acquisition is simultaneous source acquisition--an emerging technology that is stimulating both geophysical research and commercial efforts--where multiple source arrays/vessels fire shots simultaneously resulting in better coverage in marine surveys. Following the design principles of compressed sensing, we propose a pragmatic simultaneous time-jittered time-compressed marine acquisition scheme where single or multiple source vessels sail across an ocean-bottom array firing airguns at jittered times and source locations, resulting in better spatial sampling and speedup acquisition. Our acquisition is low cost since our measurements are subsampled. Simultaneous source acquisition generates data with overlapping shot records, which need to be separated for further processing. We can significantly impact the reconstruction quality of conventional seismic data from jittered data and demonstrate successful recovery by sparsity promotion. In contrast to random (sub)sampling, acquisition via jittered (sub)sampling helps in controlling the maximum gap size, which is a practical requirement of wavefield reconstruction with localized sparsifying transforms. We illustrate our results with simulations of simultaneous time-jittered marine acquisition for 2D and 3D ocean-bottom cable survey.

Cellular Oxygen and Nutrient Sensing in Microgravity Using Time-Resolved Fluorescence Microscopy

NASA Technical Reports Server (NTRS)

Szmacinski, Henryk

2003-01-01

Oxygen and nutrient sensing is fundamental to the understanding of cell growth and metabolism. This requires identification of optical probes and suitable detection technology without complex calibration procedures. Under this project Microcosm developed an experimental technique that allows for simultaneous imaging of intra- and inter-cellular events. The technique consists of frequency-domain Fluorescence Lifetime Imaging Microscopy (FLIM), a set of identified oxygen and pH probes, and methods for fabrication of microsensors. Specifications for electronic and optical components of FLIM instrumentation are provided. Hardware and software were developed for data acquisition and analysis. Principles, procedures, and representative images are demonstrated. Suitable lifetime sensitive oxygen, pH, and glucose probes for intra- and extra-cellular measurements of analyte concentrations have been identified and tested. Lifetime sensing and imaging have been performed using PBS buffer, culture media, and yeast cells as a model systems. Spectral specifications, calibration curves, and probes availability are also provided in the report.

Image sensor with motion artifact supression and anti-blooming

NASA Technical Reports Server (NTRS)

Pain, Bedabrata (Inventor); Wrigley, Chris (Inventor); Yang, Guang (Inventor); Yadid-Pecht, Orly (Inventor)

2006-01-01

An image sensor includes pixels formed on a semiconductor substrate. Each pixel includes a photoactive region in the semiconductor substrate, a sense node, and a power supply node. A first electrode is disposed near a surface of the semiconductor substrate. A bias signal on the first electrode sets a potential in a region of the semiconductor substrate between the photoactive region and the sense node. A second electrode is disposed near the surface of the semiconductor substrate. A bias signal on the second electrode sets a potential in a region of the semiconductor substrate between the photoactive region and the power supply node. The image sensor includes a controller that causes bias signals to be provided to the electrodes so that photocharges generated in the photoactive region are accumulated in the photoactive region during a pixel integration period, the accumulated photocharges are transferred to the sense node during a charge transfer period, and photocharges generated in the photoactive region are transferred to the power supply node during a third period without passing through the sense node. The imager can operate at high shutter speeds with simultaneous integration of pixels in the array. High quality images can be produced free from motion artifacts. High quantum efficiency, good blooming control, low dark current, low noise and low image lag can be obtained.

High speed CMOS imager with motion artifact supression and anti-blooming

NASA Technical Reports Server (NTRS)

Pain, Bedabrata (Inventor); Wrigley, Chris (Inventor); Yang, Guang (Inventor); Yadid-Pecht, Orly (Inventor)

2001-01-01

An image sensor includes pixels formed on a semiconductor substrate. Each pixel includes a photoactive region in the semiconductor substrate, a sense node, and a power supply node. A first electrode is disposed near a surface of the semiconductor substrate. A bias signal on the first electrode sets a potential in a region of the semiconductor substrate between the photoactive region and the sense node. A second electrode is disposed near the surface of the semiconductor substrate. A bias signal on the second electrode sets a potential in a region of the semiconductor substrate between the photoactive region and the power supply node. The image sensor includes a controller that causes bias signals to be provided to the electrodes so that photocharges generated in the photoactive region are accumulated in the photoactive region during a pixel integration period, the accumulated photocharges are transferred to the sense node during a charge transfer period, and photocharges generated in the photoactive region are transferred to the power supply node during a third period without passing through the sense node. The imager can operate at high shutter speeds with simultaneous integration of pixels in the array. High quality images can be produced free from motion artifacts. High quantum efficiency, good blooming control, low dark current, low noise and low image lag can be obtained.

Automated simultaneous multiple feature classification of MTI data

NASA Astrophysics Data System (ADS)

Harvey, Neal R.; Theiler, James P.; Balick, Lee K.; Pope, Paul A.; Szymanski, John J.; Perkins, Simon J.; Porter, Reid B.; Brumby, Steven P.; Bloch, Jeffrey J.; David, Nancy A.; Galassi, Mark C.

2002-08-01

Los Alamos National Laboratory has developed and demonstrated a highly capable system, GENIE, for the two-class problem of detecting a single feature against a background of non-feature. In addition to the two-class case, however, a commonly encountered remote sensing task is the segmentation of multispectral image data into a larger number of distinct feature classes or land cover types. To this end we have extended our existing system to allow the simultaneous classification of multiple features/classes from multispectral data. The technique builds on previous work and its core continues to utilize a hybrid evolutionary-algorithm-based system capable of searching for image processing pipelines optimized for specific image feature extraction tasks. We describe the improvements made to the GENIE software to allow multiple-feature classification and describe the application of this system to the automatic simultaneous classification of multiple features from MTI image data. We show the application of the multiple-feature classification technique to the problem of classifying lava flows on Mauna Loa volcano, Hawaii, using MTI image data and compare the classification results with standard supervised multiple-feature classification techniques.

Insulated Conducting Cantilevered Nanotips and Two-Chamber Recording System for High Resolution Ion Sensing AFM

PubMed Central

Meckes, Brian; Arce, Fernando Teran; Connelly, Laura S.; Lal, Ratnesh

2014-01-01

Biological membranes contain ion channels, which are nanoscale pores allowing controlled ionic transport and mediating key biological functions underlying normal/abnormal living. Synthetic membranes with defined pores are being developed to control various processes, including filtration of pollutants, charge transport for energy storage, and separation of fluids and molecules. Although ionic transport (currents) can be measured with single channel resolution, imaging their structure and ionic currents simultaneously is difficult. Atomic force microscopy enables high resolution imaging of nanoscale structures and can be modified to measure ionic currents simultaneously. Moreover, the ionic currents can also be used to image structures. A simple method for fabricating conducting AFM cantilevers to image pore structures at high resolution is reported. Tungsten microwires with nanoscale tips are insulated except at the apex. This allows simultaneous imaging via cantilever deflections in normal AFM force feedback mode as well as measuring localized ionic currents. These novel probes measure ionic currents as small as picoampere while providing nanoscale spatial resolution surface topography and is suitable for measuring ionic currents and conductance of biological ion channels. PMID:24663394

Wavefront Sensing for WFIRST with a Linear Optical Model

NASA Technical Reports Server (NTRS)

Jurling, Alden S.; Content, David A.

2012-01-01

In this paper we develop methods to use a linear optical model to capture the field dependence of wavefront aberrations in a nonlinear optimization-based phase retrieval algorithm for image-based wavefront sensing. The linear optical model is generated from a ray trace model of the system and allows the system state to be described in terms of mechanical alignment parameters rather than wavefront coefficients. This approach allows joint optimization over images taken at different field points and does not require separate convergence of phase retrieval at individual field points. Because the algorithm exploits field diversity, multiple defocused images per field point are not required for robustness. Furthermore, because it is possible to simultaneously fit images of many stars over the field, it is not necessary to use a fixed defocus to achieve adequate signal-to-noise ratio despite having images with high dynamic range. This allows high performance wavefront sensing using in-focus science data. We applied this technique in a simulation model based on the Wide Field Infrared Survey Telescope (WFIRST) Intermediate Design Reference Mission (IDRM) imager using a linear optical model with 25 field points. We demonstrate sub-thousandth-wave wavefront sensing accuracy in the presence of noise and moderate undersampling for both monochromatic and polychromatic images using 25 high-SNR target stars. Using these high-quality wavefront sensing results, we are able to generate upsampled point-spread functions (PSFs) and use them to determine PSF ellipticity to high accuracy in order to reduce the systematic impact of aberrations on the accuracy of galactic ellipticity determination for weak-lensing science.

Wideband Interferometric Sensing and Imaging Polarimetry

NASA Technical Reports Server (NTRS)

Verdi, James Salvatore; Kessler, Otto; Boerner, Wolfgang-Martin

1996-01-01

Wideband Interferometric Sensing and Imaging Polarimetry (WISIP) has become an important, indispensible tool in wide area military surveillance and global environmental monitoring of the terrestrial and planetary covers. It enables dynamic, real time optimal feature extraction of significant characteristics of desirable targets and/or target sections with simultaneous suppression of undesirable background clutter and propagation path speckle at hitherto unknown clarity and never before achieved quality. WISIP may be adopted to the detection, recognition, and identification (DRI) of any stationary, moving or vibrating targets or distributed scatterer segments versus arbitrary stationary, dynamical changing and/or moving geo-physical/ecological environments, provided the instantaneous 2x2 phasor and 4x4 power density matrices for forward propagation/backward scattering, respectively, can be measured with sufficient accuracy. For example, the DRI of stealthy, dynamically moving inhomogeneous volumetric scatter environments such as precipitation scatter, the ocean/sea/lake surface boundary layers, the littoral coastal surf zones, pack ice and snow or vegetative canopies, dry sands and soils, etc. can now be successfully realized. A comprehensive overview is presented on how these modern high resolution/precision, complete polarimetric co-registered signature sensing and imaging techniques, complemented by full integration of novel navigational electronic tools, such as DGPS, will advance electromagnetic vector wave sensing and imaging towards the limits of physical realization. Various examples utilizing the most recent image data take sets of airborne, space shuttle, and satellite imaging systems demonstrate the utility of WISIP.

High Sensitivity Stress Sensor Based on Hybrid Materials

NASA Technical Reports Server (NTRS)

Cao, Xian-An (Inventor)

2014-01-01

A sensing device is used to detect the spatial distributions of stresses applied by physical contact with the surface of the sensor or induced by pressure, temperature gradients, and surface absorption. The sensor comprises a hybrid active layer that includes luminophores doped in a polymeric or organic host, altogether embedded in a matrix. Under an electrical bias, the sensor simultaneously converts stresses into electrical and optical signals. Among many applications, the device may be used for tactile sensing and biometric imaging.

Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.

PubMed

Zhang, Lefei; Zhang, Qian; Du, Bo; Huang, Xin; Tang, Yuan Yan; Tao, Dacheng

2018-01-01

In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature, and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial features into a single but high dimensional vector and then apply a certain dimension reduction technique directly on that concatenated vector before feed it into the subsequent classifier. However, multiple features from various domains definitely have different physical meanings and statistical properties, and thus such concatenation has not efficiently explore the complementary properties among different features, which should benefit for boost the feature discriminability. Furthermore, it is also difficult to interpret the transformed results of the concatenated vector. Consequently, finding a physically meaningful consensus low dimensional feature representation of original multiple features is still a challenging task. In order to address these issues, we propose a novel feature learning framework, i.e., the simultaneous spectral-spatial feature selection and extraction algorithm, for hyperspectral images spectral-spatial feature representation and classification. Specifically, the proposed method learns a latent low dimensional subspace by projecting the spectral-spatial feature into a common feature space, where the complementary information has been effectively exploited, and simultaneously, only the most significant original features have been transformed. Encouraging experimental results on three public available hyperspectral remote sensing datasets confirm that our proposed method is effective and efficient.

Parallel algorithm of real-time infrared image restoration based on total variation theory

NASA Astrophysics Data System (ADS)

Zhu, Ran; Li, Miao; Long, Yunli; Zeng, Yaoyuan; An, Wei

2015-10-01

Image restoration is a necessary preprocessing step for infrared remote sensing applications. Traditional methods allow us to remove the noise but penalize too much the gradients corresponding to edges. Image restoration techniques based on variational approaches can solve this over-smoothing problem for the merits of their well-defined mathematical modeling of the restore procedure. The total variation (TV) of infrared image is introduced as a L1 regularization term added to the objective energy functional. It converts the restoration process to an optimization problem of functional involving a fidelity term to the image data plus a regularization term. Infrared image restoration technology with TV-L1 model exploits the remote sensing data obtained sufficiently and preserves information at edges caused by clouds. Numerical implementation algorithm is presented in detail. Analysis indicates that the structure of this algorithm can be easily implemented in parallelization. Therefore a parallel implementation of the TV-L1 filter based on multicore architecture with shared memory is proposed for infrared real-time remote sensing systems. Massive computation of image data is performed in parallel by cooperating threads running simultaneously on multiple cores. Several groups of synthetic infrared image data are used to validate the feasibility and effectiveness of the proposed parallel algorithm. Quantitative analysis of measuring the restored image quality compared to input image is presented. Experiment results show that the TV-L1 filter can restore the varying background image reasonably, and that its performance can achieve the requirement of real-time image processing.

Shielded piezoresistive cantilever probes for nanoscale topography and electrical imaging

NASA Astrophysics Data System (ADS)

Yang, Yongliang; Ma, Eric Yue; Cui, Yong-Tao; Haemmerli, Alexandre; Lai, Keji; Kundhikanjana, Worasom; Harjee, Nahid; Pruitt, Beth L.; Kelly, Michael; Shen, Zhi-Xun

2014-04-01

This paper presents the design and fabrication of piezoresistive cantilever probes for microwave impedance microscopy (MIM) to enable simultaneous topographic and electrical imaging. Plasma enhanced chemical vapor deposited Si3N4 cantilevers with a shielded center conductor line and nanoscale conductive tip apex are batch fabricated on silicon-on-insulator wafers. Doped silicon piezoresistors are integrated at the root of the cantilevers to sense their deformation. The piezoresistive sensitivity is 2 nm for a bandwidth of 10 kHz, enabling topographical imaging with reasonable speed. The aluminum center conductor has a low resistance (less than 5 Ω) and small capacitance (˜1.7 pF) to ground; these parameters are critical for high sensitivity MIM imaging. High quality piezoresistive topography and MIM images are simultaneously obtained with the fabricated probes at ambient and cryogenic temperatures. These new piezoresistive probes remarkably broaden the horizon of MIM for scientific applications by operating with an integrated feedback mechanism at low temperature and for photosensitive samples.

NASA Fluid Lensing & MiDAR: Next-Generation Remote Sensing Technologies for Aquatic Remote Sensing

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2018-01-01

We present two recent instrument technology developments at NASA, Fluid Lensing and MiDAR, and their application to remote sensing of Earth's aquatic systems. Fluid Lensing is the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions. MiDAR is a next-generation active hyperspectral remote sensing and optical communications instrument capable of active fluid lensing. Fluid Lensing has been used to provide 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs, or drones), including coral reefs in American Samoa and stromatolite reefs in Hamelin Pool, Western Australia. MiDAR is being deployed on aircraft and underwater remotely operated vehicles (ROVs) to enable a new method for remote sensing of living and nonliving structures in extreme environments. MiDAR images targets with high-intensity narrowband structured optical radiation to measure an objectâ€"TM"s non-linear spectral reflectance, image through fluid interfaces such as ocean waves with active fluid lensing, and simultaneously transmit high-bandwidth data. As an active instrument, MiDAR is capable of remotely sensing reflectance at the centimeter (cm) spatial scale with a signal-to-noise ratio (SNR) multiple orders of magnitude higher than passive airborne and spaceborne remote sensing systems with significantly reduced integration time. This allows for rapid video-frame-rate hyperspectral sensing into the far ultraviolet and VNIR wavelengths. Previously, MiDAR was developed into a TRL 2 laboratory instrument capable of imaging in thirty-two narrowband channels across the VNIR spectrum (400-950nm). Recently, MiDAR UV was raised to TRL4 and expanded to include five ultraviolet bands from 280-400nm, permitting UV remote sensing capabilities in UV A, B, and C bands and enabling mineral identification and stimulated fluorescence measurements of organic proteins and compounds, such as green fluorescent proteins in terrestrial and aquatic organics.

Self-referenced directional enhanced Raman scattering using plasmon waveguide resonance for surface and bulk sensing

NASA Astrophysics Data System (ADS)

Wan, Xiu-mei; Gao, Ran; Lu, Dan-feng; Qi, Zhi-mei

2018-01-01

Surface plasmon-coupled emission has been widely used in fluorescence imaging, biochemical sensing, and enhanced Raman spectroscopy. A self-referenced directional enhanced Raman scattering for simultaneous detection of surface and bulk effects by using plasmon waveguide resonance (PWR) based surface plasmon-coupled emission has been proposed and experimentally demonstrated. Raman scattering was captured on the prism side in Kretschmann-surface plasmon-coupled emission. The distinct penetration depths (δ) of the evanescent field for the transverse electric (TE) and transverse magnetic (TM) modes result in different detected distances of the Raman signal. The experimental results demonstrate that the self-referenced directional enhanced Raman scattering of the TE and TM modes based on the PWR can detect and distinguish the surface and bulk effects simultaneously, which appears to have potential applications in researches of chemistry, medicine, and biology.

Towards real-time thermometry using simultaneous multislice MRI

NASA Astrophysics Data System (ADS)

Borman, P. T. S.; Bos, C.; de Boorder, T.; Raaymakers, B. W.; Moonen, C. T. W.; Crijns, S. P. M.

2016-09-01

MR-guided thermal therapies, such as high-intensity focused ultrasound (MRgHIFU) and laser-induced thermal therapy (MRgLITT) are increasingly being applied in oncology and neurology. MRI is used for guidance since it can measure temperature noninvasively based on the proton resonance frequency shift (PRFS). For therapy guidance using PRFS thermometry, high temporal resolution and large spatial coverage are desirable. We propose to use the parallel imaging technique simultaneous multislice (SMS) in combination with controlled aliasing (CAIPIRINHA) to accelerate the acquisition. We compare this with the sensitivity encoding (SENSE) acceleration technique. Two experiments were performed to validate that SMS can be used to increase the spatial coverage or the temporal resolution. The first was performed in agar gel using LITT heating and a gradient-echo sequence with echo-planar imaging (EPI), and the second was performed in bovine muscle using HIFU heating and a gradient-echo sequence without EPI. In both experiments temperature curves from an unaccelerated scan and from SMS, SENSE, and SENSE/SMS accelerated scans were compared. The precision was quantified by a standard deviation analysis of scans without heating. Both experiments showed a good agreement between the temperature curves obtained from the unaccelerated, and SMS accelerated scans, confirming that accuracy was maintained during SMS acceleration. The standard deviations of the temperature measurements obtained with SMS were significantly smaller than when SENSE was used, implying that SMS allows for higher acceleration. In the LITT and HIFU experiments SMS factors up to 4 and 3 were reached, respectively, with a loss of precision of less than a factor of 3. Based on these results we conclude that SMS acceleration of PRFS thermometry is a valuable addition to SENSE, because it allows for a higher temporal resolution or bigger spatial coverage, with a higher precision.

High-resolution imaging of cellular processes across textured surfaces using an indexed-matched elastomer.

PubMed

Ravasio, Andrea; Vaishnavi, Sree; Ladoux, Benoit; Viasnoff, Virgile

2015-03-01

Understanding and controlling how cells interact with the microenvironment has emerged as a prominent field in bioengineering, stem cell research and in the development of the next generation of in vitro assays as well as organs on a chip. Changing the local rheology or the nanotextured surface of substrates has proved an efficient approach to improve cell lineage differentiation, to control cell migration properties and to understand environmental sensing processes. However, introducing substrate surface textures often alters the ability to image cells with high precision, compromising our understanding of molecular mechanisms at stake in environmental sensing. In this paper, we demonstrate how nano/microstructured surfaces can be molded from an elastomeric material with a refractive index matched to the cell culture medium. Once made biocompatible, contrast imaging (differential interference contrast, phase contrast) and high-resolution fluorescence imaging of subcellular structures can be implemented through the textured surface using an inverted microscope. Simultaneous traction force measurements by micropost deflection were also performed, demonstrating the potential of our approach to study cell-environment interactions, sensing processes and cellular force generation with unprecedented resolution. Copyright © 2014 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

a Novel Deep Convolutional Neural Network for Spectral-Spatial Classification of Hyperspectral Data

NASA Astrophysics Data System (ADS)

Li, N.; Wang, C.; Zhao, H.; Gong, X.; Wang, D.

2018-04-01

Spatial and spectral information are obtained simultaneously by hyperspectral remote sensing. Joint extraction of these information of hyperspectral image is one of most import methods for hyperspectral image classification. In this paper, a novel deep convolutional neural network (CNN) is proposed, which extracts spectral-spatial information of hyperspectral images correctly. The proposed model not only learns sufficient knowledge from the limited number of samples, but also has powerful generalization ability. The proposed framework based on three-dimensional convolution can extract spectral-spatial features of labeled samples effectively. Though CNN has shown its robustness to distortion, it cannot extract features of different scales through the traditional pooling layer that only have one size of pooling window. Hence, spatial pyramid pooling (SPP) is introduced into three-dimensional local convolutional filters for hyperspectral classification. Experimental results with a widely used hyperspectral remote sensing dataset show that the proposed model provides competitive performance.

Multispectral Photography

NASA Technical Reports Server (NTRS)

1982-01-01

Model II Multispectral Camera is an advanced aerial camera that provides optimum enhancement of a scene by recording spectral signatures of ground objects only in narrow, preselected bands of the electromagnetic spectrum. Its photos have applications in such areas as agriculture, forestry, water pollution investigations, soil analysis, geologic exploration, water depth studies and camouflage detection. The target scene is simultaneously photographed in four separate spectral bands. Using a multispectral viewer, such as their Model 75 Spectral Data creates a color image from the black and white positives taken by the camera. With this optical image analysis unit, all four bands are superimposed in accurate registration and illuminated with combinations of blue green, red, and white light. Best color combination for displaying the target object is selected and printed. Spectral Data Corporation produces several types of remote sensing equipment and also provides aerial survey, image processing and analysis and number of other remote sensing services.

Optical to optical interface device

NASA Technical Reports Server (NTRS)

Oliver, D. S.; Vohl, P.; Nisenson, P.

1972-01-01

The development, fabrication, and testing of a preliminary model of an optical-to-optical (noncoherent-to-coherent) interface device for use in coherent optical parallel processing systems are described. The developed device demonstrates a capability for accepting as an input a scene illuminated by a noncoherent radiation source and providing as an output a coherent light beam spatially modulated to represent the original noncoherent scene. The converter device developed under this contract employs a Pockels readout optical modulator (PROM). This is a photosensitive electro-optic element which can sense and electrostatically store optical images. The stored images can be simultaneously or subsequently readout optically by utilizing the electrostatic storage pattern to control an electro-optic light modulating property of the PROM. The readout process is parallel as no scanning mechanism is required. The PROM provides the functions of optical image sensing, modulation, and storage in a single active material.

Quantum dots in imaging, drug delivery and sensor applications

PubMed Central

Matea, Cristian T; Mocan, Teodora; Tabaran, Flaviu; Pop, Teodora; Mosteanu, Ofelia; Puia, Cosmin; Iancu, Cornel; Mocan, Lucian

2017-01-01

Quantum dots (QDs), also known as nanoscale semiconductor crystals, are nanoparticles with unique optical and electronic properties such as bright and intensive fluorescence. Since most conventional organic label dyes do not offer the near-infrared (>650 nm) emission possibility, QDs, with their tunable optical properties, have gained a lot of interest. They possess characteristics such as good chemical and photo-stability, high quantum yield and size-tunable light emission. Different types of QDs can be excited with the same light wavelength, and their narrow emission bands can be detected simultaneously for multiple assays. There is an increasing interest in the development of nano-theranostics platforms for simultaneous sensing, imaging and therapy. QDs have great potential for such applications, with notable results already published in the fields of sensors, drug delivery and biomedical imaging. This review summarizes the latest developments available in literature regarding the use of QDs for medical applications. PMID:28814860

Quantum dots in imaging, drug delivery and sensor applications.

PubMed

Matea, Cristian T; Mocan, Teodora; Tabaran, Flaviu; Pop, Teodora; Mosteanu, Ofelia; Puia, Cosmin; Iancu, Cornel; Mocan, Lucian

2017-01-01

Quantum dots (QDs), also known as nanoscale semiconductor crystals, are nanoparticles with unique optical and electronic properties such as bright and intensive fluorescence. Since most conventional organic label dyes do not offer the near-infrared (>650 nm) emission possibility, QDs, with their tunable optical properties, have gained a lot of interest. They possess characteristics such as good chemical and photo-stability, high quantum yield and size-tunable light emission. Different types of QDs can be excited with the same light wavelength, and their narrow emission bands can be detected simultaneously for multiple assays. There is an increasing interest in the development of nano-theranostics platforms for simultaneous sensing, imaging and therapy. QDs have great potential for such applications, with notable results already published in the fields of sensors, drug delivery and biomedical imaging. This review summarizes the latest developments available in literature regarding the use of QDs for medical applications.

A bio-image sensor for simultaneous detection of multi-neurotransmitters.

PubMed

Lee, You-Na; Okumura, Koichi; Horio, Tomoko; Iwata, Tatsuya; Takahashi, Kazuhiro; Hattori, Toshiaki; Sawada, Kazuaki

2018-03-01

We report here a new bio-image sensor for simultaneous detection of spatial and temporal distribution of multi-neurotransmitters. It consists of multiple enzyme-immobilized membranes on a 128 × 128 pixel array with read-out circuit. Apyrase and acetylcholinesterase (AChE), as selective elements, are used to recognize adenosine 5'-triphosphate (ATP) and acetylcholine (ACh), respectively. To enhance the spatial resolution, hydrogen ion (H + ) diffusion barrier layers are deposited on top of the bio-image sensor and demonstrated their prevention capability. The results are used to design the space among enzyme-immobilized pixels and the null H + sensor to minimize the undesired signal overlap by H + diffusion. Using this bio-image sensor, we can obtain H + diffusion-independent imaging of concentration gradients of ATP and ACh in real-time. The sensing characteristics, such as sensitivity and detection of limit, are determined experimentally. With the proposed bio-image sensor the possibility exists for customizable monitoring of the activities of various neurochemicals by using different kinds of proton-consuming or generating enzymes. Copyright © 2017 Elsevier B.V. All rights reserved.

A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

NASA Astrophysics Data System (ADS)

Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; Kucera, Jan; Vogt, Peter; Seebach, Lucia; San-Miguel-Ayanz, Jesús

2011-09-01

This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and cloud free MODIS composites as reference images. The selected scenes included a wide range of cloud types and surface features. The resulting cloud masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated cloud masks and with the automatic cloud cover assessment algorithm (ACCA). In general the results showed an agreement in detected clouds higher than 95% for clouds larger than 50 ha. The approach produced consistent results identifying and mapping clouds of different type and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.

Single-cell photoacoustic thermometry

PubMed Central

Gao, Liang; Wang, Lidai; Li, Chiye; Liu, Yan; Ke, Haixin; Zhang, Chi

2013-01-01

Abstract. A novel photoacoustic thermometric method is presented for simultaneously imaging cells and sensing their temperature. With three-seconds-per-frame imaging speed, a temperature resolution of 0.2°C was achieved in a photo-thermal cell heating experiment. Compared to other approaches, the photoacoustic thermometric method has the advantage of not requiring custom-developed temperature-sensitive biosensors. This feature should facilitate the conversion of single-cell thermometry into a routine lab tool and make it accessible to a much broader biological research community. PMID:23377004

Development of a Pressure Sensitive Paint System with Correction for Temperature Variation

NASA Technical Reports Server (NTRS)

Simmons, Kantis A.

1995-01-01

Pressure Sensitive Paint (PSP) is known to provide a global image of pressure over a model surface. However, improvements in its accuracy and reliability are needed. Several factors contribute to the inaccuracy of PSP. One major factor is that luminescence is temperature dependent. To correct the luminescence of the pressure sensing component for changes in temperature, a temperature sensitive luminophore incorporated in the paint allows the user to measure both pressure and temperature simultaneously on the surface of a model. Magnesium Octaethylporphine (MgOEP) was used as a temperature sensing luminophore, with the pressure sensing luminophore, Platinum Octaethylporphine (PtOEP), to correct for temperature variations in model surface pressure measurements.

Hyperspectral techniques in analysis of oral dosage forms.

PubMed

Hamilton, Sara J; Lowell, Amanda E; Lodder, Robert A

2002-10-01

Pharmaceutical oral dosage forms are used in this paper to test the sensitivity and spatial resolution of hyperspectral imaging instruments. The first experiment tested the hypothesis that a near-infrared (IR) tunable diode-based remote sensing system is capable of monitoring degradation of hard gelatin capsules at a relatively long distance (0.5 km). Spectra from the capsules were used to differentiate among capsules exposed to an atmosphere containing 150 ppb formaldehyde for 0, 2, 4, and 8 h. Robust median-based principal component regression with Bayesian inference was employed for outlier detection. The second experiment tested the hypothesis that near-IR imaging spectrometry of tablets permits the identification and composition of multiple individual tablets to be determined simultaneously. A near-IR camera was used to collect thousands of spectra simultaneously from a field of blister-packaged tablets. The number of tablets that a typical near-IR camera can currently analyze simultaneously was estimated to be approximately 1300. The bootstrap error-adjusted single-sample technique chemometric-imaging algorithm was used to draw probability-density contour plots that revealed tablet composition. The single-capsule analysis provides an indication of how far apart the sample and instrumentation can be and still maintain adequate signal-to-noise ratio (S/N), while the multiple-tablet imaging experiment gives an indication of how many samples can be analyzed simultaneously while maintaining an adequate S/N and pixel coverage on each sample.

Organic light emitting board for dynamic interactive display

PubMed Central

Kim, Eui Hyuk; Cho, Sung Hwan; Lee, Ju Han; Jeong, Beomjin; Kim, Richard Hahnkee; Yu, Seunggun; Lee, Tae-Woo; Shim, Wooyoung; Park, Cheolmin

2017-01-01

Interactive displays involve the interfacing of a stimuli-responsive sensor with a visual human-readable response. Here, we describe a polymeric electroluminescence-based stimuli-responsive display method that simultaneously detects external stimuli and visualizes the stimulant object. This organic light-emitting board is capable of both sensing and direct visualization of a variety of conductive information. Simultaneous sensing and visualization of the conductive substance is achieved when the conductive object is coupled with the light emissive material layer on application of alternating current. A variety of conductive materials can be detected regardless of their work functions, and thus information written by a conductive pen is clearly visualized, as is a human fingerprint with natural conductivity. Furthermore, we demonstrate that integration of the organic light-emitting board with a fluidic channel readily allows for dynamic monitoring of metallic liquid flow through the channel, which may be suitable for biological detection and imaging applications. PMID:28406151

Organic light emitting board for dynamic interactive display

NASA Astrophysics Data System (ADS)

Kim, Eui Hyuk; Cho, Sung Hwan; Lee, Ju Han; Jeong, Beomjin; Kim, Richard Hahnkee; Yu, Seunggun; Lee, Tae-Woo; Shim, Wooyoung; Park, Cheolmin

2017-04-01

Interactive displays involve the interfacing of a stimuli-responsive sensor with a visual human-readable response. Here, we describe a polymeric electroluminescence-based stimuli-responsive display method that simultaneously detects external stimuli and visualizes the stimulant object. This organic light-emitting board is capable of both sensing and direct visualization of a variety of conductive information. Simultaneous sensing and visualization of the conductive substance is achieved when the conductive object is coupled with the light emissive material layer on application of alternating current. A variety of conductive materials can be detected regardless of their work functions, and thus information written by a conductive pen is clearly visualized, as is a human fingerprint with natural conductivity. Furthermore, we demonstrate that integration of the organic light-emitting board with a fluidic channel readily allows for dynamic monitoring of metallic liquid flow through the channel, which may be suitable for biological detection and imaging applications.

Oxygen sensing PLIM together with FLIM of intrinsic cellular fluorophores for metabolic mapping

NASA Astrophysics Data System (ADS)

Kalinina, Sviatlana; Schaefer, Patrick; Breymayer, Jasmin; Bisinger, Dominik; Chakrabortty, Sabyasachi; Rueck, Angelika

2018-02-01

Otical imaging techniques based on time correlated single photon counting (TCSPC) has found wide applications in medicine and biology. Non-invasive and information-rich fluorescence lifetime imaging microscopy (FLIM) is successfully used for monitoring fluorescent intrinsic metabolic coenzymes as NAD(P)H (nicotinamide adenine dinucleotide (phosphate)) and FAD+ (flavin adenine dinucleotide) in living cells and tissues. The ratio between proteinbound and free coenzymes gives an information about the balance between oxidative phosphorylation and glycolysis in the cells. The changes of the ratio reflects major cellular disorders. A correlation exists between metabolic activity, redox ratio and fluorescence lifetime during stem cell differentiation, neurodegenerative diseases, and carcinogenesis. A multichannel FLIM detection system was designed for monitoring the redox state of NAD(P)H and FAD+ and other intrinsic fluorophores as protoporphyrin IX. In addition, the unique upgrade is useful to perform FLIM and PLIM (phosphorescence lifetime imaging microscopy) simultaneously. PLIM is a promising method to investigate oxygen sensing in biomedical samples. In detail, the oxygen-dependent quenching of phosphorescence of some compounds as transition metal complexes enables measuring of oxygen partial pressure (pO2). Using a two-channel FLIM/PLIM system we monitored intrinsic pO2 by PLIM simultaneously with NAD(P)H by FLIM providing complex metabolic and redox imaging of living cells. Physico-chemical properties of oxygen sensitive probes define certain parameters including their localisation. We present results of some ruthenium based complexes including those specifically bound to mitochondria.

Cross-calibration of the Landsat-7 ETM+ and Landsat-5 TM with the ResourceSat-1 (IRS-P6) AWiFS and LISS-III sensors

USGS Publications Warehouse

Chander, G.; Scaramuzza, P.L.

2006-01-01

Increasingly, data from multiple sensors are used to gain a more complete understanding of land surface processes at a variety of scales. The Landsat suite of satellites has collected the longest continuous archive of multispectral data. The ResourceSat-1 Satellite (also called as IRS-P6) was launched into the polar sunsynchronous orbit on Oct 17, 2003. It carries three remote sensing sensors: the High Resolution Linear Imaging Self-Scanner (LISS-IV), Medium Resolution Linear Imaging Self-Scanner (LISS-III), and the Advanced Wide Field Sensor (AWiFS). These three sensors are used together to provide images with different resolution and coverage. To understand the absolute radiometric calibration accuracy of IRS-P6 AWiFS and LISS-III sensors, image pairs from these sensors were compared to the Landsat-5 TM and Landsat-7 ETM+ sensors. The approach involved the calibration of nearly simultaneous surface observations based on image statistics from areas observed simultaneously by the two sensors.

Ratiometric Imaging Using a Single Dye Enables Simultaneous Visualization of Rac1 and Cdc42 Activation.

PubMed

MacNevin, Christopher J; Toutchkine, Alexei; Marston, Daniel J; Hsu, Chia-Wen; Tsygankov, Denis; Li, Li; Liu, Bei; Qi, Timothy; Nguyen, Dan-Vinh; Hahn, Klaus M

2016-03-02

Biosensors that report endogenous protein activity in vivo can be based on environment-sensing fluorescent dyes. The dyes can be attached to reagents that bind selectively to a specific conformation of the targeted protein, such that binding leads to a fluorescence change. Dyes that are sufficiently bright for use at low, nonperturbing intracellular concentrations typically undergo changes in intensity rather than the shifts in excitation or emission maxima that would enable precise quantitation through ratiometric imaging. We report here mero199, an environment-sensing dye that undergoes a 33 nm solvent-dependent shift in excitation. The dye was used to generate a ratiometric biosensor of Cdc42 (CRIB199) without the need for additional fluorophores. CRIB199 was used in the same cell with a FRET sensor of Rac1 activation to simultaneously observe Cdc42 and Rac1 activity in cellular protrusions, indicating that Rac1 but not Cdc42 activity was reduced during tail retraction, and specific protrusions had reduced Cdc42 activity. A novel program (EdgeProps) used to correlate localized activation with cell edge dynamics indicated that Rac1 was specifically reduced during retraction.

Joint Segmentation of Anatomical and Functional Images: Applications in Quantification of Lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT Images

PubMed Central

Bagci, Ulas; Udupa, Jayaram K.; Mendhiratta, Neil; Foster, Brent; Xu, Ziyue; Yao, Jianhua; Chen, Xinjian; Mollura, Daniel J.

2013-01-01

We present a novel method for the joint segmentation of anatomical and functional images. Our proposed methodology unifies the domains of anatomical and functional images, represents them in a product lattice, and performs simultaneous delineation of regions based on random walk image segmentation. Furthermore, we also propose a simple yet effective object/background seed localization method to make the proposed segmentation process fully automatic. Our study uses PET, PET-CT, MRI-PET, and fused MRI-PET-CT scans (77 studies in all) from 56 patients who had various lesions in different body regions. We validated the effectiveness of the proposed method on different PET phantoms as well as on clinical images with respect to the ground truth segmentation provided by clinicians. Experimental results indicate that the presented method is superior to threshold and Bayesian methods commonly used in PET image segmentation, is more accurate and robust compared to the other PET-CT segmentation methods recently published in the literature, and also it is general in the sense of simultaneously segmenting multiple scans in real-time with high accuracy needed in routine clinical use. PMID:23837967

Research on compressive sensing reconstruction algorithm based on total variation model

NASA Astrophysics Data System (ADS)

Gao, Yu-xuan; Sun, Huayan; Zhang, Tinghua; Du, Lin

2017-12-01

Compressed sensing for breakthrough Nyquist sampling theorem provides a strong theoretical , making compressive sampling for image signals be carried out simultaneously. In traditional imaging procedures using compressed sensing theory, not only can it reduces the storage space, but also can reduce the demand for detector resolution greatly. Using the sparsity of image signal, by solving the mathematical model of inverse reconfiguration, realize the super-resolution imaging. Reconstruction algorithm is the most critical part of compression perception, to a large extent determine the accuracy of the reconstruction of the image.The reconstruction algorithm based on the total variation (TV) model is more suitable for the compression reconstruction of the two-dimensional image, and the better edge information can be obtained. In order to verify the performance of the algorithm, Simulation Analysis the reconstruction result in different coding mode of the reconstruction algorithm based on the TV reconstruction algorithm. The reconstruction effect of the reconfigurable algorithm based on TV based on the different coding methods is analyzed to verify the stability of the algorithm. This paper compares and analyzes the typical reconstruction algorithm in the same coding mode. On the basis of the minimum total variation algorithm, the Augmented Lagrangian function term is added and the optimal value is solved by the alternating direction method.Experimental results show that the reconstruction algorithm is compared with the traditional classical algorithm based on TV has great advantages, under the low measurement rate can be quickly and accurately recovers target image.

Volumetric MRI of the lungs during forced expiration.

PubMed

Berman, Benjamin P; Pandey, Abhishek; Li, Zhitao; Jeffries, Lindsie; Trouard, Theodore P; Oliva, Isabel; Cortopassi, Felipe; Martin, Diego R; Altbach, Maria I; Bilgin, Ali

2016-06-01

Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack-of-stars gradient echo acquisition and compressed sensing reconstruction. A technique for dynamic three-dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data. Dynamic three-dimensional images can be captured at sub-150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of 4.6×4.6×10 mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements. Dynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three-dimensional radial magnetic resonance imaging. Magn Reson Med 75:2295-2302, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Multiresolution motion planning for autonomous agents via wavelet-based cell decompositions.

PubMed

Cowlagi, Raghvendra V; Tsiotras, Panagiotis

2012-10-01

We present a path- and motion-planning scheme that is "multiresolution" both in the sense of representing the environment with high accuracy only locally and in the sense of addressing the vehicle kinematic and dynamic constraints only locally. The proposed scheme uses rectangular multiresolution cell decompositions, efficiently generated using the wavelet transform. The wavelet transform is widely used in signal and image processing, with emerging applications in autonomous sensing and perception systems. The proposed motion planner enables the simultaneous use of the wavelet transform in both the perception and in the motion-planning layers of vehicle autonomy, thus potentially reducing online computations. We rigorously prove the completeness of the proposed path-planning scheme, and we provide numerical simulation results to illustrate its efficacy.

Concurrent Respiratory Motion Correction of Abdominal PET and DCE-MRI using a Compressed Sensing Approach.

PubMed

Fuin, Niccolo; Catalano, Onofrio Antonio; Scipioni, Michele; Canjels, Lisanne P W; Izquierdo, David; Pedemonte, Stefano; Catana, Ciprian

2018-01-25

Purpose: We present an approach for concurrent reconstruction of respiratory motion compensated abdominal DCE-MRI and PET data in an integrated PET/MR scanner. The MR and PET reconstructions share the same motion vector fields (MVFs) derived from radial MR data; the approach is robust to changes in respiratory pattern and do not increase the total acquisition time. Methods: PET and DCE-MRI data of 12 oncological patients were simultaneously acquired for 6 minutes on an integrated PET/MR system after administration of 18 F-FDG and gadoterate meglumine. Golden-angle radial MR data were continuously acquired simultaneously with PET data and sorted into multiple motion phases based on a respiratory signal derived directly from the radial MR data. The resulting multidimensional dataset was reconstructed using a compressed sensing approach that exploits sparsity among respiratory phases. MVFs obtained using the full 6-minute (MC_6-min) and only the last 1 minute (MC_1-min) of data were incorporated into the PET reconstruction to obtain motion-corrected PET images and in an MR iterative reconstruction algorithm to produce a series of motion-corrected DCE-MRI images (moco_GRASP). The motion-correction methods (MC_6-min and MC_1-min) were evaluated by qualitative analysis of the MR images and quantitative analysis of maximum and mean standardized uptake values (SUV max , SUVmean), contrast, signal-to-noise ratio (SNR) and lesion volume in the PET images. Results: Motion corrected MC_6-min PET images demonstrated 30%, 23%, 34% and 18% increases in average SUV max , SUVmean, contrast and SNR, and an average 40% reduction in lesion volume with respect to the non-motion-corrected PET images. The changes in these figures of merit were smaller but still substantial for the MC_1-min protocol: 19%, 10%, 15% and 9% increases in average SUV max , SUVmean, contrast and SNR; and a 28% reduction in lesion volume. Moco_GRASP images were deemed of acceptable or better diagnostic image quality with respect to conventional breath hold cartesian VIBE acquisitions. Conclusion: We presented a method that allows the simultaneous acquisition of respiratory motion-corrected diagnostic quality DCE-MRI and quantitatively accurate PET data in an integrated PET/MR scanner with negligible prolongation in acquisition time compared to routine PET/DCE-MRI protocols. Copyright © 2018 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Multiple-Octave-Spanning Vibration Sensing Based on Simultaneous Vector Demodulation of 499 Fizeau Interference Signals from Identical Ultra-Weak Fiber Bragg Gratings Over 2.5 km.

PubMed

Li, Yi; Qian, Li; Zhou, Ciming; Fan, Dian; Xu, Qiannan; Pang, Yandong; Chen, Xi; Tang, Jianguan

2018-01-12

Multi-point vibration sensing at the low frequency range of 0.5-100 Hz is of vital importance for applications such as seismic monitoring and underwater acoustic imaging. Location-resolved multi-point sensing using a single fiber and a single demodulation system can greatly reduce system deployment and maintenance costs. We propose and demonstrate the demodulation of a fiber-optic system consisting of 500 identical ultra-weak Fiber Bragg gratings (uwFBGs), capable of measuring the amplitude, frequency and phase of acoustic signals from 499 sensing fibers covering a total range of 2.5 km. For demonstration purposes, we arbitrarily chose six consecutive sensors and studied their performance in detail. Using a passive demodulation method, we interrogated the six sensors simultaneously, and achieved a high signal-to-noise ratio of 22.1 dB, excellent linearity, phase sensitivity of around 0.024 rad/Pa, and a dynamic range of about 38 dB. We demonstrated a frequency response flatness of <1.2 dB in the range of 0.5-100 Hz. Compared to the prior state-of-the-art demonstration using a similar method, we have increased the sensing range from 1 km to 2.5 km, and increased the frequency range from 0.4 octaves to 7.6 octaves, in addition to achieving sensing in the very challenging low-frequency range of 0.5-100 Hz.

Multiple-Targeted Graphene-based Nanocarrier for Intracellular Imaging of mRNAs

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

Wang, Ying; Li, Zhaohui; Liu, Misha

Simultaneous detection and imaging of multiple intracellular messenger RNA (mRNAs) hold great significant for early cancer diagnostics and preventive medicine development. Herein, we propose a multiple-targeted graphene oxide (GO) nanocarrier that can simultaneously detect and image different type mRNAs in living cells. First of all, in vitro detection of multiple targets have been realized successfully based on the multiple-targeted GO nanocarrier with linear relationship ranging from 3 nM to 200 nM, as well as sensitive detection limit of 1.84 nM for manganese superoxide dismutase (Mn-SOD) mRNA and 2.45 nM for β-actin mRNA. Additionally, this nanosensing platform composed of fluorescent labeledmore » single strand DNA probes and GO nanocarrier can identify Mn-SOD mRNA and endogenous mRNA of β-actin in living cancer cells, showing rapid response, high specificity, nuclease stability, and good biocompatibility during the cell imaging. Thirdly, changes of the expression levels of mRNA in living cells before or after the drug treatment can be monitored successfully. By using multiple ssDNA as probes and GO nanocarrier as the cellular delivery cargo, the proposed simultaneous multiple-targeted sensing platform will be of great potential as a powerful tool for intracellular trafficking process from basic research to clinical diagnosis.« less

Simultaneous PET/MR imaging with a radio frequency-penetrable PET insert

PubMed Central

Grant, Alexander M.; Lee, Brian J.; Chang, Chen-Ming; Levin, Craig S.

2017-01-01

Purpose A brain sized radio-frequency (RF)-penetrable PET insert has been designed for simultaneous operation with MRI systems. This system takes advantage of electro-optical coupling and battery power to electrically float the PET insert relative to the MRI ground, permitting RF signals to be transmitted through small gaps between the modules that form the PET ring. This design facilitates the use of the built-in body coil for RF transmission, and thus could be inserted into any existing MR site wishing to achieve simultaneous PET/MR imaging. The PET detectors employ non-magnetic silicon photomultipliers in conjunction with a compressed sensing signal multiplexing scheme, and optical fibers to transmit analog PET detector signals out of the MRI room for decoding, processing, and image reconstruction. Methods The PET insert was first constructed and tested in a laboratory benchtop setting, where tomographic images of a custom resolution phantom were successfully acquired. The PET insert was then placed within a 3T body MRI system, and tomographic resolution/contrast phantom images were acquired both with only the B0 field present, and under continuous pulsing from different MR imaging sequences. Results The resulting PET images have comparable contrast-to-noise ratios (CNR) under all MR pulsing conditions: the maximum percent CNR relative difference for each rod type among all four PET images acquired in the MRI system has a mean of 14.0±7.7%. MR images were successfully acquired through the RF-penetrable PET shielding using only the built-in MR body coil, suggesting that simultaneous imaging is possible without significant mutual interference. Conclusions These results show promise for this technology as an alternative to costly integrated PET/MR scanners; a PET insert that is compatible with any existing clinical MRI system could greatly increase the availability, accessibility, and dissemination of PET/MR. PMID:28102949

Continuous blood pressure recordings simultaneously with functional brain imaging: studies of the glymphatic system

NASA Astrophysics Data System (ADS)

Zienkiewicz, Aleksandra; Huotari, Niko; Raitamaa, Lauri; Raatikainen, Ville; Ferdinando, Hany; Vihriälä, Erkki; Korhonen, Vesa; Myllylä, Teemu; Kiviniemi, Vesa

2017-03-01

The lymph system is responsible for cleaning the tissues of metabolic waste products, soluble proteins and other harmful fluids etc. Lymph flow in the body is driven by body movements and muscle contractions. Moreover, it is indirectly dependent on the cardiovascular system, where the heart beat and blood pressure maintain force of pressure in lymphatic channels. Over the last few years, studies revealed that the brain contains the so-called glymphatic system, which is the counterpart of the systemic lymphatic system in the brain. Similarly, the flow in the glymphatic system is assumed to be mostly driven by physiological pulsations such as cardiovascular pulses. Thus, continuous measurement of blood pressure and heart function simultaneously with functional brain imaging is of great interest, particularly in studies of the glymphatic system. We present our MRI compatible optics based sensing system for continuous blood pressure measurement and show our current results on the effects of blood pressure variations on cerebral brain dynamics, with a focus on the glymphatic system. Blood pressure was measured simultaneously with near-infrared spectroscopy (NIRS) combined with an ultrafast functional brain imaging (fMRI) sequence magnetic resonance encephalography (MREG, 3D brain 10 Hz sampling rate).

Active pixel sensor array with multiresolution readout

NASA Technical Reports Server (NTRS)

Fossum, Eric R. (Inventor); Kemeny, Sabrina E. (Inventor); Pain, Bedabrata (Inventor)

1999-01-01

An imaging device formed as a monolithic complementary metal oxide semiconductor integrated circuit in an industry standard complementary metal oxide semiconductor process, the integrated circuit including a focal plane array of pixel cells, each one of the cells including a photogate overlying the substrate for accumulating photo-generated charge in an underlying portion of the substrate and a charge coupled device section formed on the substrate adjacent the photogate having a sensing node and at least one charge coupled device stage for transferring charge from the underlying portion of the substrate to the sensing node. There is also a readout circuit, part of which can be disposed at the bottom of each column of cells and be common to all the cells in the column. The imaging device can also include an electronic shutter formed on the substrate adjacent the photogate, and/or a storage section to allow for simultaneous integration. In addition, the imaging device can include a multiresolution imaging circuit to provide images of varying resolution. The multiresolution circuit could also be employed in an array where the photosensitive portion of each pixel cell is a photodiode. This latter embodiment could further be modified to facilitate low light imaging.

GPU implementation of prior image constrained compressed sensing (PICCS)

NASA Astrophysics Data System (ADS)

Nett, Brian E.; Tang, Jie; Chen, Guang-Hong

2010-04-01

The Prior Image Constrained Compressed Sensing (PICCS) algorithm (Med. Phys. 35, pg. 660, 2008) has been applied to several computed tomography applications with both standard CT systems and flat-panel based systems designed for guiding interventional procedures and radiation therapy treatment delivery. The PICCS algorithm typically utilizes a prior image which is reconstructed via the standard Filtered Backprojection (FBP) reconstruction algorithm. The algorithm then iteratively solves for the image volume that matches the measured data, while simultaneously assuring the image is similar to the prior image. The PICCS algorithm has demonstrated utility in several applications including: improved temporal resolution reconstruction, 4D respiratory phase specific reconstructions for radiation therapy, and cardiac reconstruction from data acquired on an interventional C-arm. One disadvantage of the PICCS algorithm, just as other iterative algorithms, is the long computation times typically associated with reconstruction. In order for an algorithm to gain clinical acceptance reconstruction must be achievable in minutes rather than hours. In this work the PICCS algorithm has been implemented on the GPU in order to significantly reduce the reconstruction time of the PICCS algorithm. The Compute Unified Device Architecture (CUDA) was used in this implementation.

Interferometer design and controls for pulse stacking in high power fiber lasers

NASA Astrophysics Data System (ADS)

Wilcox, Russell; Yang, Yawei; Dahlen, Dar; Xu, Yilun; Huang, Gang; Qiang, Du; Doolittle, Lawrence; Byrd, John; Leemans, Wim; Ruppe, John; Zhou, Tong; Sheikhsofla, Morteza; Nees, John; Galvanauskas, Almantas; Dawson, Jay; Chen, Diana; Pax, Paul

2017-03-01

In order to develop a design for a laser-plasma accelerator (LPA) driver, we demonstrate key technologies that enable fiber lasers to produce high energy, ultrafast pulses. These technologies must be scalable, and operate in the presence of thermal drift, acoustic noise, and other perturbations typical of an operating system. We show that coherent pulse stacking (CPS), which requires optical interferometers, can be made robust by image-relaying, multipass optical cavities, and by optical phase control schemes that sense pulse train amplitudes from each cavity. A four-stage pulse stacking system using image-relaying cavities is controlled for 14 hours using a pulse-pattern sensing algorithm. For coherent addition of simultaneous ultrafast pulses, we introduce a new scheme using diffractive optics, and show experimentally that four pulses can be added while a preserving pulse width of 128 fs.

Imaging Science Panel. Multispectral Imaging Science Working Group joint meeting with Information Science Panel: Introduction

NASA Technical Reports Server (NTRS)

1982-01-01

The state-of-the-art of multispectral sensing is reviewed and recommendations for future research and development are proposed. specifically, two generic sensor concepts were discussed. One is the multispectral pushbroom sensor utilizing linear array technology which operates in six spectral bands including two in the SWIR region and incorporates capabilities for stereo and crosstrack pointing. The second concept is the imaging spectrometer (IS) which incorporates a dispersive element and area arrays to provide both spectral and spatial information simultaneously. Other key technology areas included very large scale integration and the computer aided design of these devices.

Simultaneous measurement of breathing rate and heart rate using a microbend multimode fiber optic sensor

NASA Astrophysics Data System (ADS)

Chen, Zhihao; Lau, Doreen; Teo, Ju Teng; Ng, Soon Huat; Yang, Xiufeng; Kei, Pin Lin

2014-05-01

We propose and demonstrate the feasibility of using a highly sensitive microbend multimode fiber optic sensor for simultaneous measurement of breathing rate (BR) and heart rate (HR). The sensing system consists of a transceiver, microbend multimode fiber, and a computer. The transceiver is comprised of an optical transmitter, an optical receiver, and circuits for data communication with the computer via Bluetooth. Comparative experiments conducted between the sensor and predicate commercial physiologic devices showed an accuracy of ±2 bpm for both BR and HR measurement. Our preliminary study of simultaneous measurement of BR and HR in a clinical trial conducted on 11 healthy subjects during magnetic resonance imaging (MRI) also showed very good agreement with measurements obtained from conventional MR-compatible devices.

Electro-optic Imaging Fourier Transform Spectrometer

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

2005-01-01

JPL is developing an innovative compact, low mass, Electro-Optic Imaging Fourier Transform Spectrometer (E-O IFTS) for hyperspectral imaging applications. The spectral region of this spectrometer will be 1 - 2.5 micron (1000-4000/cm) to allow high-resolution, high-speed hyperspectral imaging applications. One application will be the remote sensing of the measurement of a large number of different atmospheric gases simultaneously in the same airmass. Due to the use of a combination of birefringent phase retarders and multiple achromatic phase switches to achieve phase delay, this spectrometer is capable of hyperspectral measurements similar to that of the conventional Fourier transform spectrometer but without any moving parts. In this paper, the principle of operations, system architecture and recent experimental progress will be presented.

Electro-optic Imaging Fourier Transform Spectrometer

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin

2005-01-01

JPL is developing an innovative compact, low mass, Electro-Optic Imaging Fourier Transform Spectrometer (E-0IFTS) for hyperspectral imaging applications. The spectral region of this spectrometer will be 1 - 2.5 pm (1000 -4000 cm-') to allow high-resolution, high-speed hyperspectral imaging applications [l-51. One application will be theremote sensing of the measurement of a large number of different atmospheric gases simultaneously in the sameairmass. Due to the use of a combination of birefiingent phase retarders and multiple achromatic phase switches toachieve phase delay, this spectrometer is capable of hyperspectral measurements similar to that of the conventionalFourier transform spectrometer but without any moving parts. In this paper, the principle of operations, systemarchitecture and recent experimental progress will be presen.

Computational and design methods for advanced imaging

NASA Astrophysics Data System (ADS)

Birch, Gabriel C.

This dissertation merges the optical design and computational aspects of imaging systems to create novel devices that solve engineering problems in optical science and attempts to expand the solution space available to the optical designer. This dissertation is divided into two parts: the first discusses a new active illumination depth sensing modality, while the second part discusses a passive illumination system called plenoptic, or lightfield, imaging. The new depth sensing modality introduced in part one is called depth through controlled aberration. This technique illuminates a target with a known, aberrated projected pattern and takes an image using a traditional, unmodified imaging system. Knowing how the added aberration in the projected pattern changes as a function of depth, we are able to quantitatively determine depth of a series of points from the camera. A major advantage this method permits is the ability for illumination and imaging axes to be coincident. Plenoptic cameras capture both spatial and angular data simultaneously. This dissertation present a new set of parameters that permit the design and comparison of plenoptic devices outside the traditionally published plenoptic 1.0 and plenoptic 2.0 configurations. Additionally, a series of engineering advancements are presented, including full system raytraces of raw plenoptic images, Zernike compression techniques of raw image files, and non-uniform lenslet arrays to compensate for plenoptic system aberrations. Finally, a new snapshot imaging spectrometer is proposed based off the plenoptic configuration.

Accelerated Fast Spin-Echo Magnetic Resonance Imaging of the Heart Using a Self-Calibrated Split-Echo Approach

PubMed Central

Klix, Sabrina; Hezel, Fabian; Fuchs, Katharina; Ruff, Jan; Dieringer, Matthias A.; Niendorf, Thoralf

2014-01-01

Purpose Design, validation and application of an accelerated fast spin-echo (FSE) variant that uses a split-echo approach for self-calibrated parallel imaging. Methods For self-calibrated, split-echo FSE (SCSE-FSE), extra displacement gradients were incorporated into FSE to decompose odd and even echo groups which were independently phase encoded to derive coil sensitivity maps, and to generate undersampled data (reduction factor up to R = 3). Reference and undersampled data were acquired simultaneously. SENSE reconstruction was employed. Results The feasibility of SCSE-FSE was demonstrated in phantom studies. Point spread function performance of SCSE-FSE was found to be competitive with traditional FSE variants. The immunity of SCSE-FSE for motion induced mis-registration between reference and undersampled data was shown using a dynamic left ventricular model and cardiac imaging. The applicability of black blood prepared SCSE-FSE for cardiac imaging was demonstrated in healthy volunteers including accelerated multi-slice per breath-hold imaging and accelerated high spatial resolution imaging. Conclusion SCSE-FSE obviates the need of external reference scans for SENSE reconstructed parallel imaging with FSE. SCSE-FSE reduces the risk for mis-registration between reference scans and accelerated acquisitions. SCSE-FSE is feasible for imaging of the heart and of large cardiac vessels but also meets the needs of brain, abdominal and liver imaging. PMID:24728341

Design, development, and testing of the DCT Cassegrain instrument support assembly

NASA Astrophysics Data System (ADS)

Bida, Thomas A.; Dunham, Edward W.; Nye, Ralph A.; Chylek, Tomas; Oliver, Richard C.

2012-09-01

The 4.3m Discovery Channel Telescope delivers an f/6.1 unvignetted 0.5° field to its RC focal plane. In order to support guiding, wavefront sensing, and instrument installations, a Cassegrain instrument support assembly has been developed which includes a facility guider and wavefront sensor package (GWAVES) and multiple interfaces for instrumentation. A 2-element, all-spherical, fused-silica corrector compensates for field curvature and astigmatism over the 0.5° FOV, while reducing ghost pupil reflections to minimal levels. Dual roving GWAVES camera probes pick off stars in the outer annulus of the corrected field, providing simultaneous guiding and wavefront sensing for telescope operations. The instrument cube supports 5 co-mounted instruments with rapid feed selection via deployable fold mirrors. The corrected beam passes through a dual filter wheel before imaging with the 6K x 6K single CCD of the Large Monolithic Imager (LMI). We describe key development strategies for the DCT Cassegrain instrument assembly and GWAVES, including construction of a prime focus test assembly with wavefront sensor utilized in fall 2011 to begin characterization of the DCT primary mirror support. We also report on 2012 on-sky test results of wavefront sensing, guiding, and imaging with the integrated Cassegrain cube.

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

Borot de Battisti, M; Maenhout, M; Lagendijk, J J W

Purpose: This study assesses the potential of Fiber Bragg Grating (FBG)-based sensing for real-time needle (including catheter or tube) tracking during MR-guided HDR brachytherapy. Methods: The proposed FBG-based sensing tracking approach involves a MR-compatible stylet composed of three optic fibers with nine sets of embedded FBG sensors each. When the stylet is inserted inside the lumen of the needle, the FBG sensing system can measure the needle’s deflection. For localization of the needle in physical space, the position and orientation of the stylet base are mandatory. For this purpose, we propose to fix the stylet base and determine its positionmore » and orientation using a MR-based calibration as follows. First, the deflection of a needle inserted in a phantom in two different configurations is measured during simultaneous MR-imaging. Then, after segmentation of the needle shapes on the MR-images, the position and orientation of the stylet base is determined using a rigid registration of the needle shapes on both MR and FBG-based measurements. The calibration method was assessed by measuring the deflection of a needle in a prostate phantom in five different configurations using FBG-based sensing during simultaneous MR-imaging. Any two needle shapes were employed for the calibration step and the proposed FGB-tracking approach was subsequently evaluated on the other three needles configurations. The tracking accuracy was evaluated by computing the Euclidian distance between the 3D FBG vs. MR-based measurements. Results: Over all needle shapes tested, the average(standard deviation) Euclidian distance between the FBG and MR-based measurements was 0.79mm(0.37mm). The update rate and latency of the FBG-based measurements were 100ms and 300ms respectively. Conclusion: The proposed FBG-based protocol can measure the needle position with an accuracy, precision, update rate and latency eligible for accurate needle steering during MR-guided HDR brachytherapy. M. Borot de Battisti is funded by Philips Medical Systems Nederland B.V.; M. Moerland is principal investigator on a contract funded by Philips Medical Systems Nederland B.V.; G. Hautvast and D. Binnekamp are fulltime employees of Philips Medical Systems Nederland B.V.« less

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

Coil compression in simultaneous multislice functional MRI with concentric ring slice-GRAPPA and SENSE.

PubMed

Chu, Alan; Noll, Douglas C

2016-10-01

Simultaneous multislice (SMS) imaging is a useful way to accelerate functional magnetic resonance imaging (fMRI). As acceleration becomes more aggressive, an increasingly larger number of receive coils are required to separate the slices, which significantly increases the computational burden. We propose a coil compression method that works with concentric ring non-Cartesian SMS imaging and should work with Cartesian SMS as well. We evaluate the method on fMRI scans of several subjects and compare it to standard coil compression methods. The proposed method uses a slice-separation k-space kernel to simultaneously compress coil data into a set of virtual coils. Five subjects were scanned using both non-SMS fMRI and SMS fMRI with three simultaneous slices. The SMS fMRI scans were processed using the proposed method, along with other conventional methods. Code is available at https://github.com/alcu/sms. The proposed method maintained functional activation with a fewer number of virtual coils than standard SMS coil compression methods. Compression of non-SMS fMRI maintained activation with a slightly lower number of virtual coils than the proposed method, but does not have the acceleration advantages of SMS fMRI. The proposed method is a practical way to compress and reconstruct concentric ring SMS data and improves the preservation of functional activation over standard coil compression methods in fMRI. Magn Reson Med 76:1196-1209, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

The design of atmosphere polarimetry sensing with multi-bands

NASA Astrophysics Data System (ADS)

Dou, Chenhao; Wang, Shurong; Zhang, Zihui; Huang, Yu; Yang, Xiaohu; Li, Bo

2018-03-01

A new aerosol and cloud polarimetry sensing (ACPS) has been presented to measure four polarization components of eight specific wavelengths selected from 400 ∼ 2400 nm simultaneously. The ACPS system can provide high accurate polarized intensity components of atmospheric radiance with a simple and compact structure. The ACPS structure can be regarded as a 4- f Fourier optics system. It takes Wollaston prisms as polarimeters, uses filters and slits to select the appropriate wavelength, and locates the monochromatic polarized light images on different places of focal plane. In our approach, the visible Part 1 is designed as an example and all fields MTFs of Part 1 are larger than 0.5 at detectors' Nyquist frequency 20 lp/mm.

Single-sensor multispeaker listening with acoustic metamaterials

PubMed Central

Xie, Yangbo; Tsai, Tsung-Han; Konneker, Adam; Popa, Bogdan-Ioan; Brady, David J.; Cummer, Steven A.

2015-01-01

Designing a “cocktail party listener” that functionally mimics the selective perception of a human auditory system has been pursued over the past decades. By exploiting acoustic metamaterials and compressive sensing, we present here a single-sensor listening device that separates simultaneous overlapping sounds from different sources. The device with a compact array of resonant metamaterials is demonstrated to distinguish three overlapping and independent sources with 96.67% correct audio recognition. Segregation of the audio signals is achieved using physical layer encoding without relying on source characteristics. This hardware approach to multichannel source separation can be applied to robust speech recognition and hearing aids and may be extended to other acoustic imaging and sensing applications. PMID:26261314

The NASA Airborne Earth Science Microwave Imaging Radiometer (AESMIR): A New Sensor for Earth Remote Sensing

NASA Technical Reports Server (NTRS)

Kim, Edward

2003-01-01

The Airborne Earth Science Microwave Imaging Radiometer (AESMIR) is a versatile new airborne imaging radiometer recently developed by NASA. The AESMIR design is unique in that it performs dual-polarized imaging at all standard passive microwave frequency bands (6-89 GHz) using only one sensor headscanner package, providing an efficient solution for Earth remote sensing applications (snow, soil moisture/land parameters, precipitation, ocean winds, sea surface temperature, water vapor, sea ice, etc.). The microwave radiometers themselves will incorporate state-of-the-art receivers, with particular attention given to instrument calibration for the best possible accuracy and sensitivity. The single-package design of AESMIR makes it compatible with high-altitude aircraft platforms such as the NASA ER-2s. The arbitrary 2-axis gimbal can perform conical and cross-track scanning, as well as fixed-beam staring. This compatibility with high-altitude platforms coupled with the flexible scanning configuration, opens up previously unavailable science opportunities for convection/precip/cloud science and co-flying with complementary instruments, as well as providing wider swath coverage for all science applications. By designing AESMIR to be compatible with these high-altitude platforms, we are also compatible with the NASA P-3, the NASA DC-8, C-130s and ground-based deployments. Thus AESMIR can provide low-, mid-, and high- altitude microwave imaging. Parallel filter banks allow AESMIR to simultaneously simulate the exact passbands of multiple satellite radiometers: SSM/I, TMI, AMSR, Windsat, SSMI/S, and the upcoming GPM/GMI and NPOESS/CMIS instruments --a unique capability among aircraft radiometers. An L-band option is also under development, again using the same scanner. With this option, simultaneous imaging from 1.4 to 89 GHz will be feasible. And, all receivers except the sounding channels will be configured for 4-Stokes polarimetric operation using high-speed digital correlators in the near future. The capabilities and unique design features of this new sensor will be described, and example imagery will be presented.

Micro-optical system based 3D imaging for full HD depth image capturing

NASA Astrophysics Data System (ADS)

Park, Yong-Hwa; Cho, Yong-Chul; You, Jang-Woo; Park, Chang-Young; Yoon, Heesun; Lee, Sang-Hun; Kwon, Jong-Oh; Lee, Seung-Wan

2012-03-01

20 Mega-Hertz-switching high speed image shutter device for 3D image capturing and its application to system prototype are presented. For 3D image capturing, the system utilizes Time-of-Flight (TOF) principle by means of 20MHz high-speed micro-optical image modulator, so called 'optical shutter'. The high speed image modulation is obtained using the electro-optic operation of the multi-layer stacked structure having diffractive mirrors and optical resonance cavity which maximizes the magnitude of optical modulation. The optical shutter device is specially designed and fabricated realizing low resistance-capacitance cell structures having small RC-time constant. The optical shutter is positioned in front of a standard high resolution CMOS image sensor and modulates the IR image reflected from the object to capture a depth image. Suggested novel optical shutter device enables capturing of a full HD depth image with depth accuracy of mm-scale, which is the largest depth image resolution among the-state-of-the-arts, which have been limited up to VGA. The 3D camera prototype realizes color/depth concurrent sensing optical architecture to capture 14Mp color and full HD depth images, simultaneously. The resulting high definition color/depth image and its capturing device have crucial impact on 3D business eco-system in IT industry especially as 3D image sensing means in the fields of 3D camera, gesture recognition, user interface, and 3D display. This paper presents MEMS-based optical shutter design, fabrication, characterization, 3D camera system prototype and image test results.

Potentiometric Dye Imaging for Pheochromocytoma and Cortical Neurons with a Novel Measurement System Using an Integrated Complementary Metal-Oxide-Semiconductor Imaging Device

NASA Astrophysics Data System (ADS)

Kobayashi, Takuma; Tagawa, Ayato; Noda, Toshihiko; Sasagawa, Kiyotaka; Tokuda, Takashi; Hatanaka, Yumiko; Tamura, Hideki; Ishikawa, Yasuyuki; Shiosaka, Sadao; Ohta, Jun

2010-11-01

The combination of optical imaging with voltage-sensitive dyes is a powerful tool for studying the spatiotemporal patterns of neural activity and understanding the neural networks of the brain. To visualize the potential status of multiple neurons simultaneously using a compact instrument with high density and a wide range, we present a novel measurement system using an implantable biomedical photonic LSI device with a red absorptive light filter for voltage-sensitive dye imaging (BpLSI-red). The BpLSI-red was developed for sensing fluorescence by the on-chip LSI, which was designed by using complementary metal-oxide-semiconductor (CMOS) technology. A micro-electro-mechanical system (MEMS) microfabrication technique was used to postprocess the CMOS sensor chip; light-emitting diodes (LEDs) were integrated for illumination and to enable long-term cell culture. Using the device, we succeeded in visualizing the membrane potential of 2000-3000 cells and the process of depolarization of pheochromocytoma cells (PC12 cells) and mouse cerebral cortical neurons in a primary culture with cellular resolution. Therefore, our measurement application enables the detection of multiple neural activities simultaneously.

Remote Acoustic Imaging of Geosynchronous Satellites

NASA Astrophysics Data System (ADS)

Watson, Z.; Hart, M.

Identification and characterization of orbiting objects that are not spatially resolved are challenging problems for traditional remote sensing methods. Hyper temporal imaging, enabled by fast, low-noise electro-optical detectors is a new sensing modality which may allow the direct detection of acoustic resonances on satellites enabling a new regime of signature and state detection. Detectable signatures may be caused by the oscillations of solar panels, high-gain antennae, or other on-board subsystems driven by thermal gradients, fluctuations in solar radiation pressure, worn reaction wheels, or orbit maneuvers. Herein we present the first hyper-temporal observations of geosynchronous satellites. Data were collected at the Kuiper 1.54-meter telescope in Arizona using an experimental dual-channel imaging instrument that simultaneously measures light in two orthogonally polarized beams at sampling rates extending up to 1 kHz. In these observations, we see evidence of acoustic resonances in the polarization state of satellites. The technique is expected to support object identification and characterization of on-board components and to act as a discriminant between active satellites, debris, and passive bodies.

Integrating Remote Sensing Data with Directional Two- Dimensional Wavelet Analysis and Open Geospatial Techniques for Efficient Disaster Monitoring and Management.

PubMed

Lin, Yun-Bin; Lin, Yu-Pin; Deng, Dong-Po; Chen, Kuan-Wei

2008-02-19

In Taiwan, earthquakes have long been recognized as a major cause oflandslides that are wide spread by floods brought by typhoons followed. Distinguishingbetween landslide spatial patterns in different disturbance regimes is fundamental fordisaster monitoring, management, and land-cover restoration. To circumscribe landslides,this study adopts the normalized difference vegetation index (NDVI), which can bedetermined by simply applying mathematical operations of near-infrared and visible-redspectral data immediately after remotely sensed data is acquired. In real-time disastermonitoring, the NDVI is more effective than using land-cover classifications generatedfrom remotely sensed data as land-cover classification tasks are extremely time consuming.Directional two-dimensional (2D) wavelet analysis has an advantage over traditionalspectrum analysis in that it determines localized variations along a specific direction whenidentifying dominant modes of change, and where those modes are located in multi-temporal remotely sensed images. Open geospatial techniques comprise a series ofsolutions developed based on Open Geospatial Consortium specifications that can beapplied to encode data for interoperability and develop an open geospatial service for sharing data. This study presents a novel approach and framework that uses directional 2Dwavelet analysis of real-time NDVI images to effectively identify landslide patterns andshare resulting patterns via open geospatial techniques. As a case study, this study analyzedNDVI images derived from SPOT HRV images before and after the ChiChi earthquake(7.3 on the Richter scale) that hit the Chenyulan basin in Taiwan, as well as images aftertwo large typhoons (Xangsane and Toraji) to delineate the spatial patterns of landslidescaused by major disturbances. Disturbed spatial patterns of landslides that followed theseevents were successfully delineated using 2D wavelet analysis, and results of patternrecognitions of landslides were distributed simultaneously to other agents using geographymarkup language. Real-time information allows successive platforms (agents) to work withlocal geospatial data for disaster management. Furthermore, the proposed is suitable fordetecting landslides in various regions on continental, regional, and local scales usingremotely sensed data in various resolutions derived from SPOT HRV, IKONOS, andQuickBird multispectral images.

Half-quadratic variational regularization methods for speckle-suppression and edge-enhancement in SAR complex image

NASA Astrophysics Data System (ADS)

Zhao, Xia; Wang, Guang-xin

2008-12-01

Synthetic aperture radar (SAR) is an active remote sensing sensor. It is a coherent imaging system, the speckle is its inherent default, which affects badly the interpretation and recognition of the SAR targets. Conventional methods of removing the speckle is studied usually in real SAR image, which reduce the edges of the images at the same time as depressing the speckle. Morever, Conventional methods lost the information about images phase. Removing the speckle and enhancing the target and edge simultaneously are still a puzzle. To suppress the spckle and enhance the targets and the edges simultaneously, a half-quadratic variational regularization method in complex SAR image is presented, which is based on the prior knowledge of the targets and the edge. Due to the non-quadratic and non- convex quality and the complexity of the cost function, a half-quadratic variational regularization variation is used to construct a new cost function,which is solved by alternate optimization. In the proposed scheme, the construction of the model, the solution of the model and the selection of the model peremeters are studied carefully. In the end, we validate the method using the real SAR data.Theoretic analysis and the experimental results illustrate the the feasibility of the proposed method. Further more, the proposed method can preserve the information about images phase.

Compressive Coded-Aperture Multimodal Imaging Systems

NASA Astrophysics Data System (ADS)

Rueda-Chacon, Hoover F.

Multimodal imaging refers to the framework of capturing images that span different physical domains such as space, spectrum, depth, time, polarization, and others. For instance, spectral images are modeled as 3D cubes with two spatial and one spectral coordinate. Three-dimensional cubes spanning just the space domain, are referred as depth volumes. Imaging cubes varying in time, spectra or depth, are referred as 4D-images. Nature itself spans different physical domains, thus imaging our real world demands capturing information in at least 6 different domains simultaneously, giving turn to 3D-spatial+spectral+polarized dynamic sequences. Conventional imaging devices, however, can capture dynamic sequences with up-to 3 spectral channels, in real-time, by the use of color sensors. Capturing multiple spectral channels require scanning methodologies, which demand long time. In general, to-date multimodal imaging requires a sequence of different imaging sensors, placed in tandem, to simultaneously capture the different physical properties of a scene. Then, different fusion techniques are employed to mix all the individual information into a single image. Therefore, new ways to efficiently capture more than 3 spectral channels of 3D time-varying spatial information, in a single or few sensors, are of high interest. Compressive spectral imaging (CSI) is an imaging framework that seeks to optimally capture spectral imagery (tens of spectral channels of 2D spatial information), using fewer measurements than that required by traditional sensing procedures which follows the Shannon-Nyquist sampling. Instead of capturing direct one-to-one representations of natural scenes, CSI systems acquire linear random projections of the scene and then solve an optimization algorithm to estimate the 3D spatio-spectral data cube by exploiting the theory of compressive sensing (CS). To date, the coding procedure in CSI has been realized through the use of ``block-unblock" coded apertures, commonly implemented as chrome-on-quartz photomasks. These apertures block or permit to pass the entire spectrum from the scene at given spatial locations, thus modulating the spatial characteristics of the scene. In the first part, this thesis aims to expand the framework of CSI by replacing the traditional block-unblock coded apertures by patterned optical filter arrays, referred as ``color" coded apertures. These apertures are formed by tiny pixelated optical filters, which in turn, allow the input image to be modulated not only spatially but spectrally as well, entailing more powerful coding strategies. The proposed colored coded apertures are either synthesized through linear combinations of low-pass, high-pass and band-pass filters, paired with binary pattern ensembles realized by a digital-micromirror-device (DMD), or experimentally realized through thin-film color-patterned filter arrays. The optical forward model of the proposed CSI architectures will be presented along with the design and proof-of-concept implementations, which achieve noticeable improvements in the quality of the reconstructions compared with conventional block-unblock coded aperture-based CSI architectures. On another front, due to the rich information contained in the infrared spectrum as well as the depth domain, this thesis aims to explore multimodal imaging by extending the range sensitivity of current CSI systems to a dual-band visible+near-infrared spectral domain, and also, it proposes, for the first time, a new imaging device that captures simultaneously 4D data cubes (2D spatial+1D spectral+depth imaging) with as few as a single snapshot. Due to the snapshot advantage of this camera, video sequences are possible, thus enabling the joint capture of 5D imagery. It aims to create super-human sensing that will enable the perception of our world in new and exciting ways. With this, we intend to advance in the state of the art in compressive sensing systems to extract depth while accurately capturing spatial and spectral material properties. The applications of such a sensor are self-evident in fields such as computer/robotic vision because they would allow an artificial intelligence to make informed decisions about not only the location of objects within a scene but also their material properties.

An MRI-Guided Telesurgery System Using a Fabry-Perot Interferometry Force Sensor and a Pneumatic Haptic Device.

PubMed

Su, Hao; Shang, Weijian; Li, Gang; Patel, Niravkumar; Fischer, Gregory S

2017-08-01

This paper presents a surgical master-slave teleoperation system for percutaneous interventional procedures under continuous magnetic resonance imaging (MRI) guidance. The slave robot consists of a piezoelectrically actuated 6-degree-of-freedom (DOF) robot for needle placement with an integrated fiber optic force sensor (1-DOF axial force measurement) using the Fabry-Perot interferometry (FPI) sensing principle; it is configured to operate inside the bore of the MRI scanner during imaging. By leveraging the advantages of pneumatic and piezoelectric actuation in force and position control respectively, we have designed a pneumatically actuated master robot (haptic device) with strain gauge based force sensing that is configured to operate the slave from within the scanner room during imaging. The slave robot follows the insertion motion of the haptic device while the haptic device displays the needle insertion force as measured by the FPI sensor. Image interference evaluation demonstrates that the telesurgery system presents a signal to noise ratio reduction of less than 17% and less than 1% geometric distortion during simultaneous robot motion and imaging. Teleoperated needle insertion and rotation experiments were performed to reach 10 targets in a soft tissue-mimicking phantom with 0.70 ± 0.35 mm Cartesian space error.

Singular structure of Mueller matrices images of biological crystal networks for diagnostic human tissues pathological changes

NASA Astrophysics Data System (ADS)

Sakhnovskiy, M. Y.; Ushenko, V. A.

2013-09-01

The process of converting of laser radiation by optically anisotropic crystals of biological networks are singular in the sense of total (simultaneous) of mechanisms of orientation and phase (birefringence) anisotropy the formation of polarization-inhomogeneous field of scattered radiation. This work is aimed at developing a method of polarization selection mechanisms of blood plasma polycrystalline networks anisotropy. The relationship between statistics, correlation and fractal parameters of polarization-inhomogeneous images of blood plasma and by linear dichroism and linear birefringence of polycrystalline networks albumin and globulin was found. The criteria of differentiation and diagnostic images of polarization-inhomogeneous plasma samples of the control group (donor) and a group of patients with malignant changes of breast tissue was identified.

Real time thermal imaging for analysis and control of crystal growth by the Czochralski technique

NASA Technical Reports Server (NTRS)

Wargo, M. J.; Witt, A. F.

1992-01-01

A real time thermal imaging system with temperature resolution better than +/- 0.5 C and spatial resolution of better than 0.5 mm has been developed. It has been applied to the analysis of melt surface thermal field distributions in both Czochralski and liquid encapsulated Czochralski growth configurations. The sensor can provide single/multiple point thermal information; a multi-pixel averaging algorithm has been developed which permits localized, low noise sensing and display of optical intensity variations at any location in the hot zone as a function of time. Temperature distributions are measured by extraction of data along a user selectable linear pixel array and are simultaneously displayed, as a graphic overlay, on the thermal image.

Improved atmospheric effect elimination method for the roughness estimation of painted surfaces.

PubMed

Zhang, Ying; Xuan, Jiabin; Zhao, Huijie; Song, Ping; Zhang, Yi; Xu, Wujian

2018-03-01

We propose a method for eliminating the atmospheric effect in polarimetric imaging remote sensing by using polarimetric imagers to simultaneously detect ground targets and skylight, which does not need calibrated targets. In addition, calculation efficiencies are improved by the skylight division method without losing estimation accuracy. Outdoor experiments are performed to obtain the polarimetric bidirectional reflectance distribution functions of painted surfaces and skylight under different weather conditions. Finally, the roughness of the painted surfaces is estimated. We find that the estimation accuracy with the proposed method is 6% on cloudy weather, while it is 30.72% without atmospheric effect elimination.

Remote sensing of cloud droplet size distributions in DC3 with the UMBC-LACO Rainbow Polarimetric Imager (RPI)

NASA Astrophysics Data System (ADS)

Buczkowski, S.; Martins, J.; Fernandez-Borda, R.; Cieslak, D.; Hall, J.

2013-12-01

The UMBC Rainbow Polarimetric Imager is a small form factor VIS imaging polarimeter suitable for use on a number of platforms. An optical system based on a Phillips prism with three Bayer filter color detectors, each detecting a separate polarization state, allows simultaneous detection of polarization and spectral information. A Mueller matrix-like calibration scheme corrects for polarization artifacts in the optical train and allows retrieval of the polarization state of incoming light to better than 0.5%. Coupled with wide field of view optics (~90°), RPI can capture images of cloudbows over a wide range of aircraft headings and solar zenith angles for retrieval of cloud droplet size distribution (DSD) parameters. In May-June 2012, RPI was flown in a nadir port on the NASA DC-8 during the DC3 field campaign. We will show examples of cloudbow DSD parameter retrievals from the campaign to demonstrate the efficacy of such a system to terrestrial atmospheric remote sensing. RPI image from DC3 06/15/2012 flight. Left panel is raw image from the RPI 90° camera. Middle panel is Stokes 'q' parameter retrieved from full three camera dataset. Right panel is a horizontal cut in 'q' through the glory. Both middle and right panels clearly show cloudbow features which can be fit to infer cloud DSD parameters.

Surface spectral emissivity derived from MODIS data

NASA Astrophysics Data System (ADS)

Chen, Yan; Sun-Mack, Sunny; Minnis, Patrick; Smith, William L.; Young, David F.

2003-04-01

Surface emissivity is essential for many remote sensing applications including the retrieval of the surface skin temperature from satellite-based infrared measurements, determining thresholds for cloud detection and for estimating the emission of longwave radiation from the surface, an important component of the energy budget of the surface-atmosphere interface. In this paper, data from the Terra MODIS (MODerate-resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 10.8, 12.0 micron are used to simultaneously derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of the clear-sky temperatures that are determined by the CERES (Clouds and Earth's Radiant Energy System) scene classification in each channel during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7 micron data. A set of simultaneous equations is then solved to derive the emissivities. Global results are derived from MODIS. Numerical weather analyses are used to provide soundings for correcting the observed radiances for atmospheric absorption. These results are verified and will be available for remote sensing applications.

Non-destructive phase contrast hard x-ray imaging to reveal the three-dimensional microstructure of soft and hard tissues

NASA Astrophysics Data System (ADS)

Khimchenko, Anna; Schulz, Georg; Deyhle, Hans; Hieber, Simone E.; Hasan, Samiul; Bikis, Christos; Schulz, Joachim; Costeur, Loïc.; Müller, Bert

2016-04-01

X-ray imaging in the absorption contrast mode is an established method of visualising calcified tissues such as bone and teeth. Physically soft tissues such as brain or muscle are often imaged using magnetic resonance imaging (MRI). However, the spatial resolution of MRI is insufficient for identifying individual biological cells within three-dimensional tissue. X-ray grating interferometry (XGI) has advantages for the investigation of soft tissues or the simultaneous three-dimensional visualisation of soft and hard tissues. Since laboratory microtomography (μCT) systems have better accessibility than tomography set-ups at synchrotron radiation facilities, a great deal of effort has been invested in optimising XGI set-ups for conventional μCT systems. In this conference proceeding, we present how a two-grating interferometer is incorporated into a commercially available nanotom m (GE Sensing and Inspection Technologies GmbH) μCT system to extend its capabilities toward phase contrast. We intend to demonstrate superior contrast in spiders (Hogna radiata (Fam. Lycosidae) and Xysticus erraticus (Fam. Thomisidae)), as well as the simultaneous visualisation of hard and soft tissues. XGI is an imaging modality that provides quantitative data, and visualisation is an important part of biomimetics; consequently, hard X-ray imaging provides a sound basis for bioinspiration, bioreplication and biomimetics and allows for the quantitative comparison of biofabricated products with their natural counterparts.

Smartphone-based simultaneous pH and nitrite colorimetric determination for paper microfluidic devices.

PubMed

Lopez-Ruiz, Nuria; Curto, Vincenzo F; Erenas, Miguel M; Benito-Lopez, Fernando; Diamond, Dermot; Palma, Alberto J; Capitan-Vallvey, Luis F

2014-10-07

In this work, an Android application for measurement of nitrite concentration and pH determination in combination with a low-cost paper-based microfluidic device is presented. The application uses seven sensing areas, containing the corresponding immobilized reagents, to produce selective color changes when a sample solution is placed in the sampling area. Under controlled conditions of light, using the flash of the smartphone as a light source, the image captured with the built-in camera is processed using a customized algorithm for multidetection of the colored sensing areas. The developed image-processing allows reducing the influence of the light source and the positioning of the microfluidic device in the picture. Then, the H (hue) and S (saturation) coordinates of the HSV color space are extracted and related to pH and nitrite concentration, respectively. A complete characterization of the sensing elements has been carried out as well as a full description of the image analysis for detection. The results show good use of a mobile phone as an analytical instrument. For the pH, the resolution obtained is 0.04 units of pH, 0.09 of accuracy, and a mean squared error of 0.167. With regard to nitrite, 0.51% at 4.0 mg L(-1) of resolution and 0.52 mg L(-1) as the limit of detection was achieved.

Secure and Energy-Efficient Data Transmission System Based on Chaotic Compressive Sensing in Body-to-Body Networks.

PubMed

Peng, Haipeng; Tian, Ye; Kurths, Jurgen; Li, Lixiang; Yang, Yixian; Wang, Daoshun

2017-06-01

Applications of wireless body area networks (WBANs) are extended from remote health care to military, sports, disaster relief, etc. With the network scale expanding, nodes increasing, and links complicated, a WBAN evolves to a body-to-body network. Along with the development, energy saving and data security problems are highlighted. In this paper, chaotic compressive sensing (CCS) is proposed to solve these two crucial problems, simultaneously. Compared with the traditional compressive sensing, CCS can save vast storage space by only storing the matrix generation parameters. Additionally, the sensitivity of chaos can improve the security of data transmission. Aimed at image transmission, modified CCS is proposed, which uses two encryption mechanisms, confusion and mask, and performs a much better encryption quality. Simulation is conducted to verify the feasibility and effectiveness of the proposed methods. The results show that the energy efficiency and security are strongly improved, while the storage space is saved. And the secret key is extremely sensitive, [Formula: see text] perturbation of the secret key could lead to a total different decoding, the relative error is larger than 100%. Particularly for image encryption, the performance of the modified method is excellent. The adjacent pixel correlation is smaller than 0.04 in different directions including horizontal, vertical, and diagonal; the entropy of the cipher image with a 256-level gray value is larger than 7.98.

Electric fish as natural models for technical sensor systems

NASA Astrophysics Data System (ADS)

von der Emde, Gerhard; Bousack, Herbert; Huck, Christina; Mayekar, Kavita; Pabst, Michael; Zhang, Yi

2009-05-01

Instead of vision, many animals use alternative senses for object detection. Weakly electric fish employ "active electrolocation", during which they discharge an electric organ emitting electrical current pulses (electric organ discharges, EOD). Local EODs are sensed by electroreceptors in the fish's skin, which respond to changes of the signal caused by nearby objects. Fish can gain information about attributes of an object, such as size, shape, distance, and complex impedance. When close to the fish, each object projects an 'electric image' onto the fish's skin. In order to get information about an object, the fish has to analyze the object's electric image by sampling its voltage distribution with the electroreceptors. We now know a great deal about the mechanisms the fish use to gain information about objects in their environment. Inspired by the remarkable capabilities of weakly electric fish in detecting and recognizing objects with their electric sense, we are designing technical sensor systems that can solve similar sensing problems. We applied the principles of active electrolocation to devices that produce electrical current pulses in water and simultaneously sense local current densities. Depending on the specific task, sensors can be designed which detect an object, localize it in space, determine its distance, and measure certain object properties such as material properties, thickness, or material faults. We present first experiments and FEM simulations on the optimal sensor arrangement regarding the sensor requirements e. g. localization of objects or distance measurements. Different methods of the sensor read-out and signal processing are compared.

Chemically designed Pt/PPy nano-composite for effective LPG gas sensor.

PubMed

Gaikwad, Namrata; Bhanoth, Sreenu; More, Priyesh V; Jain, G H; Khanna, P K

2014-03-07

Simultaneous in situ reduction of hexachloroplatinic acid by the amine group in the pyrrole monomer and oxidation of pyrrole to form polypyrrole (PPy) was examined. The reactions were performed at various temperatures to understand the degree of reduction of platinum precursor as well as doping of polypyrrole with Pt(II) chloro-complex. Spectroscopic images revealed different morphologies for the Pt/PPy nano-composite prepared at various temperatures. The as-prepared Pt/PPy nano-composite samples were tested for their ability to sense liquefied petroleum gas (LPG) which resulted in excellent sensing at relatively low temperature. The porous nature and ohmic contact between the PPy and platinum nanoparticles makes the as-prepared Pt/PPy nano-composite highly useful for sensors as well as electronic applications.

A Fabry-Perot interferometric imaging spectrometer in LWIR

NASA Astrophysics Data System (ADS)

Zhang, Fang; Gao, Jiaobo; Wang, Nan; Wu, Jianghui; Meng, Hemin; Zhang, Lei; Gao, Shan

2017-02-01

With applications ranging from the desktop to remote sensing, the long wave infrared (LWIR) interferometric spectral imaging system is always with huge volume and large weight. In order to miniaturize and light the instrument, a new method of LWIR spectral imaging system based on a variable gap Fabry-Perot (FP) interferometer is researched. With the system working principle analyzed, theoretically, it is researched that how to make certain the primary parameter, such as, wedge angle of interferometric cavity, f-number of the imaging lens and the relationship between the wedge angle and the modulation of the interferogram. A prototype is developed and a good experimental result of a uniform radiation source, a monochromatic source, is obtained. The research shows that besides high throughput and high spectral resolution, the advantage of miniaturization is also simultaneously achieved in this method.

Multidimensional Compressed Sensing MRI Using Tensor Decomposition-Based Sparsifying Transform

PubMed Central

Yu, Yeyang; Jin, Jin; Liu, Feng; Crozier, Stuart

2014-01-01

Compressed Sensing (CS) has been applied in dynamic Magnetic Resonance Imaging (MRI) to accelerate the data acquisition without noticeably degrading the spatial-temporal resolution. A suitable sparsity basis is one of the key components to successful CS applications. Conventionally, a multidimensional dataset in dynamic MRI is treated as a series of two-dimensional matrices, and then various matrix/vector transforms are used to explore the image sparsity. Traditional methods typically sparsify the spatial and temporal information independently. In this work, we propose a novel concept of tensor sparsity for the application of CS in dynamic MRI, and present the Higher-order Singular Value Decomposition (HOSVD) as a practical example. Applications presented in the three- and four-dimensional MRI data demonstrate that HOSVD simultaneously exploited the correlations within spatial and temporal dimensions. Validations based on cardiac datasets indicate that the proposed method achieved comparable reconstruction accuracy with the low-rank matrix recovery methods and, outperformed the conventional sparse recovery methods. PMID:24901331

Conjugate Observations of Optical Aurora with POLAR Satellite and Ground Based Imagers in Antarctica

NASA Technical Reports Server (NTRS)

Mende, S. H.; Frey, H.; Vo, H.; Geller, S. P.; Doolittle, J. H.; Spann, J. F., Jr.

1998-01-01

Operation of the ultraviolet imager on the POLAR satellite permits the observation of Aurora Borealis in daylight during northern summer. With optical imagers in the Automatic Geophysical Observatories (AGO-s) large regions of the oval of Aurora Australis can be observed simultaneously during the southern winter polar night. This opportunity permits conducting a systematic study of the properties of auroras on opposite ends of the same field line. It is expected that simultaneously observed conjugate auroras occurring on closed field lines should be similar to each other in appearance because of the close connection between the two hemispheres through particle scattering and mirroring processes. On open or greatly distorted field lines there is no a priori expectation of similarity between conjugate auroras. To investigate the influence of different IMF conditions on auroral behavior we have examined conjugate data for periods of southward IMF. Sudden brightening and subsequent poleward expansions are observed to occur simultaneously in both hemispheres. The POLAR data show that sudden brightening are initiated at various local time regions. When the local time of this region is in the field of view of the AGO station network then corresponding brightening is also found to occur in the southern hemisphere. Large features such as substorm induced westward propagation and resulting auroral brightening seem to occur simultaneously on conjugate hemispheres. The widely different view scales make it difficult to make unique identification of individual auroral forms in the POLAR and in the ground based data but in a general sense the data is consistent with conjugate behavior.

University of Wisconsin Cirrus Remote Sensing Pilot Experiment

NASA Technical Reports Server (NTRS)

Ackerman, Steven A.; Eloranta, Ed W.; Grund, Chris J.; Knuteson, Robert O.; Revercomb, Henry E.; Smith, William L.; Wylie, Donald P.

1993-01-01

During the period of 26 October 1989 through 6 December 1989 a unique complement of measurements was made at the University of Wisconsin-Madison to study the radiative properties of cirrus clouds. Simultaneous observations were obtained from a scanning lidar, two interferometers, a high spectral resolution lidar, geostationary and polar orbiting satellites, radiosonde launches, and a whole-sky imager. This paper describes the experiment, the instruments deployed, and, as an example, the data collected during one day of the experiment.

Remote Sensing Soil Moisture Analysis by Unmanned Aerial Vehicles Digital Imaging

NASA Astrophysics Data System (ADS)

Yeh, C. Y.; Lin, H. R.; Chen, Y. L.; Huang, S. Y.; Wen, J. C.

2017-12-01

In recent years, remote sensing analysis has been able to apply to the research of climate change, environment monitoring, geology, hydro-meteorological, and so on. However, the traditional methods for analyzing wide ranges of surface soil moisture of spatial distribution surveys may require plenty resources besides the high cost. In the past, remote sensing analysis performed soil moisture estimates through shortwave, thermal infrared ray, or infrared satellite, which requires lots of resources, labor, and money. Therefore, the digital image color was used to establish the multiple linear regression model. Finally, we can find out the relationship between surface soil color and soil moisture. In this study, we use the Unmanned Aerial Vehicle (UAV) to take an aerial photo of the fallow farmland. Simultaneously, we take the surface soil sample from 0-5 cm of the surface. The soil will be baking by 110° C and 24 hr. And the software ImageJ 1.48 is applied for the analysis of the digital images and the hue analysis into Red, Green, and Blue (R, G, B) hue values. The correlation analysis is the result from the data obtained from the image hue and the surface soil moisture at each sampling point. After image and soil moisture analysis, we use the R, G, B and soil moisture to establish the multiple regression to estimate the spatial distributions of surface soil moisture. In the result, we compare the real soil moisture and the estimated soil moisture. The coefficient of determination (R2) can achieve 0.5-0.7. The uncertainties in the field test, such as the sun illumination, the sun exposure angle, even the shadow, will affect the result; therefore, R2 can achieve 0.5-0.7 reflects good effect for the in-suit test by using the digital image to estimate the soil moisture. Based on the outcomes of the research, using digital images from UAV to estimate the surface soil moisture is acceptable. However, further investigations need to be collected more than ten days (four times a day) data to verify the relation between the image hue and the soil moisture for reliable moisture estimated model. And it is better to use the digital single lens reflex camera to prevent the deformation of the image and to have a better auto exposure. Keywords: soil, moisture, remote sensing

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

Borot de Battisti, Maxence, E-mail: M.E.P.Borot@um

Purpose: The development of MR-guided high dose rate (HDR) brachytherapy is under investigation due to the excellent tumor and organs at risk visualization of MRI. However, MR-based localization of needles (including catheters or tubes) has inherently a low update rate and the required image interpretation can be hampered by signal voids arising from blood vessels or calcifications limiting the precision of the needle guidance and reconstruction. In this paper, a new needle tracking prototype is investigated using fiber Bragg gratings (FBG)-based sensing: this prototype involves a MR-compatible stylet composed of three optic fibers with nine sets of embedded FBG sensorsmore » each. This stylet can be inserted into brachytherapy needles and allows a fast measurement of the needle deflection. This study aims to assess the potential of FBG-based sensing for real-time needle (including catheter or tube) tracking during MR-guided intervention. Methods: First, the MR compatibility of FBG-based sensing and its accuracy was evaluated. Different known needle deflections were measured using FBG-based sensing during simultaneous MR-imaging. Then, a needle tracking procedure using FBG-based sensing was proposed. This procedure involved a MR-based calibration of the FBG-based system performed prior to the interventional procedure. The needle tracking system was assessed in an experiment with a moving phantom during MR imaging. The FBG-based system was quantified by comparing the gold-standard shapes, the shape manually segmented on MRI and the FBG-based measurements. Results: The evaluation of the MR compatibility of FBG-based sensing and its accuracy shows that the needle deflection could be measured with an accuracy of 0.27 mm on average. Besides, the FBG-based measurements were comparable to the uncertainty of MR-based measurements estimated at half the voxel size in the MR image. Finally, the mean(standard deviation) Euclidean distance between MR- and FBG-based needle position measurements was equal to 0.79 mm(0.37 mm). The update rate and latency of the FBG-based needle position measurement were 100 and 300 ms, respectively. Conclusions: The FBG-based needle tracking procedure proposed in this paper is able to determine the position of the complete needle, under MR-imaging, with better accuracy and precision, higher update rate, and lower latency compared to current MR-based needle localization methods. This system would be eligible for MR-guided brachytherapy, in particular, for an improved needle guidance and reconstruction.« less

Evaluation of a multiple spin- and gradient-echo (SAGE) EPI acquisition with SENSE acceleration: applications for perfusion imaging in and outside the brain.

PubMed

Skinner, Jack T; Robison, Ryan K; Elder, Christopher P; Newton, Allen T; Damon, Bruce M; Quarles, C Chad

2014-12-01

Perfusion-based changes in MR signal intensity can occur in response to the introduction of exogenous contrast agents and endogenous tissue properties (e.g. blood oxygenation). MR measurements aimed at capturing these changes often implement single-shot echo planar imaging (ssEPI). In recent years ssEPI readouts have been combined with parallel imaging (PI) to allow fast dynamic multi-slice imaging as well as the incorporation of multiple echoes. A multiple spin- and gradient-echo (SAGE) EPI acquisition has recently been developed to allow measurement of transverse relaxation rate (R2 and R2(*)) changes in dynamic susceptibility contrast (DSC)-MRI experiments in the brain. With SAGE EPI, the use of PI can influence image quality, temporal resolution, and achievable echo times. The effect of PI on dynamic SAGE measurements, however, has not been evaluated. In this work, a SAGE EPI acquisition utilizing SENSE PI and partial Fourier (PF) acceleration was developed and evaluated. Voxel-wise measures of R2 and R2(*) in healthy brain were compared using SAGE EPI and conventional non-EPI multiple echo acquisitions with varying SENSE and PF acceleration. A conservative SENSE factor of 2 with PF factor of 0.73 was found to provide accurate measures of R2 and R2(*) in white (WM) (rR2=[0.55-0.79], rR2*=[0.47-0.71]) and gray (GM) matter (rR2=[0.26-0.59], rR2*=[0.39-0.74]) across subjects. The combined use of SENSE and PF allowed the first dynamic SAGE EPI measurements in muscle, with a SENSE factor of 3 and PF factor of 0.6 providing reliable relaxation rate estimates when compared to multi-echo methods. Application of the optimized SAGE protocol in DSC-MRI of high-grade glioma patients provided T1 leakage-corrected estimates of CBV and CBF as well as mean vessel diameter (mVD) and simultaneous measures of DCE-MRI parameters K(trans) and ve. Likewise, application of SAGE in a muscle reperfusion model allowed dynamic measures of R2', a parameter that has been shown to correlate with muscle oxy-hemoglobin saturation. Copyright © 2014 Elsevier Inc. All rights reserved.

Remote sensing of multiple vital signs using a CMOS camera-equipped infrared thermography system and its clinical application in rapidly screening patients with suspected infectious diseases.

PubMed

Sun, Guanghao; Nakayama, Yosuke; Dagdanpurev, Sumiyakhand; Abe, Shigeto; Nishimura, Hidekazu; Kirimoto, Tetsuo; Matsui, Takemi

2017-02-01

Infrared thermography (IRT) is used to screen febrile passengers at international airports, but it suffers from low sensitivity. This study explored the application of a combined visible and thermal image processing approach that uses a CMOS camera equipped with IRT to remotely sense multiple vital signs and screen patients with suspected infectious diseases. An IRT system that produced visible and thermal images was used for image acquisition. The subjects' respiration rates were measured by monitoring temperature changes around the nasal areas on thermal images; facial skin temperatures were measured simultaneously. Facial blood circulation causes tiny color changes in visible facial images that enable the determination of the heart rate. A logistic regression discriminant function predicted the likelihood of infection within 10s, based on the measured vital signs. Sixteen patients with an influenza-like illness and 22 control subjects participated in a clinical test at a clinic in Fukushima, Japan. The vital-sign-based IRT screening system had a sensitivity of 87.5% and a negative predictive value of 91.7%; these values are higher than those of conventional fever-based screening approaches. Multiple vital-sign-based screening efficiently detected patients with suspected infectious diseases. It offers a promising alternative to conventional fever-based screening. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Feature extraction from multiple data sources using genetic programming

NASA Astrophysics Data System (ADS)

Szymanski, John J.; Brumby, Steven P.; Pope, Paul A.; Eads, Damian R.; Esch-Mosher, Diana M.; Galassi, Mark C.; Harvey, Neal R.; McCulloch, Hersey D.; Perkins, Simon J.; Porter, Reid B.; Theiler, James P.; Young, Aaron C.; Bloch, Jeffrey J.; David, Nancy A.

2002-08-01

Feature extraction from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. We use the GENetic Imagery Exploitation (GENIE) software for this purpose, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land cover features including towns, wildfire burnscars, and forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.

Compressed single pixel imaging in the spatial frequency domain

PubMed Central

Torabzadeh, Mohammad; Park, Il-Yong; Bartels, Randy A.; Durkin, Anthony J.; Tromberg, Bruce J.

2017-01-01

Abstract. We have developed compressed sensing single pixel spatial frequency domain imaging (cs-SFDI) to characterize tissue optical properties over a wide field of view (35  mm×35  mm) using multiple near-infrared (NIR) wavelengths simultaneously. Our approach takes advantage of the relatively sparse spatial content required for mapping tissue optical properties at length scales comparable to the transport scattering length in tissue (ltr∼1  mm) and the high bandwidth available for spectral encoding using a single-element detector. cs-SFDI recovered absorption (μa) and reduced scattering (μs′) coefficients of a tissue phantom at three NIR wavelengths (660, 850, and 940 nm) within 7.6% and 4.3% of absolute values determined using camera-based SFDI, respectively. These results suggest that cs-SFDI can be developed as a multi- and hyperspectral imaging modality for quantitative, dynamic imaging of tissue optical and physiological properties. PMID:28300272

A compact LWIR imaging spectrometer with a variable gap Fabry-Perot interferometer

NASA Astrophysics Data System (ADS)

Zhang, Fang; Gao, Jiaobo; Wang, Nan; Zhao, Yujie; Zhang, Lei; Gao, Shan

2017-02-01

Fourier transform spectroscopy is a widely employed method for obtaining spectra, with applications ranging from the desktop to remote sensing. The long wave infrared (LWIR) interferometric spectral imaging system is always with huge volume and large weight. In order to miniaturize and light the instrument, a new method of LWIR spectral imaging system based on a variable gap Fabry-Perot (FP) interferometer is researched. With the system working principle analyzed, theoretically, it is researched that how to make certain the primary parameter, such as, the reflectivity of the two interferometric cavity surfaces, field of view (FOV) and f-number of the imaging lens. A prototype is developed and a good experimental result of CO2 laser is obtained. The research shows that besides high throughput and high spectral resolution, the advantage of miniaturization is also simultaneously achieved in this method.

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

Szymanski, J. J.; Brumby, Steven P.; Pope, P. A.

Feature extration from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. The tool used is the GENetic Imagery Exploitation (GENIE) software, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniquesmore » to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land-cover features including towns, grasslands, wild fire burn scars, and several types of forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.« less

Downscaling of Aircraft-, Landsat-, and MODIS-based Land Surface Temperature Images with Support Vector Machines

NASA Astrophysics Data System (ADS)

Ha, W.; Gowda, P. H.; Oommen, T.; Howell, T. A.; Hernandez, J. E.

2010-12-01

High spatial resolution Land Surface Temperature (LST) images are required to estimate evapotranspiration (ET) at a field scale for irrigation scheduling purposes. Satellite sensors such as Landsat 5 Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS) can offer images at several spectral bandwidths including visible, near-infrared (NIR), shortwave-infrared, and thermal-infrared (TIR). The TIR images usually have coarser spatial resolutions than those from non-thermal infrared bands. Due to this technical constraint of the satellite sensors on these platforms, image downscaling has been proposed in the field of ET remote sensing. This paper explores the potential of the Support Vector Machines (SVM) to perform downscaling of LST images derived from aircraft (4 m spatial resolution), TM (120 m), and MODIS (1000 m) using normalized difference vegetation index images derived from simultaneously acquired high resolution visible and NIR data (1 m for aircraft, 30 m for TM, and 250 m for MODIS). The SVM is a new generation machine learning algorithm that has found a wide application in the field of pattern recognition and time series analysis. The SVM would be ideally suited for downscaling problems due to its generalization ability in capturing non-linear regression relationship between the predictand and the multiple predictors. Remote sensing data acquired over the Texas High Plains during the 2008 summer growing season will be used in this study. Accuracy assessment of the downscaled 1, 30, and 250 m LST images will be made by comparing them with LST data measured with infrared thermometers at a small spatial scale, upscaled 30 m aircraft-based LST images, and upscaled 250 m TM-based LST images, respectively.

DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction.

PubMed

Yang, Guang; Yu, Simiao; Dong, Hao; Slabaugh, Greg; Dragotti, Pier Luigi; Ye, Xujiong; Liu, Fangde; Arridge, Simon; Keegan, Jennifer; Guo, Yike; Firmin, David; Keegan, Jennifer; Slabaugh, Greg; Arridge, Simon; Ye, Xujiong; Guo, Yike; Yu, Simiao; Liu, Fangde; Firmin, David; Dragotti, Pier Luigi; Yang, Guang; Dong, Hao

2018-06-01

Compressed sensing magnetic resonance imaging (CS-MRI) enables fast acquisition, which is highly desirable for numerous clinical applications. This can not only reduce the scanning cost and ease patient burden, but also potentially reduce motion artefacts and the effect of contrast washout, thus yielding better image quality. Different from parallel imaging-based fast MRI, which utilizes multiple coils to simultaneously receive MR signals, CS-MRI breaks the Nyquist-Shannon sampling barrier to reconstruct MRI images with much less required raw data. This paper provides a deep learning-based strategy for reconstruction of CS-MRI, and bridges a substantial gap between conventional non-learning methods working only on data from a single image, and prior knowledge from large training data sets. In particular, a novel conditional Generative Adversarial Networks-based model (DAGAN)-based model is proposed to reconstruct CS-MRI. In our DAGAN architecture, we have designed a refinement learning method to stabilize our U-Net based generator, which provides an end-to-end network to reduce aliasing artefacts. To better preserve texture and edges in the reconstruction, we have coupled the adversarial loss with an innovative content loss. In addition, we incorporate frequency-domain information to enforce similarity in both the image and frequency domains. We have performed comprehensive comparison studies with both conventional CS-MRI reconstruction methods and newly investigated deep learning approaches. Compared with these methods, our DAGAN method provides superior reconstruction with preserved perceptual image details. Furthermore, each image is reconstructed in about 5 ms, which is suitable for real-time processing.

Investigating the relationship between tree heights derived from SIBBORK forest model and remote sensing measurements

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Feliciano, E. A.; Armstrong, A. H.; Sun, G.; Montesano, P.; Ranson, K.

2017-12-01

Tree heights are one of the most commonly used remote sensing parameters to measure biomass of a forest. In this project, we investigate the relationship between remotely sensed tree heights (e.g. G-LiHT lidar and commercially available high resolution satellite imagery, HRSI) and the SIBBORK modeled tree heights. G-LiHT is a portable, airborne imaging system that simultaneously maps the composition, structure, and function of terrestrial ecosystems using lidar, imaging spectroscopy and thermal mapping. Ground elevation and canopy height models were generated using the lidar data acquired in 2012. A digital surface model was also generated using the HRSI technique from the commercially available WorldView data in 2016. The HRSI derived height and biomass products are available at the plot (10x10m) level. For this study, we parameterized the SIBBORK individual-based gap model for Howland forest, Maine. The parameterization was calibrated using field data for the study site and results show that the simulated forest reproduces the structural complexity of Howland old growth forest, based on comparisons of key variables including, aboveground biomass, forest height and basal area. Furthermore carbon cycle and ecosystem observational capabilities will be enhanced over the next 6 years via the launch of two LiDAR (NASA's GEDI and ICESAT 2) and two SAR (NASA's ISRO NiSAR and ESA's Biomass) systems. Our aim is to present the comparison of canopy height models obtained with SIBBORK forest model and remote sensing techniques, highlighting the synergy between individual-based forest modeling and high-resolution remote sensing.

Unmanned Aerial Systems and Spectroscopy for Remote Sensing Applications in Archaeology

NASA Astrophysics Data System (ADS)

Themistocleous, K.; Agapiou, A.; Cuca, B.; Hadjimitsis, D. G.

2015-04-01

Remote sensing has open up new dimensions in archaeological research. Although there has been significant progress in increasing the resolution of space/aerial sensors and image processing, the detection of the crop (and soil marks) formations, which relate to buried archaeological remains, are difficult to detect since these marks may not be visible in the images if observed over different period or at different spatial/spectral resolution. In order to support the improvement of earth observation remote sensing technologies specifically targeting archaeological research, a better understanding of the crop/soil marks formation needs to be studied in detail. In this paper the contribution of both Unmanned Aerial Systems as well ground spectroradiometers is discussed in a variety of examples applied in the eastern Mediterranean region (Cyprus and Greece) as well in Central Europe (Hungary). In- situ spectroradiometric campaigns can be applied for the removal of atmospheric impact to simultaneous satellite overpass images. In addition, as shown in this paper, the systematic collection of ground truth data prior to the satellite/aerial acquisition can be used to detect the optimum temporal and spectral resolution for the detection of stress vegetation related to buried archaeological remains. Moreover, phenological studies of the crops from the area of interest can be simulated to the potential sensors based on their Relative Response Filters and therefore prepare better the satellite-aerial campaigns. Ground data and the use of Unmanned Aerial Systems (UAS) can provide an increased insight for studying the formation of crop and soil marks. New algorithms such as vegetation indices and linear orthogonal equations for the enhancement of crop marks can be developed based on the specific spectral characteristics of the area. As well, UAS can be used for remote sensing applications in order to document, survey and model cultural heritage and archaeological sites.

Technology study of quantum remote sensing imaging

NASA Astrophysics Data System (ADS)

Bi, Siwen; Lin, Xuling; Yang, Song; Wu, Zhiqiang

2016-02-01

According to remote sensing science and technology development and application requirements, quantum remote sensing is proposed. First on the background of quantum remote sensing, quantum remote sensing theory, information mechanism, imaging experiments and prototype principle prototype research situation, related research at home and abroad are briefly introduced. Then we expounds compress operator of the quantum remote sensing radiation field and the basic principles of single-mode compression operator, quantum quantum light field of remote sensing image compression experiment preparation and optical imaging, the quantum remote sensing imaging principle prototype, Quantum remote sensing spaceborne active imaging technology is brought forward, mainly including quantum remote sensing spaceborne active imaging system composition and working principle, preparation and injection compression light active imaging device and quantum noise amplification device. Finally, the summary of quantum remote sensing research in the past 15 years work and future development are introduced.

Focal-plane electric field sensing with pupil-plane holograms

NASA Astrophysics Data System (ADS)

Por, Emiel H.; Keller, Christoph U.

2016-07-01

The direct detection and spectral characterization of exoplanets requires a coronagraph to suppress the diffracted star light. Amplitude and phase aberrations in the optical train fill the dark zone of the coronagraph with quasi-static speckles that limit the achievable contrast. Focal-plane electric field sensing, such as phase diversity introduced by a deformable mirror (DM), is a powerful tool to minimize this residual star light. The residual electric field can be estimated by sequentially applying phase probes on the DM to inject star light with a well-known amplitude and phase into the dark zone and analyzing the resulting intensity images. The DM can then be used to add light with the same amplitude but opposite phase to destructively interfere with this residual star light. Using a static phase-only pupil-plane element we create holographic copies of the point spread function (PSF), each superimposed with a certain pupil-plane phase probe. We therefore obtain all intensity images simultaneously while still retaining a central, unaltered science PSF. The electric field sensing method only makes use of the holographic copies, allowing for correction of the residual electric field while retaining the central PSF for uninterrupted science data collection. In this paper we demonstrate the feasibility of this method with numerical simulations.

The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce

NASA Astrophysics Data System (ADS)

Chen, Xi; Zhou, Liqing

2015-12-01

With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.

A turn-on fluorescent probe for simultaneous sensing of cysteine/homocysteine and hydrogen sulfide and its bioimaging applications.

PubMed

Chen, Fengzao; Han, Deman; Gao, Yuan; Liu, Heng; Wang, Shengfu; Zhou, Fangyu; Li, Kaibin; Zhang, Siqi; Shao, Wujun; He, Yanling

2018-09-01

Hydrogen sulfide and biothiol molecules such as Cys, Hcy, and GSH play important roles in biological systems. Exploiting a probe to simultaneously detect and distinguish them is quite important. In this work, a versatile fluorescent probe that can simultaneously detect and discriminate Cys/Hcy and H 2 S is reported. The probe easily prepared by the Knoevenagel condensation of cyanoacetylindole with chlorinated phenyl-propenal possessed three potential sites that could react with biothiols and H 2 S. This probe also exhibited rapidity, high selectivity, and sensitivity for Cys/Hcy and H 2 S with distinct optical signal changes. The probe was able to display obvious fluorescence enhancement at 480 nm for Cys/Hcy and unique absorbance enhancement at 500 nm for H 2 S. We also demonstrated that the probe can be successfully applied to image Cys in MCF-7 cells suing a confocal fluorescence microscope. Copyright © 2018 Elsevier B.V. All rights reserved.

Exploring Models and Data for Remote Sensing Image Caption Generation

NASA Astrophysics Data System (ADS)

Lu, Xiaoqiang; Wang, Binqiang; Zheng, Xiangtao; Li, Xuelong

2018-04-01

Inspired by recent development of artificial satellite, remote sensing images have attracted extensive attention. Recently, noticeable progress has been made in scene classification and target detection.However, it is still not clear how to describe the remote sensing image content with accurate and concise sentences. In this paper, we investigate to describe the remote sensing images with accurate and flexible sentences. First, some annotated instructions are presented to better describe the remote sensing images considering the special characteristics of remote sensing images. Second, in order to exhaustively exploit the contents of remote sensing images, a large-scale aerial image data set is constructed for remote sensing image caption. Finally, a comprehensive review is presented on the proposed data set to fully advance the task of remote sensing caption. Extensive experiments on the proposed data set demonstrate that the content of the remote sensing image can be completely described by generating language descriptions. The data set is available at https://github.com/201528014227051/RSICD_optimal

Effect of Shot Noise on Simultaneous Sensing in Frequency Division Multiplexed Diffuse Optical Tomographic Imaging Process.

PubMed

Jang, Hansol; Lim, Gukbin; Hong, Keum-Shik; Cho, Jaedu; Gulsen, Gultekin; Kim, Chang-Seok

2017-11-28

Diffuse optical tomography (DOT) has been studied for use in the detection of breast cancer, cerebral oxygenation, and cognitive brain signals. As optical imaging studies have increased significantly, acquiring imaging data in real time has become increasingly important. We have developed frequency-division multiplexing (FDM) DOT systems to analyze their performance with respect to acquisition time and imaging quality, in comparison with the conventional time-division multiplexing (TDM) DOT. A large tomographic area of a cylindrical phantom 60 mm in diameter could be successfully reconstructed using both TDM DOT and FDM DOT systems. In our experiment with 6 source-detector (S-D) pairs, the TDM DOT and FDM DOT systems required 6.18 and 1 s, respectively, to obtain a single tomographic data set. While the absorption coefficient of the reconstruction image was underestimated in the case of the FDM DOT, we experimentally confirmed that the abnormal region can be clearly distinguished from the background phantom using both methods.

SPR-DNA array for detection of methicillin-resistant Staphylococcus aureus (MRSA) in combination with loop-mediated isothermal amplification.

PubMed

Nawattanapaiboon, Kawin; Kiatpathomchai, Wansika; Santanirand, Pitak; Vongsakulyanon, Apirom; Amarit, Ratthasart; Somboonkaew, Armote; Sutapun, Boonsong; Srikhirin, Toemsak

2015-12-15

In this study, we evaluated surface plasmon resonance imaging (SPR imaging) as a DNA biosensor for the detection of methicillin-resistant Staphylococcus aureus (MRSA) which is one of the most common causes of nosocomial infections. The DNA sample were collected from clinical specimens, including sputum and blood hemoculture were undergone LAMP amplification for 0.18 kbp and 0.23 kbp DNA fragments of femB and mecA genes, respectively. The self-assembled monolayer surface (SAMs) was used for immobilized streptavidin-biotinylated probes on the sensor surface for the detection of LAMP amplicons from MRSA. Both LAMP amplicons were simultaneously hybridized with ssDNA probes immobilized onto a bio-functionalized surface to detect specific targets in the multiplex DNA array platform. In addition, the sensor surface could be regenerated allowing at least five cycles of use with a shortened assay time. The detection limit of LAMP-SPR sensing was 10 copies/µl and LAMP-SPR sensing system showed a good selectivity toward the MRSA. Copyright © 2015 Elsevier B.V. All rights reserved.

Communication: Two-dimensional gas-phase coherent anti-Stokes Raman spectroscopy (2D-CARS): Simultaneous planar imaging and multiplex spectroscopy in a single laser shot

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

Bohlin, Alexis; Kliewer, Christopher J.

2013-01-01

Coherent anti-Stokes Raman spectroscopy (CARS) has been widely used as a powerful tool for chemical sensing, molecular dynamics measurements, and rovibrational spectroscopy since its development over 30 years ago, finding use in fields of study as diverse as combustion diagnostics, cell biology, plasma physics, and the standoff detection of explosives. The capability for acquiring resolved CARS spectra in multiple spatial dimensions within a single laser shot has been a long-standing goal for the study of dynamical processes, but has proven elusive because of both phase-matching and detection considerations. Here, by combining new phase matching and detection schemes with the highmore » efficiency of femtosecond excitation of Raman coherences, we introduce a technique for single-shot two-dimensional (2D) spatial measurements of gas phase CARS spectra. We demonstrate a spectrometer enabling both 2D plane imaging and spectroscopy simultaneously, and present the instantaneous measurement of 15, 000 spatially correlated rotational CARS spectra in N 2 and air over a 2D field of 40 mm 2.« less

A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping

PubMed Central

Kzar, Ahmed Asal; Mat Jafri, Mohd Zubir; Mutter, Kussay N.; Syahreza, Saumi

2015-01-01

Decreasing water pollution is a big problem in coastal waters. Coastal health of ecosystems can be affected by high concentrations of suspended sediment. In this work, a Modified Hopfield Neural Network Algorithm (MHNNA) was used with remote sensing imagery to classify the total suspended solids (TSS) concentrations in the waters of coastal Langkawi Island, Malaysia. The adopted remote sensing image is the Advanced Land Observation Satellite (ALOS) image acquired on 18 January 2010. Our modification allows the Hopfield neural network to convert and classify color satellite images. The samples were collected from the study area simultaneously with the acquiring of satellite imagery. The sample locations were determined using a handheld global positioning system (GPS). The TSS concentration measurements were conducted in a lab and used for validation (real data), classification, and accuracy assessments. Mapping was achieved by using the MHNNA to classify the concentrations according to their reflectance values in band 1, band 2, and band 3. The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. The first group was used as source samples for supervisor classification via the MHNNA. The second group was used to test the MHNNA efficiency. After mapping, the locations of the second group in the produced classes were detected. Next, the correlation coefficient (R) and root mean square error (RMSE) were calculated between the two groups, according to their corresponding locations in the classes. The MHNNA exhibited a higher R (0.977) and lower RMSE (2.887). In addition, we test the MHNNA with noise, where it proves its accuracy with noisy images over a range of noise levels. All results have been compared with a minimum distance classifier (Min-Dis). Therefore, TSS mapping of polluted water in the coastal Langkawi Island, Malaysia can be performed using the adopted MHNNA with remote sensing techniques (as based on ALOS images). PMID:26729148

Suggested hurricane operational scenario for GOES I-M

NASA Technical Reports Server (NTRS)

Menzel, W. P.; Merrill, R. T.; Shenk, W. E.

1987-01-01

Improvements in tropical cyclone forecasts require optimum use of remote sensing capabilities, because conventional data sources cannot provide the necessary spatial and temporal data density over tropical and subtropical oceanic regions. In 1989, the first of a series of geostationary weather satellites, GOES 1-M, will be launched with the capability for simultaneous imaging and sounding. Careful scheduling of the GOES 1-M will enable measurements of both the wind and mass fields over the entire tropical cyclone activity area. The document briefly describes the GOES 1-M imager and sounder, surveys the data needs for hurricane forecasting, discusses how geostationary satellite observations help to meet them, and proposes a GOES 1-M schedule of observations and hurricane relevant derived products.

GPU-accelerated compressed-sensing (CS) image reconstruction in chest digital tomosynthesis (CDT) using CUDA programming

NASA Astrophysics Data System (ADS)

Choi, Sunghoon; Lee, Haenghwa; Lee, Donghoon; Choi, Seungyeon; Shin, Jungwook; Jang, Woojin; Seo, Chang-Woo; Kim, Hee-Joung

2017-03-01

A compressed-sensing (CS) technique has been rapidly applied in medical imaging field for retrieving volumetric data from highly under-sampled projections. Among many variant forms, CS technique based on a total-variation (TV) regularization strategy shows fairly reasonable results in cone-beam geometry. In this study, we implemented the TV-based CS image reconstruction strategy in our prototype chest digital tomosynthesis (CDT) R/F system. Due to the iterative nature of time consuming processes in solving a cost function, we took advantage of parallel computing using graphics processing units (GPU) by the compute unified device architecture (CUDA) programming to accelerate our algorithm. In order to compare the algorithmic performance of our proposed CS algorithm, conventional filtered back-projection (FBP) and simultaneous algebraic reconstruction technique (SART) reconstruction schemes were also studied. The results indicated that the CS produced better contrast-to-noise ratios (CNRs) in the physical phantom images (Teflon region-of-interest) by factors of 3.91 and 1.93 than FBP and SART images, respectively. The resulted human chest phantom images including lung nodules with different diameters also showed better visual appearance in the CS images. Our proposed GPU-accelerated CS reconstruction scheme could produce volumetric data up to 80 times than CPU programming. Total elapsed time for producing 50 coronal planes with 1024×1024 image matrix using 41 projection views were 216.74 seconds for proposed CS algorithms on our GPU programming, which could match the clinically feasible time ( 3 min). Consequently, our results demonstrated that the proposed CS method showed a potential of additional dose reduction in digital tomosynthesis with reasonable image quality in a fast time.

Statistical framework for the utilization of simultaneous pupil plane and focal plane telemetry for exoplanet imaging. I. Accounting for aberrations in multiple planes.

PubMed

Frazin, Richard A

2016-04-01

A new generation of telescopes with mirror diameters of 20 m or more, called extremely large telescopes (ELTs), has the potential to provide unprecedented imaging and spectroscopy of exoplanetary systems, if the difficulties in achieving the extremely high dynamic range required to differentiate the planetary signal from the star can be overcome to a sufficient degree. Fully utilizing the potential of ELTs for exoplanet imaging will likely require simultaneous and self-consistent determination of both the planetary image and the unknown aberrations in multiple planes of the optical system, using statistical inference based on the wavefront sensor and science camera data streams. This approach promises to overcome the most important systematic errors inherent in the various schemes based on differential imaging, such as angular differential imaging and spectral differential imaging. This paper is the first in a series on this subject, in which a formalism is established for the exoplanet imaging problem, setting the stage for the statistical inference methods to follow in the future. Every effort has been made to be rigorous and complete, so that validity of approximations to be made later can be assessed. Here, the polarimetric image is expressed in terms of aberrations in the various planes of a polarizing telescope with an adaptive optics system. Further, it is shown that current methods that utilize focal plane sensing to correct the speckle field, e.g., electric field conjugation, rely on the tacit assumption that aberrations on multiple optical surfaces can be represented as aberration on a single optical surface, ultimately limiting their potential effectiveness for ground-based astronomy.

Surface imaging microscope

NASA Astrophysics Data System (ADS)

Rogala, Eric W.; Bankman, Isaac N.

2008-04-01

The three-dimensional shapes of microscopic objects are becoming increasingly important for battlespace CBRNE sensing. Potential applications of microscopic 3D shape observations include characterization of biological weapon particles and manufacturing of micromechanical components. Aerosol signatures of stand-off lidar systems, using elastic backscatter or polarization, are dictated by the aerosol particle shapes and sizes that must be well characterized in the lab. A low-cost, fast instrument for 3D surface shape microscopy will be a valuable point sensor for biological particle sensing applications. Both the cost and imaging durations of traditional techniques such as confocal microscopes, atomic force microscopes, and electron scanning microscopes are too high. We investigated the feasibility of a low-cost, fast interferometric technique for imaging the 3D surface shape of microscopic objects at frame rates limited only by the camera in the system. The system operates at two laser wavelengths producing two fringe images collected simultaneously by a digital camera, and a specialized algorithm we developed reconstructs the surface map of the microscopic object. The current implementation assembled to test the concept and develop the new 3D reconstruction algorithm has 0.25 micron resolution in the x and y directions, and about 0.1 micron accuracy in the z direction, as tested on a microscopic glass test object manufactured with etching techniques. We describe the interferometric instrument, present the reconstruction algorithm, and discuss further development.

Efficient single-pixel multispectral imaging via non-mechanical spatio-spectral modulation.

PubMed

Li, Ziwei; Suo, Jinli; Hu, Xuemei; Deng, Chao; Fan, Jingtao; Dai, Qionghai

2017-01-27

Combining spectral imaging with compressive sensing (CS) enables efficient data acquisition by fully utilizing the intrinsic redundancies in natural images. Current compressive multispectral imagers, which are mostly based on array sensors (e.g, CCD or CMOS), suffer from limited spectral range and relatively low photon efficiency. To address these issues, this paper reports a multispectral imaging scheme with a single-pixel detector. Inspired by the spatial resolution redundancy of current spatial light modulators (SLMs) relative to the target reconstruction, we design an all-optical spectral splitting device to spatially split the light emitted from the object into several counterparts with different spectrums. Separated spectral channels are spatially modulated simultaneously with individual codes by an SLM. This no-moving-part modulation ensures a stable and fast system, and the spatial multiplexing ensures an efficient acquisition. A proof-of-concept setup is built and validated for 8-channel multispectral imaging within 420~720 nm wavelength range on both macro and micro objects, showing a potential for efficient multispectral imager in macroscopic and biomedical applications.

Evaluation and comparison of the IRS-P6 and the landsat sensors

USGS Publications Warehouse

Chander, G.; Coan, M.J.; Scaramuzza, P.L.

2008-01-01

The Indian Remote Sensing Satellite (IRS-P6), also called ResourceSat-1, was launched in a polar sun-synchronous orbit on October 17, 2003. It carries three sensors: the highresolution Linear Imaging Self-Scanner (LISS-IV), the mediumresolution Linear Imaging Self-Scanner (LISS-III), and the Advanced Wide-Field Sensor (AWiFS). These three sensors provide images of different resolutions and coverage. To understand the absolute radiometric calibration accuracy of IRS-P6 AWiFS and LISS-III sensors, image pairs from these sensors were compared to images from the Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced TM Plus (ETM+) sensors. The approach involves calibration of surface observations based on image statistics from areas observed nearly simultaneously by the two sensors. This paper also evaluated the viability of data from these nextgeneration imagers for use in creating three National Land Cover Dataset (NLCD) products: land cover, percent tree canopy, and percent impervious surface. Individual products were consistent with previous studies but had slightly lower overall accuracies as compared to data from the Landsat sensors.

Atmospheric correction for remote sensing image based on multi-spectral information

NASA Astrophysics Data System (ADS)

Wang, Yu; He, Hongyan; Tan, Wei; Qi, Wenwen

2018-03-01

The light collected from remote sensors taken from space must transit through the Earth's atmosphere. All satellite images are affected at some level by lightwave scattering and absorption from aerosols, water vapor and particulates in the atmosphere. For generating high-quality scientific data, atmospheric correction is required to remove atmospheric effects and to convert digital number (DN) values to surface reflectance (SR). Every optical satellite in orbit observes the earth through the same atmosphere, but each satellite image is impacted differently because atmospheric conditions are constantly changing. A physics-based detailed radiative transfer model 6SV requires a lot of key ancillary information about the atmospheric conditions at the acquisition time. This paper investigates to achieve the simultaneous acquisition of atmospheric radiation parameters based on the multi-spectral information, in order to improve the estimates of surface reflectance through physics-based atmospheric correction. Ancillary information on the aerosol optical depth (AOD) and total water vapor (TWV) derived from the multi-spectral information based on specific spectral properties was used for the 6SV model. The experimentation was carried out on images of Sentinel-2, which carries a Multispectral Instrument (MSI), recording in 13 spectral bands, covering a wide range of wavelengths from 440 up to 2200 nm. The results suggest that per-pixel atmospheric correction through 6SV model, integrating AOD and TWV derived from multispectral information, is better suited for accurate analysis of satellite images and quantitative remote sensing application.

Performance assessment of a single-pixel compressive sensing imaging system

NASA Astrophysics Data System (ADS)

Du Bosq, Todd W.; Preece, Bradley L.

2016-05-01

Conventional electro-optical and infrared (EO/IR) systems capture an image by measuring the light incident at each of the millions of pixels in a focal plane array. Compressive sensing (CS) involves capturing a smaller number of unconventional measurements from the scene, and then using a companion process known as sparse reconstruction to recover the image as if a fully populated array that satisfies the Nyquist criteria was used. Therefore, CS operates under the assumption that signal acquisition and data compression can be accomplished simultaneously. CS has the potential to acquire an image with equivalent information content to a large format array while using smaller, cheaper, and lower bandwidth components. However, the benefits of CS do not come without compromise. The CS architecture chosen must effectively balance between physical considerations (SWaP-C), reconstruction accuracy, and reconstruction speed to meet operational requirements. To properly assess the value of such systems, it is necessary to fully characterize the image quality, including artifacts and sensitivity to noise. Imagery of the two-handheld object target set at range was collected using a passive SWIR single-pixel CS camera for various ranges, mirror resolution, and number of processed measurements. Human perception experiments were performed to determine the identification performance within the trade space. The performance of the nonlinear CS camera was modeled with the Night Vision Integrated Performance Model (NV-IPM) by mapping the nonlinear degradations to an equivalent linear shift invariant model. Finally, the limitations of CS modeling techniques will be discussed.

A Novel Unsupervised Segmentation Quality Evaluation Method for Remote Sensing Images

PubMed Central

Tang, Yunwei; Jing, Linhai; Ding, Haifeng

2017-01-01

The segmentation of a high spatial resolution remote sensing image is a critical step in geographic object-based image analysis (GEOBIA). Evaluating the performance of segmentation without ground truth data, i.e., unsupervised evaluation, is important for the comparison of segmentation algorithms and the automatic selection of optimal parameters. This unsupervised strategy currently faces several challenges in practice, such as difficulties in designing effective indicators and limitations of the spectral values in the feature representation. This study proposes a novel unsupervised evaluation method to quantitatively measure the quality of segmentation results to overcome these problems. In this method, multiple spectral and spatial features of images are first extracted simultaneously and then integrated into a feature set to improve the quality of the feature representation of ground objects. The indicators designed for spatial stratified heterogeneity and spatial autocorrelation are included to estimate the properties of the segments in this integrated feature set. These two indicators are then combined into a global assessment metric as the final quality score. The trade-offs of the combined indicators are accounted for using a strategy based on the Mahalanobis distance, which can be exhibited geometrically. The method is tested on two segmentation algorithms and three testing images. The proposed method is compared with two existing unsupervised methods and a supervised method to confirm its capabilities. Through comparison and visual analysis, the results verified the effectiveness of the proposed method and demonstrated the reliability and improvements of this method with respect to other methods. PMID:29064416

Design of a multispectral, wedge filter, remote-sensing instrument incorporating a multiport, thinned, CCD area array

NASA Astrophysics Data System (ADS)

Demro, James C.; Hartshorne, Richard; Woody, Loren M.; Levine, Peter A.; Tower, John R.

1995-06-01

The next generation Wedge Imaging Spectrometer (WIS) instruments currently in integration at Hughes SBRD incorporate advanced features to increase operation flexibility for remotely sensed hyperspectral imagery collection and use. These features include: a) multiple linear wedge filters to tailor the spectral bands to the scene phenomenology; b) simple, replaceable fore-optics to allow different spatial resolutions and coverages; c) data acquisition system (DAS) that collects the full data stream simultaneously from both WIS instruments (VNIR and SWIR/MWIR), stores the data in a RAID storage, and provides for down-loading of the data to MO disks; the WIS DAS also allows selection of the spectral band sets to be stored; d) high-performance VNIR camera subsystem based upon a 512 X 512 CCD area array and associated electronics.

Research on assessment and improvement method of remote sensing image reconstruction

NASA Astrophysics Data System (ADS)

Sun, Li; Hua, Nian; Yu, Yanbo; Zhao, Zhanping

2018-01-01

Remote sensing image quality assessment and improvement is an important part of image processing. Generally, the use of compressive sampling theory in remote sensing imaging system can compress images while sampling which can improve efficiency. A method of two-dimensional principal component analysis (2DPCA) is proposed to reconstruct the remote sensing image to improve the quality of the compressed image in this paper, which contain the useful information of image and can restrain the noise. Then, remote sensing image quality influence factors are analyzed, and the evaluation parameters for quantitative evaluation are introduced. On this basis, the quality of the reconstructed images is evaluated and the different factors influence on the reconstruction is analyzed, providing meaningful referential data for enhancing the quality of remote sensing images. The experiment results show that evaluation results fit human visual feature, and the method proposed have good application value in the field of remote sensing image processing.

A gold nanocluster-based fluorescent probe for simultaneous pH and temperature sensing and its application to cellular imaging and logic gates.

PubMed

Wu, Yun-Tse; Shanmugam, Chandirasekar; Tseng, Wei-Bin; Hiseh, Ming-Mu; Tseng, Wei-Lung

2016-06-07

Metal nanocluster-based nanomaterials for the simultaneous determination of temperature and pH variations in micro-environments are still a challenge. In this study, we develop a dual-emission fluorescent probe consisting of bovine serum albumin-stabilized gold nanoclusters (BSA-AuNCs) and fluorescein-5-isothiocyanate (FITC) as temperature- and pH-responsive fluorescence signals. Under single wavelength excitation the FITC/BSA-AuNCs exhibited well-separated dual emission bands at 525 and 670 nm. When FITC was used as a reference fluorophore, FITC/BSA-AuNCs showed a good linear response over the temperature range 1-71 °C and offered temperature-independent spectral shifts, temperature accuracy, activation energy, and reusability. The possible mechanism for high temperature-induced fluorescence quenching of FITC/BSA-AuNCs could be attributed to a weakening of the Au-S bond, thereby lowering the charge transfer from BSA to AuNCs. Additionally, the pH- and temperature-responsive properties of FITC/BSA-AuNCs allow simultaneous temperature sensing from 21 to 41 °C (at intervals of 5 °C) and pH from 6.0 to 8.0 (at intervals of 0.5 pH unit), facilitating the construction of two-input AND logic gates. Three-input AND logic gates were also designed using temperature, pH, and trypsin as inputs. The practicality of using FITC/BSA-AuNCs to determine the temperature and pH changes in HeLa cells is also validated.

Integrating remote sensing and terrain data in forest fire modeling

NASA Astrophysics Data System (ADS)

Medler, Michael Johns

Forest fire policies are changing. Managers now face conflicting imperatives to re-establish pre-suppression fire regimes, while simultaneously preventing resource destruction. They must, therefore, understand the spatial patterns of fires. Geographers can facilitate this understanding by developing new techniques for mapping fire behavior. This dissertation develops such techniques for mapping recent fires and using these maps to calibrate models of potential fire hazards. In so doing, it features techniques that strive to address the inherent complexity of modeling the combinations of variables found in most ecological systems. Image processing techniques were used to stratify the elements of terrain, slope, elevation, and aspect. These stratification images were used to assure sample placement considered the role of terrain in fire behavior. Examination of multiple stratification images indicated samples were placed representatively across a controlled range of scales. The incorporation of terrain data also improved preliminary fire hazard classification accuracy by 40%, compared with remotely sensed data alone. A Kauth-Thomas transformation (KT) of pre-fire and post-fire Thematic Mapper (TM) remotely sensed data produced brightness, greenness, and wetness images. Image subtraction indicated fire induced change in brightness, greenness, and wetness. Field data guided a fuzzy classification of these change images. Because fuzzy classification can characterize a continuum of a phenomena where discrete classification may produce artificial borders, fuzzy classification was found to offer a range of fire severity information unavailable with discrete classification. These mapped fire patterns were used to calibrate a model of fire hazards for the entire mountain range. Pre-fire TM, and a digital elevation model produced a set of co-registered images. Training statistics were developed from 30 polygons associated with the previously mapped fire severity. Fuzzy classifications of potential burn patterns were produced from these images. Observed field data values were displayed over the hazard imagery to indicate the effectiveness of the model. Areas that burned without suppression during maximum fire severity are predicted best. Areas with widely spaced trees and grassy understory appear to be misrepresented, perhaps as a consequence of inaccuracies in the initial fire mapping.

Prototype positron emission tomography insert with electro-optical signal transmission for simultaneous operation with MRI.

PubMed

Olcott, Peter; Kim, Ealgoo; Hong, Keyjo; Lee, Brian J; Grant, Alexander M; Chang, Chen-Ming; Glover, Gary; Levin, Craig S

2015-05-07

The simultaneous acquisition of PET and MRI data shows promise to provide powerful capabilities to study disease processes in human subjects, guide the development of novel treatments, and monitor therapy response and disease progression. A brain-size PET detector ring insert for an MRI system is being developed that, if successful, can be inserted into any existing MRI system to enable simultaneous PET and MRI images of the brain to be acquired without mutual interference. The PET insert uses electro-optical coupling to relay all the signals from the PET detectors out of the MRI system using analog modulated lasers coupled to fiber optics. Because the fibers use light instead of electrical signals, the PET detector can be electrically decoupled from the MRI making it partially transmissive to the RF field of the MRI. The SiPM devices and low power lasers were powered using non-magnetic MRI compatible batteries. Also, the number of laser-fiber channels in the system was reduced using techniques adapted from the field of compressed sensing. Using the fact that incoming PET data is sparse in time and space, electronic circuits implementing constant weight codes uniquely encode the detector signals in order to reduce the number of electro-optical readout channels by 8-fold. Two out of a total of sixteen electro-optical detector modules have been built and tested with the entire RF-shielded detector gantry for the PET ring insert. The two detectors have been tested outside and inside of a 3T MRI system to study mutual interference effects and simultaneous performance with MRI. Preliminary results show that the PET insert is feasible for high resolution simultaneous PET/MRI imaging for applications in the brain.

Prototype positron emission tomography insert with electro-optical signal transmission for simultaneous operation with MRI

NASA Astrophysics Data System (ADS)

Olcott, Peter; Kim, Ealgoo; Hong, Keyjo; Lee, Brian J.; Grant, Alexander M.; Chang, Chen-Ming; Glover, Gary; Levin, Craig S.

2015-05-01

The simultaneous acquisition of PET and MRI data shows promise to provide powerful capabilities to study disease processes in human subjects, guide the development of novel treatments, and monitor therapy response and disease progression. A brain-size PET detector ring insert for an MRI system is being developed that, if successful, can be inserted into any existing MRI system to enable simultaneous PET and MRI images of the brain to be acquired without mutual interference. The PET insert uses electro-optical coupling to relay all the signals from the PET detectors out of the MRI system using analog modulated lasers coupled to fiber optics. Because the fibers use light instead of electrical signals, the PET detector can be electrically decoupled from the MRI making it partially transmissive to the RF field of the MRI. The SiPM devices and low power lasers were powered using non-magnetic MRI compatible batteries. Also, the number of laser-fiber channels in the system was reduced using techniques adapted from the field of compressed sensing. Using the fact that incoming PET data is sparse in time and space, electronic circuits implementing constant weight codes uniquely encode the detector signals in order to reduce the number of electro-optical readout channels by 8-fold. Two out of a total of sixteen electro-optical detector modules have been built and tested with the entire RF-shielded detector gantry for the PET ring insert. The two detectors have been tested outside and inside of a 3T MRI system to study mutual interference effects and simultaneous performance with MRI. Preliminary results show that the PET insert is feasible for high resolution simultaneous PET/MRI imaging for applications in the brain.

Adaptive foveated single-pixel imaging with dynamic supersampling

PubMed Central

Phillips, David B.; Sun, Ming-Jie; Taylor, Jonathan M.; Edgar, Matthew P.; Barnett, Stephen M.; Gibson, Graham M.; Padgett, Miles J.

2017-01-01

In contrast to conventional multipixel cameras, single-pixel cameras capture images using a single detector that measures the correlations between the scene and a set of patterns. However, these systems typically exhibit low frame rates, because to fully sample a scene in this way requires at least the same number of correlation measurements as the number of pixels in the reconstructed image. To mitigate this, a range of compressive sensing techniques have been developed which use a priori knowledge to reconstruct images from an undersampled measurement set. Here, we take a different approach and adopt a strategy inspired by the foveated vision found in the animal kingdom—a framework that exploits the spatiotemporal redundancy of many dynamic scenes. In our system, a high-resolution foveal region tracks motion within the scene, yet unlike a simple zoom, every frame delivers new spatial information from across the entire field of view. This strategy rapidly records the detail of quickly changing features in the scene while simultaneously accumulating detail of more slowly evolving regions over several consecutive frames. This architecture provides video streams in which both the resolution and exposure time spatially vary and adapt dynamically in response to the evolution of the scene. The degree of local frame rate enhancement is scene-dependent, but here, we demonstrate a factor of 4, thereby helping to mitigate one of the main drawbacks of single-pixel imaging techniques. The methods described here complement existing compressive sensing approaches and may be applied to enhance computational imagers that rely on sequential correlation measurements. PMID:28439538

Calibration procedures for imaging spectrometers: improving data quality from satellite missions to UAV campaigns

NASA Astrophysics Data System (ADS)

Brachmann, Johannes F. S.; Baumgartner, Andreas; Lenhard, Karim

2016-10-01

The Calibration Home Base (CHB) at the Remote Sensing Technology Institute of the German Aerospace Center (DLR-IMF) is an optical laboratory designed for the calibration of imaging spectrometers for the VNIR/SWIR wavelength range. Radiometric, spectral and geometric characterization is realized in the CHB in a precise and highly automated fashion. This allows performing a wide range of time consuming measurements in an efficient way. The implementation of ISO 9001 standards ensures a traceable quality of results. DLR-IMF will support the calibration and characterization campaign of the future German spaceborne hyperspectral imager EnMAP. In the context of this activity, a procedure for the correction of imaging artifacts, such as due to stray light, is currently being developed by DLR-IMF. Goal is the correction of in-band stray light as well as ghost images down to a level of a few digital numbers in the whole wavelength range 420-2450 nm. DLR-IMF owns a Norsk Elektro Optikks HySpex airborne imaging spectrometer system that has been thoroughly characterized. This system will be used to test stray light calibration procedures for EnMAP. Hyperspectral snapshot sensors offer the possibility to simultaneously acquire hyperspectral data in two dimensions. Recently, these rather new spectrometers have arisen much interest in the remote sensing community. Different designs are currently used for local area observation such as by use of small unmanned aerial vehicles (sUAV). In this context the CHB's measurement capabilities are currently extended such that a standard measurement procedure for these new sensors will be implemented.

Satellite measurements of large-scale air pollution - Methods

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Ferrare, Richard A.; Fraser, Robert S.

1990-01-01

A technique for deriving large-scale pollution parameters from NIR and visible satellite remote-sensing images obtained over land or water is described and demonstrated on AVHRR images. The method is based on comparison of the upward radiances on clear and hazy days and permits simultaneous determination of aerosol optical thickness with error Delta tau(a) = 0.08-0.15, particle size with error + or - 100-200 nm, and single-scattering albedo with error + or - 0.03 (for albedos near 1), all assuming accurate and stable satellite calibration and stable surface reflectance between the clear and hazy days. In the analysis of AVHRR images of smoke from a forest fire, good agreement was obtained between satellite and ground-based (sun-photometer) measurements of aerosol optical thickness, but the satellite particle sizes were systematically greater than those measured from the ground. The AVHRR single-scattering albedo agreed well with a Landsat albedo for the same smoke.

Research on active imaging information transmission technology of satellite borne quantum remote sensing

NASA Astrophysics Data System (ADS)

Bi, Siwen; Zhen, Ming; Yang, Song; Lin, Xuling; Wu, Zhiqiang

2017-08-01

According to the development and application needs of Remote Sensing Science and technology, Prof. Siwen Bi proposed quantum remote sensing. Firstly, the paper gives a brief introduction of the background of quantum remote sensing, the research status and related researches at home and abroad on the theory, information mechanism and imaging experiments of quantum remote sensing and the production of principle prototype.Then, the quantization of pure remote sensing radiation field, the state function and squeezing effect of quantum remote sensing radiation field are emphasized. It also describes the squeezing optical operator of quantum light field in active imaging information transmission experiment and imaging experiments, achieving 2-3 times higher resolution than that of coherent light detection imaging and completing the production of quantum remote sensing imaging prototype. The application of quantum remote sensing technology can significantly improve both the signal-to-noise ratio of information transmission imaging and the spatial resolution of quantum remote sensing .On the above basis, Prof.Bi proposed the technical solution of active imaging information transmission technology of satellite borne quantum remote sensing, launched researches on its system composition and operation principle and on quantum noiseless amplifying devices, providing solutions and technical basis for implementing active imaging information technology of satellite borne Quantum Remote Sensing.

Research on remote sensing image pixel attribute data acquisition method in AutoCAD

NASA Astrophysics Data System (ADS)

Liu, Xiaoyang; Sun, Guangtong; Liu, Jun; Liu, Hui

2013-07-01

The remote sensing image has been widely used in AutoCAD, but AutoCAD lack of the function of remote sensing image processing. In the paper, ObjectARX was used for the secondary development tool, combined with the Image Engine SDK to realize remote sensing image pixel attribute data acquisition in AutoCAD, which provides critical technical support for AutoCAD environment remote sensing image processing algorithms.

A Review of Hybrid Fiber-Optic Distributed Simultaneous Vibration and Temperature Sensing Technology and Its Geophysical Applications

PubMed Central

2017-01-01

Distributed sensing systems can transform an optical fiber cable into an array of sensors, allowing users to detect and monitor multiple physical parameters such as temperature, vibration and strain with fine spatial and temporal resolution over a long distance. Fiber-optic distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) systems have been developed for various applications with varied spatial resolution, and spectral and sensing range. Rayleigh scattering-based phase optical time domain reflectometry (OTDR) for vibration and Raman/Brillouin scattering-based OTDR for temperature and strain measurements have been developed over the past two decades. The key challenge has been to find a methodology that would enable the physical parameters to be determined at any point along the sensing fiber with high sensitivity and spatial resolution, yet within acceptable frequency range for dynamic vibration, and temperature detection. There are many applications, especially in geophysical and mining engineering where simultaneous measurements of vibration and temperature are essential. In this article, recent developments of different hybrid systems for simultaneous vibration, temperature and strain measurements are analyzed based on their operation principles and performance. Then, challenges and limitations of the systems are highlighted for geophysical applications. PMID:29104259

A Review of Hybrid Fiber-Optic Distributed Simultaneous Vibration and Temperature Sensing Technology and Its Geophysical Applications.

PubMed

Miah, Khalid; Potter, David K

2017-11-01

Distributed sensing systems can transform an optical fiber cable into an array of sensors, allowing users to detect and monitor multiple physical parameters such as temperature, vibration and strain with fine spatial and temporal resolution over a long distance. Fiber-optic distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) systems have been developed for various applications with varied spatial resolution, and spectral and sensing range. Rayleigh scattering-based phase optical time domain reflectometry (OTDR) for vibration and Raman/Brillouin scattering-based OTDR for temperature and strain measurements have been developed over the past two decades. The key challenge has been to find a methodology that would enable the physical parameters to be determined at any point along the sensing fiber with high sensitivity and spatial resolution, yet within acceptable frequency range for dynamic vibration, and temperature detection. There are many applications, especially in geophysical and mining engineering where simultaneous measurements of vibration and temperature are essential. In this article, recent developments of different hybrid systems for simultaneous vibration, temperature and strain measurements are analyzed based on their operation principles and performance. Then, challenges and limitations of the systems are highlighted for geophysical applications.

Ultrasound assisted synthesis of PANI/ZnMoO4 nanocomposite for simultaneous improvement in anticorrosion, physico-chemical properties and its application in gas sensing.

PubMed

Bhanvase, B A; Darda, N S; Veerkar, N C; Shende, A S; Satpute, S R; Sonawane, S H

2015-05-01

Ultrasound assisted in-situ semi-batch emulsion polymerization has been used for the preparation of polyaniline (PANI) and PANI/ZnMoO4 nanocomposite with different loading of ZnMoO4 (ZM) nanoparticles. ZM nanoparticles were functionalized using Myristic acid (MA) for better compatibility with PANI. The cavitational effects induced due to ultrasonic irradiations have been shown significant enhancement in the dispersion of functionalized ZM nanoparticles into the PANI during ultrasound assisted in-situ emulsion polymerization process. TEM images of PANI/ZM nanocomposite particles give the direct evidence of fine dispersion and encapsulation of MA treated ZM nanoparticles in PANI matrix. The presence of ZM nanoparticles in PANI/ZM nanocomposite shows significant improvement in the mechanical (cross-cut adhesion), thermal, anticorrosion and sensing properties of PANI/ZM nanocomposite/alkyd coatings over PANI/alkyd and neat alkyd resin coating. Fine and uniform dispersion of ZM nanoparticles in PANI matrix using this novel synthesis method (PANI (p-type)/ZM (n-type) hetero-junction) improves LPG sensing ability and minimizes response time to sense LPG significantly compared with neat PANI. Copyright © 2014 Elsevier B.V. All rights reserved.

Short-Term Neural Adaptation to Simultaneous Bifocal Images

PubMed Central

Radhakrishnan, Aiswaryah; Dorronsoro, Carlos; Sawides, Lucie; Marcos, Susana

2014-01-01

Simultaneous vision is an increasingly used solution for the correction of presbyopia (the age-related loss of ability to focus near images). Simultaneous Vision corrections, normally delivered in the form of contact or intraocular lenses, project on the patient's retina a focused image for near vision superimposed with a degraded image for far vision, or a focused image for far vision superimposed with the defocused image of the near scene. It is expected that patients with these corrections are able to adapt to the complex Simultaneous Vision retinal images, although the mechanisms or the extent to which this happens is not known. We studied the neural adaptation to simultaneous vision by studying changes in the Natural Perceived Focus and in the Perceptual Score of image quality in subjects after exposure to Simultaneous Vision. We show that Natural Perceived Focus shifts after a brief period of adaptation to a Simultaneous Vision blur, similar to adaptation to Pure Defocus. This shift strongly correlates with the magnitude and proportion of defocus in the adapting image. The magnitude of defocus affects perceived quality of Simultaneous Vision images, with 0.5 D defocus scored lowest and beyond 1.5 D scored “sharp”. Adaptation to Simultaneous Vision shifts the Perceptual Score of these images towards higher rankings. Larger improvements occurred when testing simultaneous images with the same magnitude of defocus as the adapting images, indicating that wearing a particular bifocal correction improves the perception of images provided by that correction. PMID:24664087

Sea Ice Thickness Measurement by Ground Penetrating Radar for Ground Truth of Microwave Remote Sensing Data

NASA Astrophysics Data System (ADS)

Matsumoto, M.; Yoshimura, M.; Naoki, K.; Cho, K.; Wakabayashi, H.

2018-04-01

Observation of sea ice thickness is one of key issues to understand regional effect of global warming. One of approaches to monitor sea ice in large area is microwave remote sensing data analysis. However, ground truth must be necessary to discuss the effectivity of this kind of approach. The conventional method to acquire ground truth of ice thickness is drilling ice layer and directly measuring the thickness by a ruler. However, this method is destructive, time-consuming and limited spatial resolution. Although there are several methods to acquire ice thickness in non-destructive way, ground penetrating radar (GPR) can be effective solution because it can discriminate snow-ice and ice-sea water interface. In this paper, we carried out GPR measurement in Lake Saroma for relatively large area (200 m by 300 m, approximately) aiming to obtain grand truth for remote sensing data. GPR survey was conducted at 5 locations in the area. The direct measurement was also conducted simultaneously in order to calibrate GPR data for thickness estimation and to validate the result. Although GPR Bscan image obtained from 600MHz contains the reflection which may come from a structure under snow, the origin of the reflection is not obvious. Therefore, further analysis and interpretation of the GPR image, such as numerical simulation, additional signal processing and use of 200 MHz antenna, are required to move on thickness estimation.

Half-blind remote sensing image restoration with partly unknown degradation

NASA Astrophysics Data System (ADS)

Xie, Meihua; Yan, Fengxia

2017-01-01

The problem of image restoration has been extensively studied for its practical importance and theoretical interest. This paper mainly discusses the problem of image restoration with partly unknown kernel. In this model, the degraded kernel function is known but its parameters are unknown. With this model, we should estimate the parameters in Gaussian kernel and the real image simultaneity. For this new problem, a total variation restoration model is put out and an intersect direction iteration algorithm is designed. Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measurement (SSIM) are used to measure the performance of the method. Numerical results show that we can estimate the parameters in kernel accurately, and the new method has both much higher PSNR and much higher SSIM than the expectation maximization (EM) method in many cases. In addition, the accuracy of estimation is not sensitive to noise. Furthermore, even though the support of the kernel is unknown, we can also use this method to get accurate estimation.

Bioinspired active whisker sensor for robotic vibrissal tactile sensing

NASA Astrophysics Data System (ADS)

Ju, Feng; Ling, Shih-Fu

2014-12-01

A whisker transducer (WT) inspired by rat’s vibrissal tactile perception is proposed based on a transduction matrix model characterizing the electro-mechanical transduction process in both forward and backward directions. It is capable of acting as an actuator to sweep the whisker and simultaneously as a sensor to sense the force, motion, and mechanical impedance at whisker tip. Its validity is confirmed by numerical simulation using a finite element model. A prototype is then fabricated and its transduction matrix is determined by parameter identification. The calibrated WT can accurately sense mechanical impedance which is directly related to stiffness, mass and damping. Subsequent vibrissal tactile sensing of sandpaper texture reveals that the real part of mechanical impedance sensed by WT is correlated with sandpaper roughness. Texture discrimination is successfully achieved by inputting the real part to a k-means clustering algorithm. The mechanical impedance sensing ability as well as other features of the WT such as simultaneous-actuation-and-sensing makes it a good solution to robotic tactile sensing.

Simultaneous direct detection of Shiga-toxin producing Escherichia coli (STEC) strains by gold nanoparticle optical sensing

USDA-ARS?s Scientific Manuscript database

Shiga-toxin producing Escherichia coli (STEC) strains (“Big Six” – O26, O45, O103, O111, O121, O145, and O157) represent significant groups of pathogens responsible for foodborne diseases. The objective of this study was to develop a colorimetric optical sensing assay that can simultaneously detect ...

Microprocessor-controlled laser tracker for atmospheric sensing

NASA Technical Reports Server (NTRS)

Johnson, R. A.; Webster, C. R.; Menzies, R. T.

1985-01-01

An optical tracking system comprising a visible HeNe laser, an imaging detector, and a microprocessor-controlled mirror, has been designed to track a moving retroreflector located up to 500 m away from an atmospheric instrument and simultaneously direct spectrally tunable infrared laser radiation to the retroreflector for double-ended, long-path absorption measurements of atmospheric species. The tracker has been tested during the recent flight of a balloon-borne tunable diode laser absorption spectrometer which monitors the concentrations of stratospheric species within a volume defined by a 0.14-m-diameter retroreflector lowered 500 m below the instrument gondola.

MEMS Fabry-Perot sensor interrogated by optical system-on-a-chip for simultaneous pressure and temperature sensing.

PubMed

Pang, Cheng; Bae, Hyungdae; Gupta, Ashwani; Bryden, Kenneth; Yu, Miao

2013-09-23

We present a micro-electro-mechanical systems (MEMS) based Fabry-Perot (FP) sensor along with an optical system-on-a-chip (SOC) interrogator for simultaneous pressure and temperature sensing. The sensor employs a simple structure with an air-backed silicon membrane cross-axially bonded to a 45° polished optical fiber. This structure renders two cascaded FP cavities, enabling simultaneous pressure and temperature sensing in close proximity along the optical axis. The optical SOC consists of a broadband source, a MEMS FP tunable filter, a photodetector, and the supporting circuitry, serving as a miniature spectrometer for retrieving the two FP cavity lengths. Within the measured pressure and temperature ranges, experimental results demonstrate that the sensor exhibits a good linear response to external pressure and temperature changes.

Estimation of water turbidity in Gorgan Bay, South-east of Caspian Sea by using IRS-LISS-III images.

PubMed

Aghighi, Hossein; Alimohammadi, Abbas; Saradjian, Mohammad Reza; Ashourloo, Davood

2008-03-01

In this research, usefulness of IRS-LISS-III data of Gorgan Bay, South-east of Caspian Sea located in North of Iran for water turbidity mapping, has been tested. After correction of geometric and radiometric errors, the resulting radiance data were used for examination of correlations between the remotely sensed and in situ water turbidity data simultaneously measured by the Secchi depth approach. Results of this research showed good relations between the Secchi depth and spectral data. The fitted statistical model was very significant (R2 = 0.77) and test of the model performance by independent samples was encouraging. Because of the low costs encountered with acquisition and processing of remotely sensed data, further research in larger scales for the purpose of more precise test of the approach for water turbidity mapping and monitoring is recommended.

Surface Wind Vector and Rain Rate Observation Capability of Future Hurricane Imaging Radiometer (HIRAD)

NASA Technical Reports Server (NTRS)

Miller, Timothy; Atlas, Robert; Bailey, M. C.; Black, Peter; El-Nimri, Salem; Hood, Robbie; James, Mark; Johnson, James; Jones, Linwood; Ruf, Christopher;

Single-scan patient-specific scatter correction in computed tomography using peripheral detection of scatter and compressed sensing scatter retrieval

PubMed Central

Meng, Bowen; Lee, Ho; Xing, Lei; Fahimian, Benjamin P.

2013-01-01

Purpose: X-ray scatter results in a significant degradation of image quality in computed tomography (CT), representing a major limitation in cone-beam CT (CBCT) and large field-of-view diagnostic scanners. In this work, a novel scatter estimation and correction technique is proposed that utilizes peripheral detection of scatter during the patient scan to simultaneously acquire image and patient-specific scatter information in a single scan, and in conjunction with a proposed compressed sensing scatter recovery technique to reconstruct and correct for the patient-specific scatter in the projection space. Methods: The method consists of the detection of patient scatter at the edges of the field of view (FOV) followed by measurement based compressed sensing recovery of the scatter through-out the projection space. In the prototype implementation, the kV x-ray source of the Varian TrueBeam OBI system was blocked at the edges of the projection FOV, and the image detector in the corresponding blocked region was used for scatter detection. The design enables image data acquisition of the projection data on the unblocked central region of and scatter data at the blocked boundary regions. For the initial scatter estimation on the central FOV, a prior consisting of a hybrid scatter model that combines the scatter interpolation method and scatter convolution model is estimated using the acquired scatter distribution on boundary region. With the hybrid scatter estimation model, compressed sensing optimization is performed to generate the scatter map by penalizing the L1 norm of the discrete cosine transform of scatter signal. The estimated scatter is subtracted from the projection data by soft-tuning, and the scatter-corrected CBCT volume is obtained by the conventional Feldkamp-Davis-Kress algorithm. Experimental studies using image quality and anthropomorphic phantoms on a Varian TrueBeam system were carried out to evaluate the performance of the proposed scheme. Results: The scatter shading artifacts were markedly suppressed in the reconstructed images using the proposed method. On the Catphan©504 phantom, the proposed method reduced the error of CT number to 13 Hounsfield units, 10% of that without scatter correction, and increased the image contrast by a factor of 2 in high-contrast regions. On the anthropomorphic phantom, the spatial nonuniformity decreased from 10.8% to 6.8% after correction. Conclusions: A novel scatter correction method, enabling unobstructed acquisition of the high frequency image data and concurrent detection of the patient-specific low frequency scatter data at the edges of the FOV, is proposed and validated in this work. Relative to blocker based techniques, rather than obstructing the central portion of the FOV which degrades and limits the image reconstruction, compressed sensing is used to solve for the scatter from detection of scatter at the periphery of the FOV, enabling for the highest quality reconstruction in the central region and robust patient-specific scatter correction. PMID:23298098

Self-monitored photothermal nanoparticles based on core-shell engineering

NASA Astrophysics Data System (ADS)

Ximendes, Erving C.; Rocha, Uéslen; Jacinto, Carlos; Kumar, Kagola Upendra; Bravo, David; López, Fernando J.; Rodríguez, Emma Martín; García-Solé, José; Jaque, Daniel

2016-01-01

The continuous development of nanotechnology has resulted in the actual possibility of the design and synthesis of nanostructured materials with pre-tailored functionabilities. Nanostructures capable of simultaneous heating and local thermal sensing are in strong demand as they would constitute a revolutionary solution to several challenging problems in bio-medicine, including the achievement of real time control during photothermal therapies. Several approaches have been demonstrated to achieve simultaneous heating and thermal sensing at the nanoscale. Some of them lack of sufficient thermal sensitivity and others require complicated synthesis procedures for heterostructure fabrication. In this study, we demonstrate how single core/shell dielectric nanoparticles with a highly Nd3+ ion doped shell and an Yb3+,Er3+ codoped core are capable of simultaneous thermal sensing and heating under an 808 nm single beam excitation. The spatial separation between the heating shell and sensing core provides remarkable values of the heating efficiency and thermal sensitivity, enabling their application in single beam-controlled heating experiments in both aqueous and tissue environments.

Simultaneous Interfacial Reactivity and Topography Mapping with Scanning Ion Conductance Microscopy.

PubMed

Momotenko, Dmitry; McKelvey, Kim; Kang, Minkyung; Meloni, Gabriel N; Unwin, Patrick R

2016-03-01

Scanning ion conductance microscopy (SICM) is a powerful technique for imaging the topography of a wide range of materials and interfaces. In this report, we develop the use and scope of SICM, showing how it can be used for mapping spatial distributions of ionic fluxes due to (electro)chemical reactions occurring at interfaces. The basic idea is that there is a change of ion conductance inside a nanopipet probe when it approaches an active site, where the ionic composition is different to that in bulk solution, and this can be sensed via the current flow in the nanopipet with an applied bias. Careful tuning of the tip potential allows the current response to be sensitive to either topography or activity, if desired. Furthermore, the use of a distance modulation SICM scheme allows reasonably faithful probe positioning using the resulting ac response, irrespective of whether there is a reaction at the interface that changes the local ionic composition. Both strategies (distance modulation or tuned bias) allow simultaneous topography-activity mapping with a single channel probe. The application of SICM reaction imaging is demonstrated on several examples, including voltammetric mapping of electrocatalytic reactions on electrodes and high-speed electrochemical imaging at rates approaching 4 s per image frame. These two distinct approaches provide movies of electrochemical current as a function of potential with hundreds of frames (images) of surface reactivity, to reveal a wealth of spatially resolved information on potential- (and time) dependent electrochemical phenomena. The experimental studies are supported by detailed finite element method modeling that places the technique on a quantitative footing.

Autonomous Navigation for Autonomous Underwater Vehicles Based on Information Filters and Active Sensing

PubMed Central

He, Bo; Zhang, Hongjin; Li, Chao; Zhang, Shujing; Liang, Yan; Yan, Tianhong

2011-01-01

This paper addresses an autonomous navigation method for the autonomous underwater vehicle (AUV) C-Ranger applying information-filter-based simultaneous localization and mapping (SLAM), and its sea trial experiments in Tuandao Bay (Shangdong Province, P.R. China). Weak links in the information matrix in an extended information filter (EIF) can be pruned to achieve an efficient approach-sparse EIF algorithm (SEIF-SLAM). All the basic update formulae can be implemented in constant time irrespective of the size of the map; hence the computational complexity is significantly reduced. The mechanical scanning imaging sonar is chosen as the active sensing device for the underwater vehicle, and a compensation method based on feedback of the AUV pose is presented to overcome distortion of the acoustic images due to the vehicle motion. In order to verify the feasibility of the navigation methods proposed for the C-Ranger, a sea trial was conducted in Tuandao Bay. Experimental results and analysis show that the proposed navigation approach based on SEIF-SLAM improves the accuracy of the navigation compared with conventional method; moreover the algorithm has a low computational cost when compared with EKF-SLAM. PMID:22346682

Autonomous navigation for autonomous underwater vehicles based on information filters and active sensing.

PubMed

He, Bo; Zhang, Hongjin; Li, Chao; Zhang, Shujing; Liang, Yan; Yan, Tianhong

2011-01-01

This paper addresses an autonomous navigation method for the autonomous underwater vehicle (AUV) C-Ranger applying information-filter-based simultaneous localization and mapping (SLAM), and its sea trial experiments in Tuandao Bay (Shangdong Province, P.R. China). Weak links in the information matrix in an extended information filter (EIF) can be pruned to achieve an efficient approach-sparse EIF algorithm (SEIF-SLAM). All the basic update formulae can be implemented in constant time irrespective of the size of the map; hence the computational complexity is significantly reduced. The mechanical scanning imaging sonar is chosen as the active sensing device for the underwater vehicle, and a compensation method based on feedback of the AUV pose is presented to overcome distortion of the acoustic images due to the vehicle motion. In order to verify the feasibility of the navigation methods proposed for the C-Ranger, a sea trial was conducted in Tuandao Bay. Experimental results and analysis show that the proposed navigation approach based on SEIF-SLAM improves the accuracy of the navigation compared with conventional method; moreover the algorithm has a low computational cost when compared with EKF-SLAM.

Simultaneous detection of transgenic DNA by surface plasmon resonance imaging with potential application to gene doping detection.

PubMed

Scarano, Simona; Ermini, Maria Laura; Spiriti, Maria Michela; Mascini, Marco; Bogani, Patrizia; Minunni, Maria

2011-08-15

Surface plasmon resonance imaging (SPRi) was used as the transduction principle for the development of optical-based sensing for transgenes detection in human cell lines. The objective was to develop a multianalyte, label-free, and real-time approach for DNA sequences that are identified as markers of transgenosis events. The strategy exploits SPRi sensing to detect the transgenic event by targeting selected marker sequences, which are present on shuttle vector backbone used to carry out the transfection of human embryonic kidney (HEK) cell lines. Here, we identified DNA sequences belonging to the Cytomegalovirus promoter and the Enhanced Green Fluorescent Protein gene. System development is discussed in terms of probe efficiency and influence of secondary structures on biorecognition reaction on sensor; moreover, optimization of PCR samples pretreatment was carried out to allow hybridization on biosensor, together with an approach to increase SPRi signals by in situ mass enhancement. Real-time PCR was also employed as reference technique for marker sequences detection on human HEK cells. We can foresee that the developed system may have potential applications in the field of antidoping research focused on the so-called gene doping.

A feasibility study for compressed sensing combined phase contrast MR angiography reconstruction

NASA Astrophysics Data System (ADS)

Lee, Dong-Hoon; Hong, Cheol-Pyo; Lee, Man-Woo; Han, Bong-Soo

2012-02-01

Phase contrast magnetic resonance angiography (PC MRA) is a technique for flow velocity measurement and vessels visualization, simultaneously. The PC MRA takes long scan time because each flow encoding gradients which are composed bipolar gradient type need to reconstruct the angiography image. Moreover, it takes more image acquisition time when we use the PC MRA at the low-tesla MRI system. In this study, we studied and evaluation of feasibility for CS MRI reconstruction combined PC MRA which data acquired by low-tesla MRI system. We used non-linear reconstruction algorithm which named Bregman iteration for CS image reconstruction and validate the usefulness of CS combined PC MRA reconstruction technique. The results of CS reconstructed PC MRA images provide similar level of image quality between fully sampled reconstruction data and sparse sampled reconstruction using CS technique. Although our results used half of sampling ratio and do not used specification hardware device or performance which are improving the temporal resolution of MR image acquisition such as parallel imaging reconstruction using phased array coil or non-cartesian trajectory, we think that CS combined PC MRA technique will be helpful to increase the temporal resolution and at low-tesla MRI system.

Calibration and testing of a Raman hyperspectral imaging system to reveal powdered food adulteration

PubMed Central

Lohumi, Santosh; Lee, Hoonsoo; Kim, Moon S.; Qin, Jianwei; Kandpal, Lalit Mohan; Bae, Hyungjin; Rahman, Anisur

2018-01-01

The potential adulteration of foodstuffs has led to increasing concern regarding food safety and security, in particular for powdered food products where cheap ground materials or hazardous chemicals can be added to increase the quantity of powder or to obtain the desired aesthetic quality. Due to the resulting potential health threat to consumers, the development of a fast, label-free, and non-invasive technique for the detection of adulteration over a wide range of food products is necessary. We therefore report the development of a rapid Raman hyperspectral imaging technique for the detection of food adulteration and for authenticity analysis. The Raman hyperspectral imaging system comprises of a custom designed laser illumination system, sensing module, and a software interface. Laser illumination system generates a 785 nm laser line of high power, and the Gaussian like intensity distribution of laser beam is shaped by incorporating an engineered diffuser. The sensing module utilize Rayleigh filters, imaging spectrometer, and detector for collection of the Raman scattering signals along the laser line. A custom-built software to acquire Raman hyperspectral images which also facilitate the real time visualization of Raman chemical images of scanned samples. The developed system was employed for the simultaneous detection of Sudan dye and Congo red dye adulteration in paprika powder, and benzoyl peroxide and alloxan monohydrate adulteration in wheat flour at six different concentrations (w/w) from 0.05 to 1%. The collected Raman imaging data of the adulterated samples were analyzed to visualize and detect the adulterant concentrations by generating a binary image for each individual adulterant material. The results obtained based on the Raman chemical images of adulterants showed a strong correlation (R>0.98) between added and pixel based calculated concentration of adulterant materials. This developed Raman imaging system thus, can be considered as a powerful analytical technique for the quality and authenticity analysis of food products. PMID:29708973

Calibration and testing of a Raman hyperspectral imaging system to reveal powdered food adulteration.

PubMed

Lohumi, Santosh; Lee, Hoonsoo; Kim, Moon S; Qin, Jianwei; Kandpal, Lalit Mohan; Bae, Hyungjin; Rahman, Anisur; Cho, Byoung-Kwan

2018-01-01

The potential adulteration of foodstuffs has led to increasing concern regarding food safety and security, in particular for powdered food products where cheap ground materials or hazardous chemicals can be added to increase the quantity of powder or to obtain the desired aesthetic quality. Due to the resulting potential health threat to consumers, the development of a fast, label-free, and non-invasive technique for the detection of adulteration over a wide range of food products is necessary. We therefore report the development of a rapid Raman hyperspectral imaging technique for the detection of food adulteration and for authenticity analysis. The Raman hyperspectral imaging system comprises of a custom designed laser illumination system, sensing module, and a software interface. Laser illumination system generates a 785 nm laser line of high power, and the Gaussian like intensity distribution of laser beam is shaped by incorporating an engineered diffuser. The sensing module utilize Rayleigh filters, imaging spectrometer, and detector for collection of the Raman scattering signals along the laser line. A custom-built software to acquire Raman hyperspectral images which also facilitate the real time visualization of Raman chemical images of scanned samples. The developed system was employed for the simultaneous detection of Sudan dye and Congo red dye adulteration in paprika powder, and benzoyl peroxide and alloxan monohydrate adulteration in wheat flour at six different concentrations (w/w) from 0.05 to 1%. The collected Raman imaging data of the adulterated samples were analyzed to visualize and detect the adulterant concentrations by generating a binary image for each individual adulterant material. The results obtained based on the Raman chemical images of adulterants showed a strong correlation (R>0.98) between added and pixel based calculated concentration of adulterant materials. This developed Raman imaging system thus, can be considered as a powerful analytical technique for the quality and authenticity analysis of food products.

New Optical Sensing Materials for Application in Marine Research

NASA Astrophysics Data System (ADS)

Borisov, S.; Klimant, I.

2012-04-01

Optical chemosensors are versatile analytical tools which find application in numerous fields of science and technology. They proved to be a promising alternative to electrochemical methods and are applied increasingly often in marine research. However, not all state-of-the- art optical chemosensors are suitable for these demanding applications since they do not fully fulfil the requirements of high luminescence brightness, high chemical- and photochemical stability or their spectral properties are not adequate. Therefore, development of new advanced sensing materials is still of utmost importance. Here we present a set of novel optical sensing materials recently developed in the Institute of Analytical Chemistry and Food Chemistry which are optimized for marine applications. Particularly, we present new NIR indicators and sensors for oxygen and pH which feature high brightness and low level of autofluorescence. The oxygen sensors rely on highly photostable metal complexes of benzoporphyrins and azabenzoporphyrins and enable several important applications such as simultaneous monitoring of oxygen and chlorophyll or ultra-fast oxygen monitoring (Eddy correlation). We also developed ulta-sensitive oxygen optodes which enable monitoring in nM range and are primary designed for investigation of oxygen minimum zones. The dynamic range of our new NIR pH indicators based on aza-BODIPY dyes is optimized for the marine environment. A highly sensitive NIR luminescent phosphor (chromium(III) doped yttrium aluminium borate) can be used for non-invasive temperature measurements. Notably, the oxygen, pH sensors and temperature sensors are fully compatible with the commercially available fiber-optic readers (Firesting from PyroScience). An optical CO2 sensor for marine applications employs novel diketopyrrolopyrrol indicators and enables ratiometric imaging using a CCD camera. Oxygen, pH and temperature sensors suitable for lifetime and ratiometric imaging of analytes distribution are also realized. To enable versatility of applications we also obtained a range of nano- and microparticles suitable for intra- and extracellular imaging of the above analytes. Bright ratiometric 2-photon-excitable probes were also developed. Magnetic microparticles are demonstrated to be very promising tools for imaging of oxygen, temperature and other parameters in biofilms, corals etc. since they combine the sensing function with the possibility of external manipulation.

Data-intensive multispectral remote sensing of the nighttime Earth for environmental monitoring and emergency response

NASA Astrophysics Data System (ADS)

Zhizhin, M.; Poyda, A.; Velikhov, V.; Novikov, A.; Polyakov, A.

2016-02-01

All Most of the remote sensing applications rely on the daytime visible and infrared images of the Earth surface. Increase in the number of satellites, their spatial resolution as well as the number of the simultaneously observed spectral bands ensure a steady growth of the data volumes and computational complexity in the remote sensing sciences. Recent advance in the night time remote sensing is related to the enhanced sensitivity of the on-board instruments and to the unique opportunity to observe “pure” emitters in visible infrared spectra without contamination from solar heat and reflected light. A candidate set of the night-time emitters observable from the low-orbiting and geostationary satellites include steady state and temporal changes in the city and traffic electric lights, fishing boats, high-temperature industrial objects such as steel mills, oil cracking refineries and power plants, forest and agricultural fires, gas flares, volcanic eruptions and similar catastrophic events. Current satellite instruments can detect at night 10 times more of such objects compared to daytime. We will present a new data-intensive workflow of the night time remote sensing algorithms for map-reduce processing of visible and infrared images from the multispectral radiometers flown by the modern NOAA/NASA Suomi NPP and the USGS Landsat 8 satellites. Similar radiometers are installed on the new generation of the US geostationary GOES-R satellite to be launched in 2016. The new set of algorithms allows us to detect with confidence and track the abrupt changes and long-term trends in the energy of city lights, number of fishing boats, as well as the size, geometry, temperature of gas flares and to estimate monthly and early flared gas volumes by site or by country. For real-time analysis of the night time multispectral satellite images with global coverage we need gigabit network, petabyte data storage and parallel compute cluster with more than 20 nodes. To meet the processing requirements, we have used the supercomputer at the Kurchatov Institute in Moscow.

A comparison of airborne evapotranspiration maps and sapflow measurements in oak and beech forest stands

NASA Astrophysics Data System (ADS)

Schlerf, M.; Mallick, K.; Hassler, S. K.; Blume, T.; Ronellenfitsch, F.; Gerhards, M.; Udelhoven, T.; Weiler, M.

2017-12-01

Accurate estimations of spatially explicit daily Evapotranspiration (ET) may help water managers quantifying the water requirements of agricultural crops or trees. Airborne remote sensing may provide suitable ET maps, but uncertainties need to be better understood. In this study we compared high spatial resolution remotely sensed ET maps for 7 July 2016 with sap flow measurements over 32 forest stands located in the Attert catchment, Luxembourg. Forest stands differed in terms of species (Quercus robur, Fagus sylvatica), geology (schist, marl, sandstone), and geomorphology (slope position, plain, valley). Within each plot, at 1-3 trees the sap flow velocity (cm per hour) was measured between 8 am and 8 pm in 10 min intervals and averaged into a single value per plot and converted into values of volume flux (litres per day). Remotely sensed ET maps were derived by integrating airborne thermal infrared (TIR) images with an analytical surface energy balance model, Surface Temperature Initiated Closure (STIC1.2, Mallick et al. 2016). Airborne TIR images were acquired under clear sky conditions at 9:12, 10:08, 13:56, 14:50, 15:54, and 18:41 local time using a hyperspectral-thermal instrument. Images were geometrically corrected, calibrated, mosaicked, and converted to surface radiometric temperature. Surface temperature maps in conjunction with meteorological measurements recorded in the forest plots (air temperature, global radiation, relative humidity) were used as input to STIC1.2, for simultaneously estimating ET, sensible heat flux as well as surface and aerodynamic conductances. Instantaneous maps of ET were converted into daily ET maps and compared with the sap flow measurements. Results reveal a significant correspondence between remote sensing and field measured ET. The differences in the magnitude of predicted versus observed ET was found to be associated the biophysical conductances, radiometric surface temperature, and ecohydrological characteristics of the underlying landscape. Forest plots reveal differences in ET depending on the underlying geology and the slope position. Airborne remote sensing offers new ways of estimating the diurnal course of plant transpiration over entire landscapes and is an important bridging technology before high resolution TIR sensors will come into space.

Accelerated high-resolution photoacoustic tomography via compressed sensing

NASA Astrophysics Data System (ADS)

Arridge, Simon; Beard, Paul; Betcke, Marta; Cox, Ben; Huynh, Nam; Lucka, Felix; Ogunlade, Olumide; Zhang, Edward

2016-12-01

Current 3D photoacoustic tomography (PAT) systems offer either high image quality or high frame rates but are not able to deliver high spatial and temporal resolution simultaneously, which limits their ability to image dynamic processes in living tissue (4D PAT). A particular example is the planar Fabry-Pérot (FP) photoacoustic scanner, which yields high-resolution 3D images but takes several minutes to sequentially map the incident photoacoustic field on the 2D sensor plane, point-by-point. However, as the spatio-temporal complexity of many absorbing tissue structures is rather low, the data recorded in such a conventional, regularly sampled fashion is often highly redundant. We demonstrate that combining model-based, variational image reconstruction methods using spatial sparsity constraints with the development of novel PAT acquisition systems capable of sub-sampling the acoustic wave field can dramatically increase the acquisition speed while maintaining a good spatial resolution: first, we describe and model two general spatial sub-sampling schemes. Then, we discuss how to implement them using the FP interferometer and demonstrate the potential of these novel compressed sensing PAT devices through simulated data from a realistic numerical phantom and through measured data from a dynamic experimental phantom as well as from in vivo experiments. Our results show that images with good spatial resolution and contrast can be obtained from highly sub-sampled PAT data if variational image reconstruction techniques that describe the tissues structures with suitable sparsity-constraints are used. In particular, we examine the use of total variation (TV) regularization enhanced by Bregman iterations. These novel reconstruction strategies offer new opportunities to dramatically increase the acquisition speed of photoacoustic scanners that employ point-by-point sequential scanning as well as reducing the channel count of parallelized schemes that use detector arrays.

Combined SRCT & FXCT - The next steps

NASA Astrophysics Data System (ADS)

Hall, C.; Acres, R. G.; Winnett, A.; Wang, F.

2016-03-01

One of the goals in developing synchrotron radiation x-ray computed tomography (SRCT) for biomedical specimens, is allowing particular tissues and cell types to be marked in the images. This is equivalent to the staining in histology, which enables researchers to visualise and measure tissue structure and biochemical processes within the specimen. Some progress in this direction for SRCT is being made, using a variety of contrast agents that alter the natural x-ray attenuation of the marked tissue [1]. However there are limits to the usefulness of these attenuation altering techniques. Often high concentrations of potentially disruptive chemicals are required with reduced compatibility for in-vivo studies. Another image highlighting technique which might prove more sensitive is x-ray fluorescence imaging. In this case usually endogenous elemental markers are visualised. We would like to develop a lower resolution, but wider field of view means of three-dimensional (3-D) fluorescence imaging compatible with SRCT. We have previously proposed a technique in which x-ray fluorescence CT (FXCT) and SRCT data can be collected simultaneously [2]. This work resulted in proof of concept modelling, and a simple experiment test system. We show data here which demonstrate a two-dimensional (2-D) reconstruction of an iodine fluorescence map from a phantom. Measurements were performed with a fixed beam modulating mask using the Imaging and Medical beam line (IMBL) at the Australian Synchrotron. Fluorescence data was obtained during a CT scan using a single point detector, while transmission data was simultaneously collected using an area detector. A maximum likelihood expectation maximisation (MLEM) iterative algorithm was used to reconstruct the fluorescence map. We report on technique development and now believe compressive sensing (CS) imaging techniques suit SRCT and may overcome the issues encountered so far in combining SRCT and FXCT.

Remote Sensing of the Upper Atmosphere and the Ionosphere in the Extreme and Far Ultraviolet: Results from the LITES Experiment aboard the IS

NASA Astrophysics Data System (ADS)

Finn, S. C.; Chakrabarti, S.; Stephan, A. W.; Geddes, G.; Budzien, S. A.; Cook, T.; Aryal, S.; Martel, J.; Galkin, I. A.; Erickson, P. J.

2017-12-01

The Limb-Imaging Ionospheric and Thermospheric Extreme-ultraviolet Spectrograph (LITES) was launched as part of the Space Test Program Houston #5 (STP-H5) payload aboard a commercial resupply flight on February 19, 2017 and was subsequently installed on the International Space Station (ISS). LITES is an imaging spectrograph that spans the 60 - 140 nm wavelength range at 1 nm spectral resolution and samples tangent altitudes 150 - 350 km with 0.2° angular resolution. LITES, in combination with the GPS Radio Occultation and Ultraviolet Photometry - Colocated (GROUP-C) experiment, which includes a GPS receiver and a nadir viewing 135.6 nm photometer, jointly collect new information on the thermosphere and the ionosphere using simultaneous UV and radio emissions. LITES, which uses standard stars to perform in-flight calibration, observes altitude profiles of day and night airglow emissions that are being used to infer thermospheric and ionospheric density profiles. Furthermore, due to the inclination of the ISS, LITES has also observed auroral spectrum and their altitude and spatial variations. Finally, geomagnetic storm effects on its UV emissions can be used to remotely sense their effects on the upper atmospheric morphology. These ISS observations,which are complement to the upcoming ICON and GOLD NASA missions, are focused on ionosphere-atmosphere coupling and global-scale atmospheric response to space weather observed from higher altitudes . We will present an overview of the LITES instrument, some early results from the first few months of operations. We will also summarize the advantages in calibration and validation activities that are possible through space-based LITES, GROUP-C and stellar measurements and simultaneous ground-based optical and radar observations.

Oxygen Sensing Difluoroboron β-Diketonate Polylactide Materials with Tunable Dynamic Ranges for Wound Imaging.

PubMed

DeRosa, Christopher A; Seaman, Scott A; Mathew, Alexander S; Gorick, Catherine M; Fan, Ziyi; Demas, James N; Peirce, Shayn M; Fraser, Cassandra L

2016-11-23

Difluoroboron β-diketonate poly(lactic acid) materials exhibit both fluorescence (F) and oxygen sensitive room-temperature phosphorescence (RTP). Introduction of halide heavy atoms (Br and I) is an effective strategy to control the oxygen sensitivity in these materials. A series of naphthyl-phenyl (nbm) dye derivatives with hydrogen, bromide and iodide substituents were prepared for comparison. As nanoparticles, the hydrogen derivative was hypersensitive to oxygen (0-0.3%), while the bromide analogue was suited for hypoxia detection (0-3% O 2 ). The iodo derivative, BF 2 nbm(I)PLA, showed excellent F to RTP peak separation and an 0-100% oxygen sensitivity range unprecedented for metal-free RTP emitting materials. Due to the dual emission and unconventionally long RTP lifetimes of these O 2 sensing materials, a portable, cost-effective camera was used to quantify oxygen levels via lifetime and red/green/blue (RGB) ratiometry. The hypersensitive H dye was well matched to lifetime detection, simultaneous lifetime and ratiometric imaging was possible for the bromide analogue, whereas the iodide material, with intense RTP emission and a shorter lifetime, was suited for RGB ratiometry. To demonstrate the prospects of this camera/material design combination for bioimaging, iodide boron dye-PLA nanoparticles were applied to a murine wound model to detect oxygen levels. Surprisingly, wound oxygen imaging was achieved without covering (i.e. without isolating from ambient conditions, air). Additionally, would healing was monitored via wound size reduction and associated oxygen recovery, from hypoxic to normoxic. These single-component materials provide a simple tunable platform for biological oxygen sensing that can be deployed to spatially resolve oxygen in a variety of environments.

Extended hybrid-space SENSE for EPI: Off-resonance and eddy current corrected joint interleaved blip-up/down reconstruction.

PubMed

Zahneisen, Benjamin; Aksoy, Murat; Maclaren, Julian; Wuerslin, Christian; Bammer, Roland

2017-06-01

Geometric distortions along the phase encode direction caused by off-resonant spins are still a major issue in EPI based functional and diffusion imaging. If the off-resonance map is known it is possible to correct for distortions. Most correction methods operate as a post-processing step on the reconstructed magnitude images. Here, we present an algebraic reconstruction method (hybrid-space SENSE) that incorporates a physics based model of off-resonances, phase inconsistencies between k-space segments, and T2*-decay during the acquisition. The method can be used to perform a joint reconstruction of interleaved acquisitions with normal (blip-up) and inverted (blip-down) phase encode direction which results in reduced g-factor penalty. A joint blip-up/down simultaneous multi slice (SMS) reconstruction for SMS-factor 4 in combination with twofold in-plane acceleration leads to a factor of two decrease in maximum g-factor penalty while providing off-resonance and eddy-current corrected images. We provide an algebraic framework for reconstructing diffusion weighted EPI data that in addition to the general applicability of hybrid-space SENSE to 2D-EPI, SMS-EPI and 3D-EPI with arbitrary k-space coverage along z, allows for a modeling of arbitrary spatio-temporal effects during the acquisition period like off-resonances, phase inconsistencies and T2*-decay. The most immediate benefit is a reduction in g-factor penalty if an interleaved blip-up/down acquisition strategy is chosen which facilitates eddy current estimation and ensures no loss in k-space encoding in regions with strong off-resonance gradients. Copyright © 2017 Elsevier Inc. All rights reserved.

Sensing Performance Analysis on Quartz Tuning Fork-Probe at the High Order Vibration Mode for Multi-Frequency Scanning Probe Microscopy

PubMed Central

Gao, Fengli; Li, Xide

2018-01-01

Multi-frequency scanning near-field optical microscopy, based on a quartz tuning fork-probe (QTF-p) sensor using the first two orders of in-plane bending symmetrical vibration modes, has recently been developed. This method can simultaneously achieve positional feedback (based on the 1st in-plane mode called the low mode) and detect near-field optically induced forces (based on the 2nd in-plane mode called the high mode). Particularly, the high mode sensing performance of the QTF-p is an important issue for characterizing the tip-sample interactions and achieving higher resolution microscopic imaging but the related researches are insufficient. Here, we investigate the vibration performance of QTF-p at high mode based on the experiment and finite element method. The frequency spectrum characteristics are obtained by our homemade laser Doppler vibrometer system. The effects of the properties of the connecting glue layer and the probe features on the dynamic response of the QTF-p sensor at the high mode are investigated for optimization design. Finally, compared with the low mode, an obvious improvement of quality factor, of almost 50%, is obtained at the high mode. Meanwhile, the QTF-p sensor has a high force sensing sensitivity and a large sensing range at the high mode, indicating a broad application prospect for force sensing. PMID:29364847

Compressive sensing in medical imaging

PubMed Central

Graff, Christian G.; Sidky, Emil Y.

2015-01-01

The promise of compressive sensing, exploitation of compressibility to achieve high quality image reconstructions with less data, has attracted a great deal of attention in the medical imaging community. At the Compressed Sensing Incubator meeting held in April 2014 at OSA Headquarters in Washington, DC, presentations were given summarizing some of the research efforts ongoing in compressive sensing for x-ray computed tomography and magnetic resonance imaging systems. This article provides an expanded version of these presentations. Sparsity-exploiting reconstruction algorithms that have gained popularity in the medical imaging community are studied, and examples of clinical applications that could benefit from compressive sensing ideas are provided. The current and potential future impact of compressive sensing on the medical imaging field is discussed. PMID:25968400

Object-oriented recognition of high-resolution remote sensing image

NASA Astrophysics Data System (ADS)

Wang, Yongyan; Li, Haitao; Chen, Hong; Xu, Yuannan

2016-01-01

With the development of remote sensing imaging technology and the improvement of multi-source image's resolution in satellite visible light, multi-spectral and hyper spectral , the high resolution remote sensing image has been widely used in various fields, for example military field, surveying and mapping, geophysical prospecting, environment and so forth. In remote sensing image, the segmentation of ground targets, feature extraction and the technology of automatic recognition are the hotspot and difficulty in the research of modern information technology. This paper also presents an object-oriented remote sensing image scene classification method. The method is consist of vehicles typical objects classification generation, nonparametric density estimation theory, mean shift segmentation theory, multi-scale corner detection algorithm, local shape matching algorithm based on template. Remote sensing vehicles image classification software system is designed and implemented to meet the requirements .

Watershed Allied Telemetry Experimental Research

NASA Astrophysics Data System (ADS)

Li, Xin; Li, Xiaowen; Li, Zengyuan; Ma, Mingguo; Wang, Jian; Xiao, Qing; Liu, Qiang; Che, Tao; Chen, Erxue; Yan, Guangjian; Hu, Zeyong; Zhang, Lixin; Chu, Rongzhong; Su, Peixi; Liu, Qinhuo; Liu, Shaomin; Wang, Jindi; Niu, Zheng; Chen, Yan; Jin, Rui; Wang, Weizhen; Ran, Youhua; Xin, Xiaozhou; Ren, Huazhong

2009-11-01

The Watershed Allied Telemetry Experimental Research (WATER) is a simultaneous airborne, satellite-borne, and ground-based remote sensing experiment aiming to improve the observability, understanding, and predictability of hydrological and related ecological processes at a catchment scale. WATER consists of the cold region, forest, and arid region hydrological experiments as well as a hydrometeorology experiment and took place in the Heihe River Basin, a typical inland river basin in the northwest of China. The field campaigns have been completed, with an intensive observation period lasting from 7 March to 12 April, from 15 May to 22 July, and from 23 August to 5 September 2008: in total, 120 days. Twenty-five airborne missions were flown. Airborne sensors including microwave radiometers at L, K, and Ka bands, imaging spectrometer, thermal imager, CCD, and lidar were used. Various satellite data were collected. Ground measurements were carried out at four scales, that is, key experimental area, foci experimental area, experiment site, and elementary sampling plot, using ground-based remote sensing instruments, densified network of automatic meteorological stations, flux towers, and hydrological stations. On the basis of these measurements, the remote sensing retrieval models and algorithms of water cycle variables are to be developed or improved, and a catchment-scale land/hydrological data assimilation system is being developed. This paper reviews the background, scientific objectives, experiment design, filed campaign implementation, and current status of WATER. The analysis of the data will continue over the next 2 years, and limited revisits to the field are anticipated.

Determining biosonar images using sparse representations.

PubMed

Fontaine, Bertrand; Peremans, Herbert

2009-05-01

Echolocating bats are thought to be able to create an image of their environment by emitting pulses and analyzing the reflected echoes. In this paper, the theory of sparse representations and its more recent further development into compressed sensing are applied to this biosonar image formation task. Considering the target image representation as sparse allows formulation of this inverse problem as a convex optimization problem for which well defined and efficient solution methods have been established. The resulting technique, referred to as L1-minimization, is applied to simulated data to analyze its performance relative to delay accuracy and delay resolution experiments. This method performs comparably to the coherent receiver for the delay accuracy experiments, is quite robust to noise, and can reconstruct complex target impulse responses as generated by many closely spaced reflectors with different reflection strengths. This same technique, in addition to reconstructing biosonar target images, can be used to simultaneously localize these complex targets by interpreting location cues induced by the bat's head related transfer function. Finally, a tentative explanation is proposed for specific bat behavioral experiments in terms of the properties of target images as reconstructed by the L1-minimization method.

The Acoustic Lens Design and in Vivo Use of a Multifunctional Catheter Combining Intracardiac Ultrasound Imaging and Electrophysiology Sensing

PubMed Central

Stephens, Douglas N.; Cannata, Jonathan; Liu, Ruibin; Zhao, Jian Zhong; Shung, K. Kirk; Nguyen, Hien; Chia, Raymond; Dentinger, Aaron; Wildes, Douglas; Thomenius, Kai E.; Mahajan, Aman; Shivkumar, Kalyanam; Kim, Kang; O’Donnell, Matthew; Sahn, David

2009-01-01

A multifunctional 9F intracardiac imaging and electrophysiology mapping catheter was developed and tested to help guide diagnostic and therapeutic intracardiac electrophysiology (EP) procedures. The catheter tip includes a 7.25-MHz, 64-element, side-looking phased array for high resolution sector scanning. Multiple electrophysiology mapping sensors were mounted as ring electrodes near the array for electrocardiographic synchronization of ultrasound images. The catheter array elevation beam performance in particular was investigated. An acoustic lens for the distal tip array designed with a round cross section can produce an acceptable elevation beam shape; however, the velocity of sound in the lens material should be approximately 155 m/s slower than in tissue for the best beam shape and wide bandwidth performance. To help establish the catheter’s unique ability for integration with electrophysiology interventional procedures, it was used in vivo in a porcine animal model, and demonstrated both useful intracardiac echocardiographic visualization and simultaneous 3-D positional information using integrated electroanatomical mapping techniques. The catheter also performed well in high frame rate imaging, color flow imaging, and strain rate imaging of atrial and ventricular structures. PMID:18407850

Apparatus and method for the simultaneous detection of neutrons and ionizing electromagnetic radiation

DOEpatents

Bell, Zane W.

2000-01-01

A sensor for simultaneously detecting neutrons and ionizing electromagnetic radiation comprising: a sensor for the detection of gamma radiation, the sensor defining a sensing head; the sensor further defining an output end in communication with the sensing head; and an exterior neutron-sensitive material configured to form around the sensing head; wherein the neutron-sensitive material, subsequent to the capture of the neutron, fissions into an alpha-particle and a .sup.7 Li ion that is in a first excited state in a majority of the fissions, the first excited state decaying via the emission of a single gamma ray at 478 keV which can in turn be detected by the sensing head; and wherein the sensing head can also detect the ionizing electromagnetic radiation from an incident radiation field without significant interference from the neutron-sensitive material. A method for simultaneously detecting neutrons and ionizing electromagnetic radiation comprising the steps of: providing a gamma ray sensitive detector comprising a sensing head and an output end; conforming an exterior neutron-sensitive material configured to form around the sensing head of the detector; capturing neutrons by the sensing head causing the neutron-sensitive material to fission into an alpha-particle and a .sup.7 Li ion that is in a first excited state in a majority of the fissions, the state decaying via the emission of a single gamma ray at 478 keV; sensing gamma rays entering the detector through the neutron-sensitive material; and producing an output through a readout device coupled to the output end; wherein the detector provides an output which is proportional to the energy of the absorbed ionizing electromagnetic radiation.

An Approach of Registration between Remote Sensing Image and Electronic Chart Based on Coastal Line

NASA Astrophysics Data System (ADS)

Li, Ying; Yu, Shuiming; Li, Chuanlong

Remote sensing plays an important role marine oil spill emergency. In order to implement a timely and effective countermeasure, it is important to provide exact position of oil spills. Therefore it is necessary to match remote sensing image and electronic chart properly. Variance ordinarily exists between oil spill image and electronic chart, although geometric correction is applied to remote sensing image. It is difficult to find the steady control points on sea to make exact rectification of remote sensing image. An improved relaxation algorithm was developed for finding the control points along the coastline since oil spills occurs generally near the coast. A conversion function is created with the least square, and remote sensing image can be registered with the vector map based on this function. SAR image was used as the remote sensing data and shape format map as the electronic chart data. The results show that this approach can guarantee the precision of the registration, which is essential for oil spill monitoring.

Masking agent-free and channel-switch-mode simultaneous sensing of Fe(3+) and Hg(2+) using dual-excitation graphene quantum dots.

PubMed

Xu, Fengzhou; Shi, Hui; He, Xiaoxiao; Wang, Kemin; He, Dinggeng; Yan, Lv'an; Ye, Xiaosheng; Tang, Jinlu; Shangguan, Jingfang; Luo, Lan

2015-06-21

A novel channel-switch-mode strategy for simultaneous sensing of Fe(3+) and Hg(2+) is developed with dual-excitation single-emission graphene quantum dots (GQDs). By utilizing the dual-channel fluorescence response performance of GQDs, this strategy achieved a facile, low-cost, masking agent-free, quantitative and selective dual-ion assay even in mixed ion samples and practical water samples.

Optical quasi-distributed simultaneous vibration and temperature sensing in stator bars of a 370-MVA electric generator

NASA Astrophysics Data System (ADS)

Dreyer, Uilian José; Vagner da Silva, Erlon; Martelli, Cicero; Cardozo da Silva, Jean Carlos

2017-08-01

In this paper, we propose a new multiparametric optical fiber transducer applied to an electric generator of 370 MVA. The optical transducer has three multiplexed FBGs in the same optical fiber as the sensing element. The FBG sensors can simultaneously measure both the temperature and vibration independently of the other multiplexed FBGs. The installation in the power plant was performed using six transducers and it was obtained 23 hours of simultaneous vibration and temperature measurement. All the FBGs used to monitor generator vibration were able to monitor the frequency of mechanical and electromagnetic vibrations, which were measured at 2 Hz and 120 Hz, respectively. During the measurement, the machine was turned off due to a failure and all the FBGs sensed temperature changes, as well as frequency vibration changes. The largest temperature difference measured between the FBGs during the test is approximately 2°C.

Measurement of Entrance Surface Dose on an Anthropomorphic Thorax Phantom Using a Miniature Fiber-Optic Dosimeter

PubMed Central

Yoo, Wook Jae; Shin, Sang Hun; Jeon, Dayeong; Hong, Seunghan; Sim, Hyeok In; Kim, Seon Geun; Jang, Kyoung Won; Cho, Seunghyun; Youn, Won Sik; Lee, Bongsoo

2014-01-01

A miniature fiber-optic dosimeter (FOD) system was fabricated using a plastic scintillating fiber, a plastic optical fiber, and a multi-pixel photon counter to measure real-time entrance surface dose (ESD) during radiation diagnosis. Under varying exposure parameters of a digital radiography (DR) system, we measured the scintillating light related to the ESD using the sensing probe of the FOD, which was placed at the center of the beam field on an anthropomorphic thorax phantom. Also, we obtained DR images using a flat panel detector of the DR system to evaluate the effects of the dosimeter on image artifacts during posteroanterior (PA) chest radiography. From the experimental results, the scintillation output signals of the FOD were similar to the ESDs including backscatter simultaneously obtained using a semiconductor dosimeter. We demonstrated that the proposed miniature FOD can be used to measure real-time ESDs with minimization of DR image artifacts in the X-ray energy range of diagnostic radiology. PMID:24694678

Measurement of entrance surface dose on an anthropomorphic thorax phantom using a miniature fiber-optic dosimeter.

PubMed

Yoo, Wook Jae; Shin, Sang Hun; Jeon, Dayeong; Hong, Seunghan; Sim, Hyeok In; Kim, Seon Geun; Jang, Kyoung Won; Cho, Seunghyun; Youn, Won Sik; Lee, Bongsoo

2014-04-01

A miniature fiber-optic dosimeter (FOD) system was fabricated using a plastic scintillating fiber, a plastic optical fiber, and a multi-pixel photon counter to measure real-time entrance surface dose (ESD) during radiation diagnosis. Under varying exposure parameters of a digital radiography (DR) system, we measured the scintillating light related to the ESD using the sensing probe of the FOD, which was placed at the center of the beam field on an anthropomorphic thorax phantom. Also, we obtained DR images using a flat panel detector of the DR system to evaluate the effects of the dosimeter on image artifacts during posteroanterior (PA) chest radiography. From the experimental results, the scintillation output signals of the FOD were similar to the ESDs including backscatter simultaneously obtained using a semiconductor dosimeter. We demonstrated that the proposed miniature FOD can be used to measure real-time ESDs with minimization of DR image artifacts in the X-ray energy range of diagnostic radiology.

Three-dimensional nanometre localization of nanoparticles to enhance super-resolution microscopy

NASA Astrophysics Data System (ADS)

Bon, Pierre; Bourg, Nicolas; Lécart, Sandrine; Monneret, Serge; Fort, Emmanuel; Wenger, Jérôme; Lévêque-Fort, Sandrine

2015-07-01

Meeting the nanometre resolution promised by super-resolution microscopy techniques (pointillist: PALM, STORM, scanning: STED) requires stabilizing the sample drifts in real time during the whole acquisition process. Metal nanoparticles are excellent probes to track the lateral drifts as they provide crisp and photostable information. However, achieving nanometre axial super-localization is still a major challenge, as diffraction imposes large depths-of-fields. Here we demonstrate fast full three-dimensional nanometre super-localization of gold nanoparticles through simultaneous intensity and phase imaging with a wavefront-sensing camera based on quadriwave lateral shearing interferometry. We show how to combine the intensity and phase information to provide the key to the third axial dimension. Presently, we demonstrate even in the occurrence of large three-dimensional fluctuations of several microns, unprecedented sub-nanometre localization accuracies down to 0.7 nm in lateral and 2.7 nm in axial directions at 50 frames per second. We demonstrate that nanoscale stabilization greatly enhances the image quality and resolution in direct stochastic optical reconstruction microscopy imaging.

Prostate segmentation: an efficient convex optimization approach with axial symmetry using 3-D TRUS and MR images.

PubMed

Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

2014-04-01

We propose a novel global optimization-based approach to segmentation of 3-D prostate transrectal ultrasound (TRUS) and T2 weighted magnetic resonance (MR) images, enforcing inherent axial symmetry of prostate shapes to simultaneously adjust a series of 2-D slice-wise segmentations in a "global" 3-D sense. We show that the introduced challenging combinatorial optimization problem can be solved globally and exactly by means of convex relaxation. In this regard, we propose a novel coherent continuous max-flow model (CCMFM), which derives a new and efficient duality-based algorithm, leading to a GPU-based implementation to achieve high computational speeds. Experiments with 25 3-D TRUS images and 30 3-D T2w MR images from our dataset, and 50 3-D T2w MR images from a public dataset, demonstrate that the proposed approach can segment a 3-D prostate TRUS/MR image within 5-6 s including 4-5 s for initialization, yielding a mean Dice similarity coefficient of 93.2%±2.0% for 3-D TRUS images and 88.5%±3.5% for 3-D MR images. The proposed method also yields relatively low intra- and inter-observer variability introduced by user manual initialization, suggesting a high reproducibility, independent of observers.

Biphasic DC measurement approach for enhanced measurement stability and multi-channel sampling of self-sensing multi-functional structural materials doped with carbon-based additives

NASA Astrophysics Data System (ADS)

Downey, Austin; D'Alessandro, Antonella; Ubertini, Filippo; Laflamme, Simon; Geiger, Randall

2017-06-01

Investigation of multi-functional carbon-based self-sensing structural materials for structural health monitoring applications is a topic of growing interest. These materials are self-sensing in the sense that they can provide measurable electrical outputs corresponding to physical changes such as strain or induced damage. Nevertheless, the development of an appropriate measurement technique for such materials is yet to be achieved, as many results in the literature suggest that these materials exhibit a drift in their output when measured with direct current (DC) methods. In most of the cases, the electrical output is a resistance and the reported drift is an increase in resistance from the time the measurement starts due to material polarization. Alternating current methods seem more appropriate at eliminating the time drift. However, published results show they are not immune to drift. Moreover, the use of multiple impedance measurement devices (LCR meters) does not allow for the simultaneous multi-channel sampling of multi-sectioned self-sensing materials due to signal crosstalk. The capability to simultaneously monitor multiple sections of self-sensing structural materials is needed to deploy these multi-functional materials for structural health monitoring. Here, a biphasic DC measurement approach with a periodic measure/discharge cycle in the form of a square wave sensing current is used to provide consistent, stable resistance measurements for self-sensing structural materials. DC measurements are made during the measurement region of the square wave while material depolarization is obtained during the discharge region of the periodic signal. The proposed technique is experimentally shown to remove the signal drift in a carbon-based self-sensing cementitious material while providing simultaneous multi-channel measurements of a multi-sectioned self-sensing material. The application of the proposed electrical measurement technique appears promising for real-time utilization of self-sensing materials in structural health monitoring.

Improved l1-SPIRiT using 3D walsh transform-based sparsity basis.

PubMed

Feng, Zhen; Liu, Feng; Jiang, Mingfeng; Crozier, Stuart; Guo, He; Wang, Yuxin

2014-09-01

l1-SPIRiT is a fast magnetic resonance imaging (MRI) method which combines parallel imaging (PI) with compressed sensing (CS) by performing a joint l1-norm and l2-norm optimization procedure. The original l1-SPIRiT method uses two-dimensional (2D) Wavelet transform to exploit the intra-coil data redundancies and a joint sparsity model to exploit the inter-coil data redundancies. In this work, we propose to stack all the coil images into a three-dimensional (3D) matrix, and then a novel 3D Walsh transform-based sparsity basis is applied to simultaneously reduce the intra-coil and inter-coil data redundancies. Both the 2D Wavelet transform-based and the proposed 3D Walsh transform-based sparsity bases were investigated in the l1-SPIRiT method. The experimental results show that the proposed 3D Walsh transform-based l1-SPIRiT method outperformed the original l1-SPIRiT in terms of image quality and computational efficiency. Copyright © 2014 Elsevier Inc. All rights reserved.

Super-resolved Parallel MRI by Spatiotemporal Encoding

PubMed Central

Schmidt, Rita; Baishya, Bikash; Ben-Eliezer, Noam; Seginer, Amir; Frydman, Lucio

2016-01-01

Recent studies described an alternative “ultrafast” scanning method based on spatiotemporal (SPEN) principles. SPEN demonstrates numerous potential advantages over EPI-based alternatives, at no additional expense in experimental complexity. An important aspect that SPEN still needs to achieve for providing a competitive acquisition alternative entails exploiting parallel imaging algorithms, without compromising its proven capabilities. The present work introduces a combination of multi-band frequency-swept pulses simultaneously encoding multiple, partial fields-of-view; together with a new algorithm merging a Super-Resolved SPEN image reconstruction and SENSE multiple-receiving methods. The ensuing approach enables one to reduce both the excitation and acquisition times of ultrafast SPEN acquisitions by the customary acceleration factor R, without compromises in either the ensuing spatial resolution, SAR deposition, or the capability to operate in multi-slice mode. The performance of these new single-shot imaging sequences and their ancillary algorithms were explored on phantoms and human volunteers at 3T. The gains of the parallelized approach were particularly evident when dealing with heterogeneous systems subject to major T2/T2* effects, as is the case upon single-scan imaging near tissue/air interfaces. PMID:24120293

Target detection method by airborne and spaceborne images fusion based on past images

NASA Astrophysics Data System (ADS)

Chen, Shanjing; Kang, Qing; Wang, Zhenggang; Shen, ZhiQiang; Pu, Huan; Han, Hao; Gu, Zhongzheng

2017-11-01

To solve the problem that remote sensing target detection method has low utilization rate of past remote sensing data on target area, and can not recognize camouflage target accurately, a target detection method by airborne and spaceborne images fusion based on past images is proposed in this paper. The target area's past of space remote sensing image is taken as background. The airborne and spaceborne remote sensing data is fused and target feature is extracted by the means of airborne and spaceborne images registration, target change feature extraction, background noise suppression and artificial target feature extraction based on real-time aerial optical remote sensing image. Finally, the support vector machine is used to detect and recognize the target on feature fusion data. The experimental results have established that the proposed method combines the target area change feature of airborne and spaceborne remote sensing images with target detection algorithm, and obtains fine detection and recognition effect on camouflage and non-camouflage targets.

Blind compressed sensing image reconstruction based on alternating direction method

NASA Astrophysics Data System (ADS)

Liu, Qinan; Guo, Shuxu

2018-04-01

In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.

Image quality enhancement in low-light-level ghost imaging using modified compressive sensing method

NASA Astrophysics Data System (ADS)

Shi, Xiaohui; Huang, Xianwei; Nan, Suqin; Li, Hengxing; Bai, Yanfeng; Fu, Xiquan

2018-04-01

Detector noise has a significantly negative impact on ghost imaging at low light levels, especially for existing recovery algorithm. Based on the characteristics of the additive detector noise, a method named modified compressive sensing ghost imaging is proposed to reduce the background imposed by the randomly distributed detector noise at signal path. Experimental results show that, with an appropriate choice of threshold value, modified compressive sensing ghost imaging algorithm can dramatically enhance the contrast-to-noise ratio of the object reconstruction significantly compared with traditional ghost imaging and compressive sensing ghost imaging methods. The relationship between the contrast-to-noise ratio of the reconstruction image and the intensity ratio (namely, the average signal intensity to average noise intensity ratio) for the three reconstruction algorithms are also discussed. This noise suppression imaging technique will have great applications in remote-sensing and security areas.

Development of a UAV system for VNIR-TIR acquisitions in precision agriculture

NASA Astrophysics Data System (ADS)

Misopolinos, L.; Zalidis, Ch.; Liakopoulos, V.; Stavridou, D.; Katsigiannis, P.; Alexandridis, T. K.; Zalidis, G.

2015-06-01

Adoption of precision agriculture techniques requires the development of specialized tools that provide spatially distributed information. Both flying platforms and airborne sensors are being continuously evolved to cover the needs of plant and soil sensing at affordable costs. Due to restrictions in payload, flying platforms are usually limited to carry a single sensor on board. The aim of this work is to present the development of a vertical take-off and landing autonomous unmanned aerial vehicle (VTOL UAV) system for the simultaneous acquisition of high resolution vertical images at the visible, near infrared (VNIR) and thermal infrared (TIR) wavelengths. A system was developed that has the ability to trigger two cameras simultaneously with a fully automated process and no pilot intervention. A commercial unmanned hexacopter UAV platform was optimized to increase reliability, ease of operation and automation. The designed systems communication platform is based on a reduced instruction set computing (RISC) processor running Linux OS with custom developed drivers in an efficient way, while keeping the cost and weight to a minimum. Special software was also developed for the automated image capture, data processing and on board data and metadata storage. The system was tested over a kiwifruit field in northern Greece, at flying heights of 70 and 100m above the ground. The acquired images were mosaicked and geo-corrected. Images from both flying heights were of good quality and revealed unprecedented detail within the field. The normalized difference vegetation index (NDVI) was calculated along with the thermal image in order to provide information on the accurate location of stressors and other parameters related to the crop productivity. Compared to other available sources of data, this system can provide low cost, high resolution and easily repeatable information to cover the requirements of precision agriculture.

A New Joint-Blade SENSE Reconstruction for Accelerated PROPELLER MRI

PubMed Central

Lyu, Mengye; Liu, Yilong; Xie, Victor B.; Feng, Yanqiu; Guo, Hua; Wu, Ed X.

2017-01-01

PROPELLER technique is widely used in MRI examinations for being motion insensitive, but it prolongs scan time and is restricted mainly to T2 contrast. Parallel imaging can accelerate PROPELLER and enable more flexible contrasts. Here, we propose a multi-step joint-blade (MJB) SENSE reconstruction to reduce the noise amplification in parallel imaging accelerated PROPELLER. MJB SENSE utilizes the fact that PROPELLER blades contain sharable information and blade-combined images can serve as regularization references. It consists of three steps. First, conventional blade-combined images are obtained using the conventional simple single-blade (SSB) SENSE, which reconstructs each blade separately. Second, the blade-combined images are employed as regularization for blade-wise noise reduction. Last, with virtual high-frequency data resampled from the previous step, all blades are jointly reconstructed to form the final images. Simulations were performed to evaluate the proposed MJB SENSE for noise reduction and motion correction. MJB SENSE was also applied to both T2-weighted and T1-weighted in vivo brain data. Compared to SSB SENSE, MJB SENSE greatly reduced the noise amplification at various acceleration factors, leading to increased image SNR in all simulation and in vivo experiments, including T1-weighted imaging with short echo trains. Furthermore, it preserved motion correction capability and was computationally efficient. PMID:28205602

A New Joint-Blade SENSE Reconstruction for Accelerated PROPELLER MRI.

PubMed

Lyu, Mengye; Liu, Yilong; Xie, Victor B; Feng, Yanqiu; Guo, Hua; Wu, Ed X

2017-02-16

PROPELLER technique is widely used in MRI examinations for being motion insensitive, but it prolongs scan time and is restricted mainly to T2 contrast. Parallel imaging can accelerate PROPELLER and enable more flexible contrasts. Here, we propose a multi-step joint-blade (MJB) SENSE reconstruction to reduce the noise amplification in parallel imaging accelerated PROPELLER. MJB SENSE utilizes the fact that PROPELLER blades contain sharable information and blade-combined images can serve as regularization references. It consists of three steps. First, conventional blade-combined images are obtained using the conventional simple single-blade (SSB) SENSE, which reconstructs each blade separately. Second, the blade-combined images are employed as regularization for blade-wise noise reduction. Last, with virtual high-frequency data resampled from the previous step, all blades are jointly reconstructed to form the final images. Simulations were performed to evaluate the proposed MJB SENSE for noise reduction and motion correction. MJB SENSE was also applied to both T2-weighted and T1-weighted in vivo brain data. Compared to SSB SENSE, MJB SENSE greatly reduced the noise amplification at various acceleration factors, leading to increased image SNR in all simulation and in vivo experiments, including T1-weighted imaging with short echo trains. Furthermore, it preserved motion correction capability and was computationally efficient.

Molecular imaging and sensing using plasmonic nanoparticles

NASA Astrophysics Data System (ADS)

Crow, Matthew James

Noble metal nanoparticles exhibit unique optical properties that are beneficial to a variety of applications, including molecular imaging. The large scattering cross sections of nanoparticles provide high contrast necessary for biomarkers. Unlike alternative contrast agents, nanoparticles provide refractive index sensitivity revealing information regarding the local cellular environment. Altering the shape and composition of the nanoparticle shifts the peak resonant wavelength of scattered light, allowing for implementation of multiple spectrally distinct tags. In this project, nanoparticles that scatter in different spectral windows are functionalized with various antibodies recognizing extra-cellular receptors integral to cancer progression. A hyperspectral imaging system is developed, allowing for visualization and spectral characterization of cells labeled with these conjugates. Various molecular imaging and microspectroscopy applications of plasmonic nanoparticles are then investigated. First, anti-EGFR gold nanospheres are shown to quantitatively measure receptor expression with similar performance to fluorescence assays. Second, anti-EGFR gold nanorods and novel anti-IGF-1R silver nanospheres are implemented to indicate local cellular refractive indices. Third, because biosensing capabilities of nanoparticle tags may be limited by plasmonic coupling, polarization mapping is investigated as a method to discern these effects. Fourth, plasmonic coupling is tested to monitor HER-2 dimerization. Experiments reveal the interparticle conformation of proximal HER-2 bound labels, required for plasmonic coupling-enhanced dielectric sensing. Fifth, all three functionalized plasmonic tags are implemented simultaneously to indicate clinically relevant cell immunophenotype information and changes in the cellular dielectric environment. Finally, flow cytometry experiments are conducted utilizing the anti-EGFR nanorod tag to demonstrate profiling of receptor expression distribution and potential increased multiplexing capability.

Tools and Methods for the Registration and Fusion of Remotely Sensed Data

NASA Technical Reports Server (NTRS)

Goshtasby, Arthur Ardeshir; LeMoigne, Jacqueline

2010-01-01

Tools and methods for image registration were reviewed. Methods for the registration of remotely sensed data at NASA were discussed. Image fusion techniques were reviewed. Challenges in registration of remotely sensed data were discussed. Examples of image registration and image fusion were given.

Near-field Oblique Remote Sensing of Stream Water-surface Elevation, Slope, and Surface Velocity

NASA Astrophysics Data System (ADS)

Minear, J. T.; Kinzel, P. J.; Nelson, J. M.; McDonald, R.; Wright, S. A.

2014-12-01

A major challenge for estimating discharges during flood events or in steep channels is the difficulty and hazard inherent in obtaining in-stream measurements. One possible solution is to use near-field remote sensing to obtain simultaneous water-surface elevations, slope, and surface velocities. In this test case, we utilized Terrestrial Laser Scanning (TLS) to remotely measure water-surface elevations and slope in combination with surface velocities estimated from particle image velocimetry (PIV) obtained by video-camera and/or infrared camera. We tested this method at several sites in New Mexico and Colorado using independent validation data consisting of in-channel measurements from survey-grade GPS and Acoustic Doppler Current Profiler (ADCP) instruments. Preliminary results indicate that for relatively turbid or steep streams, TLS collects tens of thousands of water-surface elevations and slopes in minutes, much faster than conventional means and at relatively high precision, at least as good as continuous survey-grade GPS measurements. Estimated surface velocities from this technique are within 15% of measured velocity magnitudes and within 10 degrees from the measured velocity direction (using extrapolation from the shallowest bin of the ADCP measurements). Accurately aligning the PIV results into Cartesian coordinates appears to be one of the main sources of error, primarily due to the sensitivity at these shallow oblique look angles and the low numbers of stationary objects for rectification. Combining remotely-sensed water-surface elevations, slope, and surface velocities produces simultaneous velocity measurements from a large number of locations in the channel and is more spatially extensive than traditional velocity measurements. These factors make this technique useful for improving estimates of flow measurements during flood flows and in steep channels while also decreasing the difficulty and hazard associated with making measurements in these conditions.

A compressive-sensing Fourier-transform on-chip Raman spectrometer

NASA Astrophysics Data System (ADS)

Podmore, Hugh; Scott, Alan; Lee, Regina

2018-02-01

We demonstrate a novel compressive sensing Fourier-transform spectrometer (FTS) for snapshot Raman spectroscopy in a compact format. The on-chip FTS consists of a set of planar-waveguide Mach-Zehnder interferometers (MZIs) arrayed on a photonic chip, effecting a discrete Fourier-transform of the input spectrum. Incoherence between the sampling domain (time), and the spectral domain (frequency) permits compressive sensing retrieval using undersampled interferograms for sparse spectra such as Raman emission. In our fabricated device we retain our chosen bandwidth and resolution while reducing the number of MZIs, e.g. the size of the interferogram, to 1/4th critical sampling. This architecture simultaneously reduces chip footprint and concentrates the interferogram in fewer pixels to improve the signal to noise ratio. Our device collects interferogram samples simultaneously, therefore a time-gated detector may be used to separate Raman peaks from sample fluorescence. A challenge for FTS waveguide spectrometers is to achieve multi-aperture high throughput broadband coupling to a large number of single-mode waveguides. A multi-aperture design allows one to increase the bandwidth and spectral resolution without sacrificing optical throughput. In this device, multi-aperture coupling is achieved using an array of microlenses bonded to the surface of the chip, and aligned with a grid of vertically illuminated waveguide apertures. The microlens array accepts a collimated beam with near 100% fill-factor, and the resulting spherical wavefronts are coupled into the single-mode waveguides using 45& mirrors etched into the waveguide layer via focused ion-beam (FIB). The interferogram from the waveguide outputs is imaged using a CCD, and inverted via l1-norm minimization to correctly retrieve a sparse input spectrum.

Remote sensing image segmentation based on Hadoop cloud platform

NASA Astrophysics Data System (ADS)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

Global-scale Observations of the Limb and Disk (GOLD) Mission - A New Approach to Ultraviolet Remote Sensing of Earth's Space Environment

NASA Astrophysics Data System (ADS)

Eastes, R.; McClintock, W. E.; Anderson, D. N.; Andersson, L.; Burns, A. G.; Codrescu, M.; Daniell, R. E.; England, S.; Krywonos, A.; Lumpe, J. D.; Richmond, A. D.; Rusch, D. W.; Siegmund, O.; Solomon, S. C.; Strickland, D. J.; Woods, T. N.; Budzien, S. A.; Dymond, K.; Eparvier, F. G.; Jones, S.; Martinis, C. R.; Oberheide, J.; Talaat, E. R.; Barrett, R.; Harvey, J.

2016-12-01

The GOLD mission of opportunity will fly a far ultraviolet imaging spectrograph in geostationary (GEO) orbit as a hosted payload. The mission is scheduled for launch in late 2017 on SES-14, a commercial communications satellite that will be stationed over eastern South America at 47.5 degrees west longitude. GOLD is on schedule to be the first NASA science mission to fly as a hosted payload on a commercial communications satellite. The GOLD imager has two identical channels. Each channel can scan the full disk at a 30 minute cadence, making spectral images of Earth's UV emission from 132 to 162 nm, as well as make a measurement on the Earth's limb. Remote sensing techniques that have been proven on previous Low Earth Orbit (LEO) missions will be used to derive fundamental parameters for the neutral and ionized space environment. Parameters that will be derived include composition (O/N2 ratio) and temperature of the neutral atmosphere on the dayside disk. On the nightside, peak electron densities will be obtained in the low latitude ionosphere. Similar imaging of atmospheric composition from LEO, at only a daily cadence for revisiting locations, has already provided many new insights into the behavior of Earth's Thermosphere-Ionosphere (T-I) system. From geostationary orbit, GOLD can repeatedly image the same geographic locations over most of the hemisphere at a cadence comparable to that of the T-I system (order of an hour). Such time resolution and spatial coverage will allow the mission to track the changes due to geomagnetic storms, variations in solar extreme ultraviolet radiation, and forcing from the lower atmosphere. In addition to providing a new perspective by being able to repeatedly remotely sense the same hemisphere at a high cadence, GOLD's simultaneous measurements of not only composition but also temperatures across the disk will provide a valuable, new parameter for understanding of how the T-I system responds to forcing from the sun and the lower atmosphere.

Investigating the limits of filopodial sensing: a brief report using SEM to image the interaction between 10 nm high nano-topography and fibroblast filopodia.

PubMed

Dalby, M J; Riehle, M O; Johnstone, H; Affrossman, S; Curtis, A S G

2004-01-01

Having the ability to control cell behaviour would be of great advantage in tissue engineering. One method of gaining control over cell adhesion, proliferation, guidance and differentiation is use of topography. Whilst it has be known for some time that cells can be guided by micro-topography, it is only recently becoming clear that cells will respond strongly to nano-scale topography. The fact that cells will take cues from their micro- and nano-environment suggests that the cells are in some way 'spatially aware'. It is likely that cells probe the shape of their surroundings using filopodia, and that this initial filopodia/topography interaction may be critical to down-stream cell reactions to biomaterials, or indeed, the extracellular matrix. One intriguing question is how small a feature can cells sense? In order to investigate the limits of cell sensing, high-resolution scanning electron microscopy has been used to simultaneously view cell filopodia and 10 nm high nano-islands. Fluorescence microscopy has also been used to look at adhesion formation. The results showed distinct filopodial/nano-island interaction and changes in adhesion morphology.

Whole left ventricular functional assessment from two minutes free breathing multi-slice CINE acquisition

NASA Astrophysics Data System (ADS)

Usman, M.; Atkinson, D.; Heathfield, E.; Greil, G.; Schaeffter, T.; Prieto, C.

2015-04-01

Two major challenges in cardiovascular MRI are long scan times due to slow MR acquisition and motion artefacts due to respiratory motion. Recently, a Motion Corrected-Compressed Sensing (MC-CS) technique has been proposed for free breathing 2D dynamic cardiac MRI that addresses these challenges by simultaneously accelerating MR acquisition and correcting for any arbitrary motion in a compressed sensing reconstruction. In this work, the MC-CS framework is combined with parallel imaging for further acceleration, and is termed Motion Corrected Sparse SENSE (MC-SS). Validation of the MC-SS framework is demonstrated in eight volunteers and three patients for left ventricular functional assessment and results are compared with the breath-hold acquisitions as reference. A non-significant difference (P > 0.05) was observed in the volumetric functional measurements (end diastolic volume, end systolic volume, ejection fraction) and myocardial border sharpness values obtained with the proposed and gold standard methods. The proposed method achieves whole heart multi-slice coverage in 2 min under free breathing acquisition eliminating the time needed between breath-holds for instructions and recovery. This results in two-fold speed up of the total acquisition time in comparison to the breath-hold acquisition.

Efficient Imaging and Real-Time Display of Scanning Ion Conductance Microscopy Based on Block Compressive Sensing

NASA Astrophysics Data System (ADS)

Li, Gongxin; Li, Peng; Wang, Yuechao; Wang, Wenxue; Xi, Ning; Liu, Lianqing

2014-07-01

Scanning Ion Conductance Microscopy (SICM) is one kind of Scanning Probe Microscopies (SPMs), and it is widely used in imaging soft samples for many distinctive advantages. However, the scanning speed of SICM is much slower than other SPMs. Compressive sensing (CS) could improve scanning speed tremendously by breaking through the Shannon sampling theorem, but it still requires too much time in image reconstruction. Block compressive sensing can be applied to SICM imaging to further reduce the reconstruction time of sparse signals, and it has another unique application that it can achieve the function of image real-time display in SICM imaging. In this article, a new method of dividing blocks and a new matrix arithmetic operation were proposed to build the block compressive sensing model, and several experiments were carried out to verify the superiority of block compressive sensing in reducing imaging time and real-time display in SICM imaging.

Objected-oriented remote sensing image classification method based on geographic ontology model

NASA Astrophysics Data System (ADS)

Chu, Z.; Liu, Z. J.; Gu, H. Y.

2016-11-01

Nowadays, with the development of high resolution remote sensing image and the wide application of laser point cloud data, proceeding objected-oriented remote sensing classification based on the characteristic knowledge of multi-source spatial data has been an important trend on the field of remote sensing image classification, which gradually replaced the traditional method through improving algorithm to optimize image classification results. For this purpose, the paper puts forward a remote sensing image classification method that uses the he characteristic knowledge of multi-source spatial data to build the geographic ontology semantic network model, and carries out the objected-oriented classification experiment to implement urban features classification, the experiment uses protégé software which is developed by Stanford University in the United States, and intelligent image analysis software—eCognition software as the experiment platform, uses hyperspectral image and Lidar data that is obtained through flight in DaFeng City of JiangSu as the main data source, first of all, the experiment uses hyperspectral image to obtain feature knowledge of remote sensing image and related special index, the second, the experiment uses Lidar data to generate nDSM(Normalized DSM, Normalized Digital Surface Model),obtaining elevation information, the last, the experiment bases image feature knowledge, special index and elevation information to build the geographic ontology semantic network model that implement urban features classification, the experiment results show that, this method is significantly higher than the traditional classification algorithm on classification accuracy, especially it performs more evidently on the respect of building classification. The method not only considers the advantage of multi-source spatial data, for example, remote sensing image, Lidar data and so on, but also realizes multi-source spatial data knowledge integration and application of the knowledge to the field of remote sensing image classification, which provides an effective way for objected-oriented remote sensing image classification in the future.

A NDVI assisted remote sensing image adaptive scale segmentation method

NASA Astrophysics Data System (ADS)

Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

2018-03-01

Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

Practical human abdominal fat imaging utilizing electrical impedance tomography.

PubMed

Yamaguchi, T; Maki, K; Katashima, M

2010-07-01

The fundamental cause of metabolic syndrome is thought to be abdominal obesity. Accurate diagnosis of abdominal obesity can be done by an x-ray computed tomography (CT) scan. But CT is expensive, bulky and entails the risks involved with radiation. To overcome such disadvantages, we attempted to develop a measuring device that could apply electrical impedance tomography to abdominal fat imaging. The device has 32 electrodes that can be attached to a subject's abdomen by a pneumatic mechanism. That way, electrode position data can be acquired simultaneously. An applied alternating current of 1.0 mArms was used at a frequency of 500 kHz. Sensed voltage data were carefully filtered to remove noise and processed to satisfy the reciprocal theorem. The image reconstruction software was developed concurrently, applying standard finite element methods and the Marquardt method to solve the mathematical inverse problem. The results of preliminary experiments showed that abdominal subcutaneous fat and the muscle surrounding the viscera could be imaged in humans. While our imaging of visceral fat was not of sufficient quality, it was suggested that we will be able to develop a safe and practical abdominal fat scanner through future improvements.

Computational imaging with a balanced detector.

PubMed

Soldevila, F; Clemente, P; Tajahuerce, E; Uribe-Patarroyo, N; Andrés, P; Lancis, J

2016-06-29

Single-pixel cameras allow to obtain images in a wide range of challenging scenarios, including broad regions of the electromagnetic spectrum and through scattering media. However, there still exist several drawbacks that single-pixel architectures must address, such as acquisition speed and imaging in the presence of ambient light. In this work we introduce balanced detection in combination with simultaneous complementary illumination in a single-pixel camera. This approach enables to acquire information even when the power of the parasite signal is higher than the signal itself. Furthermore, this novel detection scheme increases both the frame rate and the signal-to-noise ratio of the system. By means of a fast digital micromirror device together with a low numerical aperture collecting system, we are able to produce a live-feed video with a resolution of 64 × 64 pixels at 5 Hz. With advanced undersampling techniques, such as compressive sensing, we can acquire information at rates of 25 Hz. By using this strategy, we foresee real-time biological imaging with large area detectors in conditions where array sensors are unable to operate properly, such as infrared imaging and dealing with objects embedded in turbid media.

Computational imaging with a balanced detector

NASA Astrophysics Data System (ADS)

Soldevila, F.; Clemente, P.; Tajahuerce, E.; Uribe-Patarroyo, N.; Andrés, P.; Lancis, J.

2016-06-01

Single-pixel cameras allow to obtain images in a wide range of challenging scenarios, including broad regions of the electromagnetic spectrum and through scattering media. However, there still exist several drawbacks that single-pixel architectures must address, such as acquisition speed and imaging in the presence of ambient light. In this work we introduce balanced detection in combination with simultaneous complementary illumination in a single-pixel camera. This approach enables to acquire information even when the power of the parasite signal is higher than the signal itself. Furthermore, this novel detection scheme increases both the frame rate and the signal-to-noise ratio of the system. By means of a fast digital micromirror device together with a low numerical aperture collecting system, we are able to produce a live-feed video with a resolution of 64 × 64 pixels at 5 Hz. With advanced undersampling techniques, such as compressive sensing, we can acquire information at rates of 25 Hz. By using this strategy, we foresee real-time biological imaging with large area detectors in conditions where array sensors are unable to operate properly, such as infrared imaging and dealing with objects embedded in turbid media.

Visualizing photosynthesis through processing of chlorophyll fluorescence images

NASA Astrophysics Data System (ADS)

Daley, Paul F.; Ball, J. Timothy; Berry, Joseph A.; Patzke, Juergen; Raschke, Klaus E.

1990-05-01

Measurements of terrestrial plant photosynthesis frequently exploit sensing of gas exchange from leaves enclosed in gas-tight, climate controlled chambers. These methods are typically slow, and do not resolve variation in photosynthesis below the whole leaf level. A photosynthesis visualization technique is presented that uses images of leaves employing light from chlorophyll (Chl) fluorescence. Images of Chl fluorescence from whole leaves undergoing steady-state photosynthesis, photosynthesis induction, or response to stress agents were digitized during light flashes that saturated photochemical reactions. Use of saturating flashes permitted deconvolution of photochemical energy use from biochemical quenching mechanisms (qN) that dissipate excess excitation energy, otherwise damaging to the light harvesting apparatus. Combination of the digital image frames of variable fluorescence with reference frames obtained from the same leaves when dark-adapted permitted derivation of frames in which grey scale represented the magnitude of qN. Simultaneous measurements with gas-exchange apparatus provided data for non-linear calibration filters for subsequent rendering of grey-scale "images" of photosynthesis. In several experiments significant non-homogeneity of photosynthetic activity was observed following treatment with growth hormones, or shifts in light or humidity, and following infection by virus. The technique provides a rapid, non-invasive probe for stress physiology and plant disease detection.

Computational imaging with a balanced detector

PubMed Central

Soldevila, F.; Clemente, P.; Tajahuerce, E.; Uribe-Patarroyo, N.; Andrés, P.; Lancis, J.

2016-01-01

Single-pixel cameras allow to obtain images in a wide range of challenging scenarios, including broad regions of the electromagnetic spectrum and through scattering media. However, there still exist several drawbacks that single-pixel architectures must address, such as acquisition speed and imaging in the presence of ambient light. In this work we introduce balanced detection in combination with simultaneous complementary illumination in a single-pixel camera. This approach enables to acquire information even when the power of the parasite signal is higher than the signal itself. Furthermore, this novel detection scheme increases both the frame rate and the signal-to-noise ratio of the system. By means of a fast digital micromirror device together with a low numerical aperture collecting system, we are able to produce a live-feed video with a resolution of 64 × 64 pixels at 5 Hz. With advanced undersampling techniques, such as compressive sensing, we can acquire information at rates of 25 Hz. By using this strategy, we foresee real-time biological imaging with large area detectors in conditions where array sensors are unable to operate properly, such as infrared imaging and dealing with objects embedded in turbid media. PMID:27353733

Remote Sensing: Analyzing Satellite Images to Create Higher Order Thinking Skills.

ERIC Educational Resources Information Center

Marks, Steven K.; And Others

1996-01-01

Presents a unit that uses remote-sensing images from satellites and other spacecraft to provide new perspectives of the earth and generate greater global awareness. Relates the levels of Bloom's hierarchy to different aspects of the remote sensing unit to confirm that the concepts and principles of remote sensing and related images belong in…

Superresolution parallel magnetic resonance imaging: Application to functional and spectroscopic imaging

PubMed Central

Otazo, Ricardo; Lin, Fa-Hsuan; Wiggins, Graham; Jordan, Ramiro; Sodickson, Daniel; Posse, Stefan

2009-01-01

Standard parallel magnetic resonance imaging (MRI) techniques suffer from residual aliasing artifacts when the coil sensitivities vary within the image voxel. In this work, a parallel MRI approach known as Superresolution SENSE (SURE-SENSE) is presented in which acceleration is performed by acquiring only the central region of k-space instead of increasing the sampling distance over the complete k-space matrix and reconstruction is explicitly based on intra-voxel coil sensitivity variation. In SURE-SENSE, parallel MRI reconstruction is formulated as a superresolution imaging problem where a collection of low resolution images acquired with multiple receiver coils are combined into a single image with higher spatial resolution using coil sensitivities acquired with high spatial resolution. The effective acceleration of conventional gradient encoding is given by the gain in spatial resolution, which is dictated by the degree of variation of the different coil sensitivity profiles within the low resolution image voxel. Since SURE-SENSE is an ill-posed inverse problem, Tikhonov regularization is employed to control noise amplification. Unlike standard SENSE, for which acceleration is constrained to the phase-encoding dimension/s, SURE-SENSE allows acceleration along all encoding directions — for example, two-dimensional acceleration of a 2D echo-planar acquisition. SURE-SENSE is particularly suitable for low spatial resolution imaging modalities such as spectroscopic imaging and functional imaging with high temporal resolution. Application to echo-planar functional and spectroscopic imaging in human brain is presented using two-dimensional acceleration with a 32-channel receiver coil. PMID:19341804

Band-Moment Compression of AVIRIS Hyperspectral Data and its Use in the Detection of Vegetation Stress

NASA Technical Reports Server (NTRS)

Estep, L.; Davis, B.

2001-01-01

A remote sensing campaign was conducted over a U.S. Department of Agriculture test farm at Shelton, Nebraska. An experimental field was set off in plots that were differentially treated with anhydrous ammonia. Four replicates of 0-kg/ha to 200-kg/ha plots, in 50-kg/ha increments, were set out in a random block design. Low-altitude (GSD of 3 m) Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral data were collected over the site in 224 bands. Simultaneously, ground data were collected to support the airborne imagery. In an effort to reduce data load while maintaining or enhancing algorithm performance for vegetation stress detection, band-moment compression and analysis was applied to the AVIRIS image cube. The results indicated that band-moment techniques compress the AVIRIS dataset significantly while retaining the capability of detecting environmentally induced vegetation stress.

Energy-Discriminative Performance of a Spectral Micro-CT System

PubMed Central

He, Peng; Yu, Hengyong; Bennett, James; Ronaldson, Paul; Zainon, Rafidah; Butler, Anthony; Butler, Phil; Wei, Biao; Wang, Ge

2013-01-01

Experiments were performed to evaluate the energy-discriminative performance of a spectral (multi-energy) micro-CT system. The system, designed by MARS (Medipix All Resolution System) Bio-Imaging Ltd. (Christchurch, New Zealand), employs a photon-counting energy-discriminative detector technology developed by CERN (European Organization for Nuclear Research). We used the K-edge attenuation characteristic of some known materials to calibrate the detector’s photon energy discrimination. For tomographic analysis, we used the compressed sensing (CS) based ordered-subset simultaneous algebraic reconstruction techniques (OS-SART) to reconstruct sample images, which is effective to reduce noise and suppress artifacts. Unlike conventional CT, the principal component analysis (PCA) method can be applied to extract and quantify additional attenuation information from a spectral CT dataset. Our results show that the spectral CT has a good energy-discriminative performance and provides more attenuation information than the conventional CT. PMID:24004864

Accurate estimation of motion blur parameters in noisy remote sensing image

NASA Astrophysics Data System (ADS)

Shi, Xueyan; Wang, Lin; Shao, Xiaopeng; Wang, Huilin; Tao, Zhong

2015-05-01

The relative motion between remote sensing satellite sensor and objects is one of the most common reasons for remote sensing image degradation. It seriously weakens image data interpretation and information extraction. In practice, point spread function (PSF) should be estimated firstly for image restoration. Identifying motion blur direction and length accurately is very crucial for PSF and restoring image with precision. In general, the regular light-and-dark stripes in the spectrum can be employed to obtain the parameters by using Radon transform. However, serious noise existing in actual remote sensing images often causes the stripes unobvious. The parameters would be difficult to calculate and the error of the result relatively big. In this paper, an improved motion blur parameter identification method to noisy remote sensing image is proposed to solve this problem. The spectrum characteristic of noisy remote sensing image is analyzed firstly. An interactive image segmentation method based on graph theory called GrabCut is adopted to effectively extract the edge of the light center in the spectrum. Motion blur direction is estimated by applying Radon transform on the segmentation result. In order to reduce random error, a method based on whole column statistics is used during calculating blur length. Finally, Lucy-Richardson algorithm is applied to restore the remote sensing images of the moon after estimating blur parameters. The experimental results verify the effectiveness and robustness of our algorithm.

A battery-less photo-detector enabled with simultaneous ferroelectric sensing and energy harnessing mechanism

NASA Astrophysics Data System (ADS)

Lai, Szu Cheng; Yao, Kui; Chen, Yi Fan

2013-08-01

A self-sustainable mechanism for simultaneously sensing and harnessing photon energy was proposed and implemented to create a battery-less and wire-less ultraviolet sensor made of ferroelectric lead lanthanum zirconate titanate thin film with in-plane polarization configuration. The mechanism involved accumulating and storing the photovoltaic charge, and transferring the stored charge via a piezoelectric switch to a radio frequency transmitter. The time-interval between the radio frequency pulses generated by the transmitter was inversely proportional to the photo-intensity. The sustainability of the operation was ascribed to the low leakage, high photovoltage, and linear current-voltage characteristics of ferroelectric sensing material instead of semiconductors.

Chirped fiber Bragg grating written in highly birefringent fiber in simultaneous strain and temperature monitoring.

PubMed

Bieda, Marcin S; Sobotka, Piotr; Woliński, Tomasz R

2017-02-20

A new sensor configuration is proposed for simultaneous strain and temperature monitoring in a composite material that is based on a chirped fiber Bragg grating (CFBG) written in a highly birefringent (HB) polarization-maintaining fiber. The sensor is designed in the reflective configuration in which the CFBG acts both as a reflector and a sensing element. Since CFBG and HB fiber induce changes in the state of polarization (SOP), interference between polarization modes in the reflected spectrum is observed and analyzed. We used a simple readout setup to enable fast, linear operation of strain sensing as well simultaneous strain and temperature measurements in the composite.

Linear high-boost fusion of Stokes vector imagery for effective discrimination and recognition of real targets in the presence of multiple identical decoys

NASA Astrophysics Data System (ADS)

El-Saba, Aed; Sakla, Wesam A.

2010-04-01

Recently, the use of imaging polarimetry has received considerable attention for use in automatic target recognition (ATR) applications. In military remote sensing applications, there is a great demand for sensors that are capable of discriminating between real targets and decoys. Accurate discrimination of decoys from real targets is a challenging task and often requires the fusion of various sensor modalities that operate simultaneously. In this paper, we use a simple linear fusion technique known as the high-boost fusion method for effective discrimination of real targets in the presence of multiple decoys. The HBF assigns more weight to the polarization-based imagery in forming the final fused image that is used for detection. We have captured both intensity and polarization-based imagery from an experimental laboratory arrangement containing a mixture of sand/dirt, rocks, vegetation, and other objects for the purpose of simulating scenery that would be acquired in a remote sensing military application. A target object and three decoys that are identical in physical appearance (shape, surface structure and color) and different in material composition have also been placed in the scene. We use the wavelet-filter joint transform correlation (WFJTC) technique to perform detection between input scenery and the target object. Our results show that use of the HBF method increases the correlation performance metrics associated with the WFJTC-based detection process when compared to using either the traditional intensity or polarization-based images.

Restoration of color in a remote sensing image and its quality evaluation

NASA Astrophysics Data System (ADS)

Zhang, Zuxun; Li, Zhijiang; Zhang, Jianqing; Wang, Zhihe

2003-09-01

This paper is focused on the restoration of color remote sensing (including airborne photo). A complete approach is recommended. It propose that two main aspects should be concerned in restoring a remote sensing image, that are restoration of space information, restoration of photometric information. In this proposal, the restoration of space information can be performed by making the modulation transfer function (MTF) as degradation function, in which the MTF is obtained by measuring the edge curve of origin image. The restoration of photometric information can be performed by improved local maximum entropy algorithm. What's more, a valid approach in processing color remote sensing image is recommended. That is splits the color remote sensing image into three monochromatic images which corresponding three visible light bands and synthesizes the three images after being processed separately with psychological color vision restriction. Finally, three novel evaluation variables are obtained based on image restoration to evaluate the image restoration quality in space restoration quality and photometric restoration quality. An evaluation is provided at last.

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.

Integrating dynamic and distributed compressive sensing techniques to enhance image quality of the compressive line sensing system for unmanned aerial vehicles application

NASA Astrophysics Data System (ADS)

Ouyang, Bing; Hou, Weilin; Caimi, Frank M.; Dalgleish, Fraser R.; Vuorenkoski, Anni K.; Gong, Cuiling

2017-07-01

The compressive line sensing imaging system adopts distributed compressive sensing (CS) to acquire data and reconstruct images. Dynamic CS uses Bayesian inference to capture the correlated nature of the adjacent lines. An image reconstruction technique that incorporates dynamic CS in the distributed CS framework was developed to improve the quality of reconstructed images. The effectiveness of the technique was validated using experimental data acquired in an underwater imaging test facility. Results that demonstrate contrast and resolution improvements will be presented. The improved efficiency is desirable for unmanned aerial vehicles conducting long-duration missions.

Split Bregman's optimization method for image construction in compressive sensing

NASA Astrophysics Data System (ADS)

Skinner, D.; Foo, S.; Meyer-Bäse, A.

2014-05-01

The theory of compressive sampling (CS) was reintroduced by Candes, Romberg and Tao, and D. Donoho in 2006. Using a priori knowledge that a signal is sparse, it has been mathematically proven that CS can defY Nyquist sampling theorem. Theoretically, reconstruction of a CS image relies on the minimization and optimization techniques to solve this complex almost NP-complete problem. There are many paths to consider when compressing and reconstructing an image but these methods have remained untested and unclear on natural images, such as underwater sonar images. The goal of this research is to perfectly reconstruct the original sonar image from a sparse signal while maintaining pertinent information, such as mine-like object, in Side-scan sonar (SSS) images. Goldstein and Osher have shown how to use an iterative method to reconstruct the original image through a method called Split Bregman's iteration. This method "decouples" the energies using portions of the energy from both the !1 and !2 norm. Once the energies are split, Bregman iteration is used to solve the unconstrained optimization problem by recursively solving the problems simultaneously. The faster these two steps or energies can be solved then the faster the overall method becomes. While the majority of CS research is still focused on the medical field, this paper will demonstrate the effectiveness of the Split Bregman's methods on sonar images.

An object-based storage model for distributed remote sensing images

NASA Astrophysics Data System (ADS)

Yu, Zhanwu; Li, Zhongmin; Zheng, Sheng

2006-10-01

It is very difficult to design an integrated storage solution for distributed remote sensing images to offer high performance network storage services and secure data sharing across platforms using current network storage models such as direct attached storage, network attached storage and storage area network. Object-based storage, as new generation network storage technology emerged recently, separates the data path, the control path and the management path, which solves the bottleneck problem of metadata existed in traditional storage models, and has the characteristics of parallel data access, data sharing across platforms, intelligence of storage devices and security of data access. We use the object-based storage in the storage management of remote sensing images to construct an object-based storage model for distributed remote sensing images. In the storage model, remote sensing images are organized as remote sensing objects stored in the object-based storage devices. According to the storage model, we present the architecture of a distributed remote sensing images application system based on object-based storage, and give some test results about the write performance comparison of traditional network storage model and object-based storage model.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features.

PubMed

Li, Linyi; Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features

PubMed Central

Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images. PMID:28761440

Research on Method of Interactive Segmentation Based on Remote Sensing Images

NASA Astrophysics Data System (ADS)

Yang, Y.; Li, H.; Han, Y.; Yu, F.

2017-09-01

In this paper, we aim to solve the object extraction problem in remote sensing images using interactive segmentation tools. Firstly, an overview of the interactive segmentation algorithm is proposed. Then, our detailed implementation of intelligent scissors and GrabCut for remote sensing images is described. Finally, several experiments on different typical features (water area, vegetation) in remote sensing images are performed respectively. Compared with the manual result, it indicates that our tools maintain good feature boundaries and show good performance.

Geometric correction of synchronous scanned Operational Modular Imaging Spectrometer II hyperspectral remote sensing images using spatial positioning data of an inertial navigation system

NASA Astrophysics Data System (ADS)

Zhou, Xiaohu; Neubauer, Franz; Zhao, Dong; Xu, Shichao

2015-01-01

The high-precision geometric correction of airborne hyperspectral remote sensing image processing was a hard nut to crack, and conventional methods of remote sensing image processing by selecting ground control points to correct the images are not suitable in the correction process of airborne hyperspectral image. The optical scanning system of an inertial measurement unit combined with differential global positioning system (IMU/DGPS) is introduced to correct the synchronous scanned Operational Modular Imaging Spectrometer II (OMIS II) hyperspectral remote sensing images. Posture parameters, which were synchronized with the OMIS II, were first obtained from the IMU/DGPS. Second, coordinate conversion and flight attitude parameters' calculations were conducted. Third, according to the imaging principle of OMIS II, mathematical correction was applied and the corrected image pixels were resampled. Then, better image processing results were achieved.

Continuous sensing of tumor-targeted molecular probes with a vertical cavity surface emitting laser-based biosensor

NASA Astrophysics Data System (ADS)

Parashurama, Natesh; O'Sullivan, Thomas D.; De La Zerda, Adam; El Kalassi, Pascale; Cho, Seongjae; Liu, Hongguang; Teed, Robert; Levy, Hart; Rosenberg, Jarrett; Cheng, Zhen; Levi, Ofer; Harris, James S.; Gambhir, Sanjiv S.

2012-11-01

Molecular optical imaging is a widespread technique for interrogating molecular events in living subjects. However, current approaches preclude long-term, continuous measurements in awake, mobile subjects, a strategy crucial in several medical conditions. Consequently, we designed a novel, lightweight miniature biosensor for in vivo continuous optical sensing. The biosensor contains an enclosed vertical-cavity surface-emitting semiconductor laser and an adjacent pair of near-infrared optically filtered detectors. We employed two sensors (dual sensing) to simultaneously interrogate normal and diseased tumor sites. Having established the sensors are precise with phantom and in vivo studies, we performed dual, continuous sensing in tumor (human glioblastoma cells) bearing mice using the targeted molecular probe cRGD-Cy5.5, which targets αVβ3 cell surface integrins in both tumor neovasculature and tumor. The sensors capture the dynamic time-activity curve of the targeted molecular probe. The average tumor to background ratio after signal calibration for cRGD-Cy5.5 injection is approximately 2.43±0.95 at 1 h and 3.64±1.38 at 2 h (N=5 mice), consistent with data obtained with a cooled charge coupled device camera. We conclude that our novel, portable, precise biosensor can be used to evaluate both kinetics and steady state levels of molecular probes in various disease applications.

Continuous sensing of tumor-targeted molecular probes with a vertical cavity surface emitting laser-based biosensor

PubMed Central

Parashurama, Natesh; O’Sullivan, Thomas D.; De La Zerda, Adam; El Kalassi, Pascale; Cho, Seongjae; Liu, Hongguang; Teed, Robert; Levy, Hart; Rosenberg, Jarrett; Cheng, Zhen; Levi, Ofer; Harris, James S.

2012-01-01

Abstract. Molecular optical imaging is a widespread technique for interrogating molecular events in living subjects. However, current approaches preclude long-term, continuous measurements in awake, mobile subjects, a strategy crucial in several medical conditions. Consequently, we designed a novel, lightweight miniature biosensor for in vivo continuous optical sensing. The biosensor contains an enclosed vertical-cavity surface-emitting semiconductor laser and an adjacent pair of near-infrared optically filtered detectors. We employed two sensors (dual sensing) to simultaneously interrogate normal and diseased tumor sites. Having established the sensors are precise with phantom and in vivo studies, we performed dual, continuous sensing in tumor (human glioblastoma cells) bearing mice using the targeted molecular probe cRGD-Cy5.5, which targets αVβ3 cell surface integrins in both tumor neovasculature and tumor. The sensors capture the dynamic time-activity curve of the targeted molecular probe. The average tumor to background ratio after signal calibration for cRGD-Cy5.5 injection is approximately 2.43±0.95 at 1 h and 3.64±1.38 at 2 h (N=5 mice), consistent with data obtained with a cooled charge coupled device camera. We conclude that our novel, portable, precise biosensor can be used to evaluate both kinetics and steady state levels of molecular probes in various disease applications. PMID:23123976

Remote Sensing Image Fusion Method Based on Nonsubsampled Shearlet Transform and Sparse Representation

NASA Astrophysics Data System (ADS)

Moonon, Altan-Ulzii; Hu, Jianwen; Li, Shutao

2015-12-01

The remote sensing image fusion is an important preprocessing technique in remote sensing image processing. In this paper, a remote sensing image fusion method based on the nonsubsampled shearlet transform (NSST) with sparse representation (SR) is proposed. Firstly, the low resolution multispectral (MS) image is upsampled and color space is transformed from Red-Green-Blue (RGB) to Intensity-Hue-Saturation (IHS). Then, the high resolution panchromatic (PAN) image and intensity component of MS image are decomposed by NSST to high and low frequency coefficients. The low frequency coefficients of PAN and the intensity component are fused by the SR with the learned dictionary. The high frequency coefficients of intensity component and PAN image are fused by local energy based fusion rule. Finally, the fused result is obtained by performing inverse NSST and inverse IHS transform. The experimental results on IKONOS and QuickBird satellites demonstrate that the proposed method provides better spectral quality and superior spatial information in the fused image than other remote sensing image fusion methods both in visual effect and object evaluation.

Quantum-enhanced multiparameter estimation in multiarm interferometers

PubMed Central

Ciampini, Mario A.; Spagnolo, Nicolò; Vitelli, Chiara; Pezzè, Luca; Smerzi, Augusto; Sciarrino, Fabio

2016-01-01

Quantum metrology is the state-of-the-art measurement technology. It uses quantum resources to enhance the sensitivity of phase estimation over that achievable by classical physics. While single parameter estimation theory has been widely investigated, much less is known about the simultaneous estimation of multiple phases, which finds key applications in imaging and sensing. In this manuscript we provide conditions of useful particle (qudit) entanglement for multiphase estimation and adapt them to multiarm Mach-Zehnder interferometry. We theoretically discuss benchmark multimode Fock states containing useful qudit entanglement and overcoming the sensitivity of separable qudit states in three and four arm Mach-Zehnder-like interferometers - currently within the reach of integrated photonics technology. PMID:27381743

Optimal Measurements for Simultaneous Quantum Estimation of Multiple Phases

NASA Astrophysics Data System (ADS)

Pezzè, Luca; Ciampini, Mario A.; Spagnolo, Nicolò; Humphreys, Peter C.; Datta, Animesh; Walmsley, Ian A.; Barbieri, Marco; Sciarrino, Fabio; Smerzi, Augusto

2017-09-01

A quantum theory of multiphase estimation is crucial for quantum-enhanced sensing and imaging and may link quantum metrology to more complex quantum computation and communication protocols. In this Letter, we tackle one of the key difficulties of multiphase estimation: obtaining a measurement which saturates the fundamental sensitivity bounds. We derive necessary and sufficient conditions for projective measurements acting on pure states to saturate the ultimate theoretical bound on precision given by the quantum Fisher information matrix. We apply our theory to the specific example of interferometric phase estimation using photon number measurements, a convenient choice in the laboratory. Our results thus introduce concepts and methods relevant to the future theoretical and experimental development of multiparameter estimation.

Generating and Separating Twisted Light by gradient-rotation Split-Ring Antenna Metasurfaces.

PubMed

Zeng, Jinwei; Li, Ling; Yang, Xiaodong; Gao, Jie

2016-05-11

Nanoscale compact optical vortex generators promise substantially significant prospects in modern optics and photonics, leading to many advances in sensing, imaging, quantum communication, and optical manipulation. However, conventional vortex generators often suffer from bulky size, low vortex mode purity in the converted beam, or limited operation bandwidth. Here, we design and demonstrate gradient-rotation split-ring antenna metasurfaces as unique spin-to-orbital angular momentum beam converters to simultaneously generate and separate pure optical vortices in a broad wavelength range. Our proposed design has the potential for realizing miniaturized on-chip OAM-multiplexers, as well as enabling new types of metasurface devices for the manipulation of complex structured light beams.

A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

NASA Astrophysics Data System (ADS)

Shuxin, Li; Zhilong, Zhang; Biao, Li

2018-01-01

Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

A light and faster regional convolutional neural network for object detection in optical remote sensing images

NASA Astrophysics Data System (ADS)

Ding, Peng; Zhang, Ye; Deng, Wei-Jian; Jia, Ping; Kuijper, Arjan

2018-07-01

Detection of objects from satellite optical remote sensing images is very important for many commercial and governmental applications. With the development of deep convolutional neural networks (deep CNNs), the field of object detection has seen tremendous advances. Currently, objects in satellite remote sensing images can be detected using deep CNNs. In general, optical remote sensing images contain many dense and small objects, and the use of the original Faster Regional CNN framework does not yield a suitably high precision. Therefore, after careful analysis we adopt dense convoluted networks, a multi-scale representation and various combinations of improvement schemes to enhance the structure of the base VGG16-Net for improving the precision. We propose an approach to reduce the test-time (detection time) and memory requirements. To validate the effectiveness of our approach, we perform experiments using satellite remote sensing image datasets of aircraft and automobiles. The results show that the improved network structure can detect objects in satellite optical remote sensing images more accurately and efficiently.

Ontology-based classification of remote sensing images using spectral rules

NASA Astrophysics Data System (ADS)

Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent

2017-05-01

Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.

Automated railroad reconstruction from remote sensing image based on texture filter

NASA Astrophysics Data System (ADS)

Xiao, Jie; Lu, Kaixia

2018-03-01

Techniques of remote sensing have been improved incredibly in recent years and very accurate results and high resolution images can be acquired. There exist possible ways to use such data to reconstruct railroads. In this paper, an automated railroad reconstruction method from remote sensing images based on Gabor filter was proposed. The method is divided in three steps. Firstly, the edge-oriented railroad characteristics (such as line features) in a remote sensing image are detected using Gabor filter. Secondly, two response images with the filtering orientations perpendicular to each other are fused to suppress the noise and acquire a long stripe smooth region of railroads. Thirdly, a set of smooth regions can be extracted by firstly computing global threshold for the previous result image using Otsu's method and then converting it to a binary image based on the previous threshold. This workflow is tested on a set of remote sensing images and was found to deliver very accurate results in a quickly and highly automated manner.

Hyperspectral imaging for simultaneous measurements of two FRET biosensors in pancreatic β-cells.

PubMed

Elliott, Amicia D; Bedard, Noah; Ustione, Alessandro; Baird, Michelle A; Davidson, Michael W; Tkaczyk, Tomasz; Piston, David W

2017-01-01

Fluorescent protein (FP) biosensors based on Förster resonance energy transfer (FRET) are commonly used to study molecular processes in living cells. There are FP-FRET biosensors for many cellular molecules, but it remains difficult to perform simultaneous measurements of multiple biosensors. The overlapping emission spectra of the commonly used FPs, including CFP/YFP and GFP/RFP make dual FRET measurements challenging. In addition, a snapshot imaging modality is required for simultaneous imaging. The Image Mapping Spectrometer (IMS) is a snapshot hyperspectral imaging system that collects high resolution spectral data and can be used to overcome these challenges. We have previously demonstrated the IMS's capabilities for simultaneously imaging GFP and CFP/YFP-based biosensors in pancreatic β-cells. Here, we demonstrate a further capability of the IMS to image simultaneously two FRET biosensors with a single excitation band, one for cAMP and the other for Caspase-3. We use these measurements to measure simultaneously cAMP signaling and Caspase-3 activation in pancreatic β-cells during oxidative stress and hyperglycemia, which are essential components in the pathology of diabetes.

The effects of SENSE on PROPELLER imaging.

PubMed

Chang, Yuchou; Pipe, James G; Karis, John P; Gibbs, Wende N; Zwart, Nicholas R; Schär, Michael

2015-12-01

To study how sensitivity encoding (SENSE) impacts periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) image quality, including signal-to-noise ratio (SNR), robustness to motion, precision of motion estimation, and image quality. Five volunteers were imaged by three sets of scans. A rapid method for generating the g-factor map was proposed and validated via Monte Carlo simulations. Sensitivity maps were extrapolated to increase the area over which SENSE can be performed and therefore enhance the robustness to head motion. The precision of motion estimation of PROPELLER blades that are unfolded with these sensitivity maps was investigated. An interleaved R-factor PROPELLER sequence was used to acquire data with similar amounts of motion with and without SENSE acceleration. Two neuroradiologists independently and blindly compared 214 image pairs. The proposed method of g-factor calculation was similar to that provided by the Monte Carlo methods. Extrapolation and rotation of the sensitivity maps allowed for continued robustness of SENSE unfolding in the presence of motion. SENSE-widened blades improved the precision of rotation and translation estimation. PROPELLER images with a SENSE factor of 3 outperformed the traditional PROPELLER images when reconstructing the same number of blades. SENSE not only accelerates PROPELLER but can also improve robustness and precision of head motion correction, which improves overall image quality even when SNR is lost due to acceleration. The reduction of SNR, as a penalty of acceleration, is characterized by the proposed g-factor method. © 2014 Wiley Periodicals, Inc.

Integrated satellite data fusion and mining for monitoring lake water quality status of the Albufera de Valencia in Spain.

PubMed

Doña, Carolina; Chang, Ni-Bin; Caselles, Vicente; Sánchez, Juan M; Camacho, Antonio; Delegido, Jesús; Vannah, Benjamin W

2015-03-15

Lake eutrophication is a critical issue in the interplay of water supply, environmental management, and ecosystem conservation. Integrated sensing, monitoring, and modeling for a holistic lake water quality assessment with respect to multiple constituents is in acute need. The aim of this paper is to develop an integrated algorithm for data fusion and mining of satellite remote sensing images to generate daily estimates of some water quality parameters of interest, such as chlorophyll a concentrations and water transparency, to be applied for the assessment of the hypertrophic Albufera de Valencia. The Albufera de Valencia is the largest freshwater lake in Spain, which can often present values of chlorophyll a concentration over 200 mg m(-3) and values of transparency (Secchi Disk, SD) as low as 20 cm. Remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper (TM) and Enhance Thematic Mapper (ETM+) images were fused to carry out an integrative near-real time water quality assessment on a daily basis. Landsat images are useful to study the spatial variability of the water quality parameters, due to its spatial resolution of 30 m, in comparison to the low spatial resolution (250/500 m) of MODIS. While Landsat offers a high spatial resolution, the low temporal resolution of 16 days is a significant drawback to achieve a near real-time monitoring system. This gap may be bridged by using MODIS images that have a high temporal resolution of 1 day, in spite of its low spatial resolution. Synthetic Landsat images were fused for dates with no Landsat overpass over the study area. Finally, with a suite of ground truth data, a few genetic programming (GP) models were derived to estimate the water quality using the fused surface reflectance data as inputs. The GP model for chlorophyll a estimation yielded a R(2) of 0.94, with a Root Mean Square Error (RMSE) = 8 mg m(-3), and the GP model for water transparency estimation using Secchi disk showed a R(2) of 0.89, with an RMSE = 4 cm. With this effort, the spatiotemporal variations of water transparency and chlorophyll a concentrations may be assessed simultaneously on a daily basis throughout the lake for environmental management. Copyright © 2014 Elsevier Ltd. All rights reserved.

Sensing and Tactile Artificial Muscles from Reactive Materials

PubMed Central

Conzuelo, Laura Valero; Arias-Pardilla, Joaquín; Cauich-Rodríguez, Juan V.; Smit, Mascha Afra; Otero, Toribio Fernández

2010-01-01

Films of conducting polymers can be oxidized and reduced in a reversible way. Any intermediate oxidation state determines an electrochemical equilibrium. Chemical or physical variables acting on the film may modify the equilibrium potential, so that the film acts as a sensor of the variable. The working potential of polypyrrole/DBSA (Dodecylbenzenesulfonic acid) films, oxidized or reduced under constant currents, changes as a function of the working conditions: electrolyte concentration, temperature or mechanical stress. During oxidation, the reactive material is a sensor of the ambient, the consumed electrical energy being the sensing magnitude. Devices based on any of the electrochemical properties of conducting polymers must act simultaneously as sensors of the working conditions. Artificial muscles, as electrochemical actuators constituted by reactive materials, respond to the ambient conditions during actuation. In this way, they can be used as actuators, sensing the surrounding conditions during actuation. Actuating and sensing signals are simultaneously included by the same two connecting wires. PMID:22319265

Multibeam Interferometer Using a Photonic Crystal Fiber with Two Asymmetric Cores for Torsion, Strain and Temperature Sensing

PubMed Central

Naeem, Khurram; Kwon, Il-Bum; Chung, Youngjoo

2017-01-01

We present a fiber-optic multibeam Mach-Zehnder interferometer (m-MZI) for simultaneous multi-parameter measurement. The m-MZI is comprised of a section of photonic crystal fiber integrated with two independent cores of distinct construction and birefringence properties characterized for torsion, strain and temperature sensing. Due to the presence of small core geometry and use of a short fiber length, the sensing device demonstrates inter-modal interference in the small core alongside the dominant inter-core interference between the cores for each of the orthogonal polarizations. The output spectrum of the device is characterized by the three-beam interference model and is polarization-dependent. The two types of interferometers present in the fiber m-MZI exhibit distinct sensitivities to torsion, strain and temperature for different polarizations, and matrix coefficients allowing simultaneous measurement of the three sensing parameters are proposed in experiment. PMID:28085046

Some Defence Applications of Civilian Remote Sensing Satellite Images

DTIC Science & Technology

1993-11-01

This report is on a pilot study to demonstrate some of the capabilities of remote sensing in intelligence gathering. A wide variety of issues, both...colour images. The procedure will be presented in a companion report. Remote sensing , Satellite imagery, Image analysis, Military applications, Military intelligence.

NDSI products system based on Hadoop platform

NASA Astrophysics Data System (ADS)

Zhou, Yan; Jiang, He; Yang, Xiaoxia; Geng, Erhui

2015-12-01

Snow is solid state of water resources on earth, and plays an important role in human life. Satellite remote sensing is significant in snow extraction with the advantages of cyclical, macro, comprehensiveness, objectivity, timeliness. With the continuous development of remote sensing technology, remote sensing data access to the trend of multiple platforms, multiple sensors and multiple perspectives. At the same time, in view of the remote sensing data of compute-intensive applications demand increase gradually. However, current the producing system of remote sensing products is in a serial mode, and this kind of production system is used for professional remote sensing researchers mostly, and production systems achieving automatic or semi-automatic production are relatively less. Facing massive remote sensing data, the traditional serial mode producing system with its low efficiency has been difficult to meet the requirements of mass data timely and efficient processing. In order to effectively improve the production efficiency of NDSI products, meet the demand of large-scale remote sensing data processed timely and efficiently, this paper build NDSI products production system based on Hadoop platform, and the system mainly includes the remote sensing image management module, NDSI production module, and system service module. Main research contents and results including: (1)The remote sensing image management module: includes image import and image metadata management two parts. Import mass basis IRS images and NDSI product images (the system performing the production task output) into HDFS file system; At the same time, read the corresponding orbit ranks number, maximum/minimum longitude and latitude, product date, HDFS storage path, Hadoop task ID (NDSI products), and other metadata information, and then create thumbnails, and unique ID number for each record distribution, import it into base/product image metadata database. (2)NDSI production module: includes the index calculation, production tasks submission and monitoring two parts. Read HDF images related to production task in the form of a byte stream, and use Beam library to parse image byte stream to the form of Product; Use MapReduce distributed framework to perform production tasks, at the same time monitoring task status; When the production task complete, calls remote sensing image management module to store NDSI products. (3)System service module: includes both image search and DNSI products download. To image metadata attributes described in JSON format, return to the image sequence ID existing in the HDFS file system; For the given MapReduce task ID, package several task output NDSI products into ZIP format file, and return to the download link (4)System evaluation: download massive remote sensing data and use the system to process it to get the NDSI products testing the performance, and the result shows that the system has high extendibility, strong fault tolerance, fast production speed, and the image processing results with high accuracy.

Remote sensing data of SP Mountain and SP Lava flow in North-Central Arizona

USGS Publications Warehouse

Schaber, G.G.; Elachi, C.; Farr, T.G.

1980-01-01

Multifrequency airborne radar image data of SP Mountain [Official name of feature (U.S. Geological Survey, 1970)] and SP flow (and vicinity) in north-central Arizona were obtained in diverse viewing directions and direct and cross-polarization, then compared with surface and aerial photography, LANDSAT multispectral scanner data, airborne thermal infrared imagery, surface geology, and surface roughness statistics. The extremely blocky, basaltic andesite of SP flow is significantly brighter on direct-polarization K-band (0.9-cm wavelength) images than on cross-polarized images taken simultaneously. Conversely, for the longer wavelength (25 cm) L-band radar images, the cross-polarization image returns from SP flow are brighter than the direct-polarized image. This effect is explained by multiple scattering and the strong wavelength dependence of polarization effects caused by the rectilinear basaltic andesite scatters. Two distinct types of surface relief on SP flow, one extremely blocky, the other subdued, are found to be clearly discriminated on the visible and thermal wavelength images but are separable only on the longer wavelength L-band radar image data. The inability of the K- and X- (3-cm wavelength) band radars to portray the differences in roughness between the two SP flow surface units is attributed to the radar frequency dependence of the surface-relief scale, which, described as the Rayleigh criterion, represents the transition between quasispecular and primarily diffuse backscatter. ?? 1980.

Compressed Sensing for Body MRI

PubMed Central

Feng, Li; Benkert, Thomas; Block, Kai Tobias; Sodickson, Daniel K; Otazo, Ricardo; Chandarana, Hersh

2016-01-01

The introduction of compressed sensing for increasing imaging speed in MRI has raised significant interest among researchers and clinicians, and has initiated a large body of research across multiple clinical applications over the last decade. Compressed sensing aims to reconstruct unaliased images from fewer measurements than that are traditionally required in MRI by exploiting image compressibility or sparsity. Moreover, appropriate combinations of compressed sensing with previously introduced fast imaging approaches, such as parallel imaging, have demonstrated further improved performance. The advent of compressed sensing marks the prelude to a new era of rapid MRI, where the focus of data acquisition has changed from sampling based on the nominal number of voxels and/or frames to sampling based on the desired information content. This paper presents a brief overview of the application of compressed sensing techniques in body MRI, where imaging speed is crucial due to the presence of respiratory motion along with stringent constraints on spatial and temporal resolution. The first section provides an overview of the basic compressed sensing methodology, including the notion of sparsity, incoherence, and non-linear reconstruction. The second section reviews state-of-the-art compressed sensing techniques that have been demonstrated for various clinical body MRI applications. In the final section, the paper discusses current challenges and future opportunities. PMID:27981664

Sense of place in outdoor-pursuits trip groups

Treesearch

Sharon L. Todd; Anderson B. Young; Lynn S. Anderson; Timothy S. O' Connell; Mary Breunig

2009-01-01

Studies have revealed that sense of community and group cohesion increase significantly over time in outdoor-pursuits trip groups. This study sought to understand similar development of sense of place. Do people simultaneously become more attached to or dependent on the natural environment as they grow closer to each other? Results from a study of college students...

Redundancy in Simultaneously Presented Audio-Visual Message Elements as a Determinant of Recall. Final Report.

ERIC Educational Resources Information Center

Baldwin, Thomas F.

Man seems unable to retain different information from different senses or channels simultaneously; one channel gains full attention. However, it is hypothesized that if the message elements arriving simultaneously from audio and visual channels are redundant, man will retain the information. An attempt was made to measure redundancy in the audio…

Approach for removing ghost-images in remote field eddy current testing of ferromagnetic pipes

NASA Astrophysics Data System (ADS)

Luo, Q. W.; Shi, Y. B.; Wang, Z. G.; Zhang, W.; Zhang, Y.

2016-10-01

In the non-destructive testing of ferromagnetic pipes based on remote field eddy currents, an array of sensing coils is often used to detect local defects. While testing, the image that is obtained by sensing coils exhibits a ghost-image, which originates from both the transmitter and sensing coils passing over the same defects in pipes. Ghost-images are caused by transmitters and lead to undesirable assessments of defects. In order to remove ghost-images, two pickup coils are coaxially set to each other in remote field. Due to the time delay between differential signals tested by the two pickup coils, a Wiener deconvolution filter is used to identify the artificial peaks that lead to ghost-images. Because the sensing coils and two pickup coils all receive the same signal from one transmitter, they all contain the same artificial peaks. By subtracting the artificial peak values obtained by the two pickup coils from the imaging data, the ghost-image caused by the transmitter is eliminated. Finally, a relatively highly accurate image of local defects is obtained by these sensing coils. With proposed method, there is no need to subtract the average value of the sensing coils, and it is sensitive to ringed defects.

Approach for removing ghost-images in remote field eddy current testing of ferromagnetic pipes.

PubMed

Luo, Q W; Shi, Y B; Wang, Z G; Zhang, W; Zhang, Y

2016-10-01

In the non-destructive testing of ferromagnetic pipes based on remote field eddy currents, an array of sensing coils is often used to detect local defects. While testing, the image that is obtained by sensing coils exhibits a ghost-image, which originates from both the transmitter and sensing coils passing over the same defects in pipes. Ghost-images are caused by transmitters and lead to undesirable assessments of defects. In order to remove ghost-images, two pickup coils are coaxially set to each other in remote field. Due to the time delay between differential signals tested by the two pickup coils, a Wiener deconvolution filter is used to identify the artificial peaks that lead to ghost-images. Because the sensing coils and two pickup coils all receive the same signal from one transmitter, they all contain the same artificial peaks. By subtracting the artificial peak values obtained by the two pickup coils from the imaging data, the ghost-image caused by the transmitter is eliminated. Finally, a relatively highly accurate image of local defects is obtained by these sensing coils. With proposed method, there is no need to subtract the average value of the sensing coils, and it is sensitive to ringed defects.

Remote sensing programs and courses in engineering and water resources

NASA Technical Reports Server (NTRS)

Kiefer, R. W.

1981-01-01

The content of typical basic and advanced remote sensing and image interpretation courses are described and typical remote sensing graduate programs of study in civil engineering and in interdisciplinary environmental remote sensing and water resources management programs are outlined. Ideally, graduate programs with an emphasis on remote sensing and image interpretation should be built around a core of five courses: (1) a basic course in fundamentals of remote sensing upon which the more specialized advanced remote sensing courses can build; (2) a course dealing with visual image interpretation; (3) a course dealing with quantitative (computer-based) image interpretation; (4) a basic photogrammetry course; and (5) a basic surveying course. These five courses comprise up to one-half of the course work required for the M.S. degree. The nature of other course work and thesis requirements vary greatly, depending on the department in which the degree is being awarded.

NASA COAST and OCEANIA Airborne Missions Support Ecosystem and Water Quality Research in the Coastal Zone

NASA Technical Reports Server (NTRS)

Guild, Liane; Kudela, Raphael; Hooker, Stanford; Morrow, John; Russell, Philip; Palacios, Sherry; Livingston, John M.; Negrey, Kendra; Torres-Perez, Juan; Broughton, Jennifer

2014-01-01

NASA has a continuing requirement to collect high-quality in situ data for the vicarious calibration of current and next generation ocean color satellite sensors and to validate the algorithms that use the remotely sensed observations. Recent NASA airborne missions over Monterey Bay, CA, have demonstrated novel above- and in-water measurement capabilities supporting a combined airborne sensor approach (imaging spectrometer, microradiometers, and a sun photometer). The results characterize coastal atmospheric and aquatic properties through an end-to-end assessment of image acquisition, atmospheric correction, algorithm application, plus sea-truth observations from state-of-the-art instrument systems. The primary goal is to demonstrate the following in support of calibration and validation exercises for satellite coastal ocean color products: 1) the utility of a multi-sensor airborne instrument suite to assess the bio-optical properties of coastal California, including water quality; and 2) the importance of contemporaneous atmospheric measurements to improve atmospheric correction in the coastal zone. The imaging spectrometer (Headwall) is optimized in the blue spectral domain to emphasize remote sensing of marine and freshwater ecosystems. The novel airborne instrument, Coastal Airborne In-situ Radiometers (C-AIR) provides measurements of apparent optical properties with high dynamic range and fidelity for deriving exact water leaving radiances at the land-ocean boundary, including radiometrically shallow aquatic ecosystems. Simultaneous measurements supporting empirical atmospheric correction of image data are accomplished using the Ames Airborne Tracking Sunphotometer (AATS-14). Flight operations are presented for the instrument payloads using the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter flown over Monterey Bay during the seasonal fall algal bloom in 2011 (COAST) and 2013 (OCEANIA) to support bio-optical measurements of phytoplankton for coastal zone research.

iShadow: Design of a Wearable, Real-Time Mobile Gaze Tracker.

PubMed

Mayberry, Addison; Hu, Pan; Marlin, Benjamin; Salthouse, Christopher; Ganesan, Deepak

2014-06-01

Continuous, real-time tracking of eye gaze is valuable in a variety of scenarios including hands-free interaction with the physical world, detection of unsafe behaviors, leveraging visual context for advertising, life logging, and others. While eye tracking is commonly used in clinical trials and user studies, it has not bridged the gap to everyday consumer use. The challenge is that a real-time eye tracker is a power-hungry and computation-intensive device which requires continuous sensing of the eye using an imager running at many tens of frames per second, and continuous processing of the image stream using sophisticated gaze estimation algorithms. Our key contribution is the design of an eye tracker that dramatically reduces the sensing and computation needs for eye tracking, thereby achieving orders of magnitude reductions in power consumption and form-factor. The key idea is that eye images are extremely redundant, therefore we can estimate gaze by using a small subset of carefully chosen pixels per frame. We instantiate this idea in a prototype hardware platform equipped with a low-power image sensor that provides random access to pixel values, a low-power ARM Cortex M3 microcontroller, and a bluetooth radio to communicate with a mobile phone. The sparse pixel-based gaze estimation algorithm is a multi-layer neural network learned using a state-of-the-art sparsity-inducing regularization function that minimizes the gaze prediction error while simultaneously minimizing the number of pixels used. Our results show that we can operate at roughly 70mW of power, while continuously estimating eye gaze at the rate of 30 Hz with errors of roughly 3 degrees.

iShadow: Design of a Wearable, Real-Time Mobile Gaze Tracker

PubMed Central

Mayberry, Addison; Hu, Pan; Marlin, Benjamin; Salthouse, Christopher; Ganesan, Deepak

2015-01-01

Continuous, real-time tracking of eye gaze is valuable in a variety of scenarios including hands-free interaction with the physical world, detection of unsafe behaviors, leveraging visual context for advertising, life logging, and others. While eye tracking is commonly used in clinical trials and user studies, it has not bridged the gap to everyday consumer use. The challenge is that a real-time eye tracker is a power-hungry and computation-intensive device which requires continuous sensing of the eye using an imager running at many tens of frames per second, and continuous processing of the image stream using sophisticated gaze estimation algorithms. Our key contribution is the design of an eye tracker that dramatically reduces the sensing and computation needs for eye tracking, thereby achieving orders of magnitude reductions in power consumption and form-factor. The key idea is that eye images are extremely redundant, therefore we can estimate gaze by using a small subset of carefully chosen pixels per frame. We instantiate this idea in a prototype hardware platform equipped with a low-power image sensor that provides random access to pixel values, a low-power ARM Cortex M3 microcontroller, and a bluetooth radio to communicate with a mobile phone. The sparse pixel-based gaze estimation algorithm is a multi-layer neural network learned using a state-of-the-art sparsity-inducing regularization function that minimizes the gaze prediction error while simultaneously minimizing the number of pixels used. Our results show that we can operate at roughly 70mW of power, while continuously estimating eye gaze at the rate of 30 Hz with errors of roughly 3 degrees. PMID:26539565

GAIA virtual observatory - development and practices

NASA Astrophysics Data System (ADS)

Syrjäsuo, Mikko; Marple, Steve

2010-05-01

The Global Auroral Imaging Access, or GAIA, is a virtual observatory providing quick access to summary data from satellite and ground-based instruments that remote sense auroral precipitation (http://gaia-vxo.org). This web-based service facilitates locating data relevant to particular events by simultaneously displaying summary images from various data sets around the world. At the moment, there are GAIA server nodes in Canada, Finland, Norway and the UK. The development is an international effort and the software and metadata are freely available. The GAIA system is based on a relational database which is queried by a dedicated software suite that also creates the graphical end-user interface if such is needed. Most commonly, the virtual observatory is used interactively by using a web browser: the user provides the date and the type of data of interest. As the summary data from multiple instruments are displayed simultaneously, the user can conveniently explore the recorded data. The virtual observatory provides essentially instant access to the images originating from all major auroral instrument networks including THEMIS, NORSTAR, GLORIA and MIRACLE. The scientific, educational and outreach use is limited by creativity rather than access. The first version of the GAIA was developed at the University of Calgary (Alberta, Canada) in 2004-2005. This proof-of-concept included mainly THEMIS and MIRACLE data, which comprised of millions of summary plots and thumbnail images. However, it was soon realised that a complete re-design was necessary to increase flexibility. In the presentation, we will discuss the early history and motivation of GAIA as well as how the development continued towards the current version. The emphasis will be on practical problems and their solutions. Relevant design choices will also be highlighted.

Broadband Phase Retrieval for Image-Based Wavefront Sensing

NASA Technical Reports Server (NTRS)

Dean, Bruce H.

2007-01-01

A focus-diverse phase-retrieval algorithm has been shown to perform adequately for the purpose of image-based wavefront sensing when (1) broadband light (typically spanning the visible spectrum) is used in forming the images by use of an optical system under test and (2) the assumption of monochromaticity is applied to the broadband image data. Heretofore, it had been assumed that in order to obtain adequate performance, it is necessary to use narrowband or monochromatic light. Some background information, including definitions of terms and a brief description of pertinent aspects of image-based phase retrieval, is prerequisite to a meaningful summary of the present development. Phase retrieval is a general term used in optics to denote estimation of optical imperfections or aberrations of an optical system under test. The term image-based wavefront sensing refers to a general class of algorithms that recover optical phase information, and phase-retrieval algorithms constitute a subset of this class. In phase retrieval, one utilizes the measured response of the optical system under test to produce a phase estimate. The optical response of the system is defined as the image of a point-source object, which could be a star or a laboratory point source. The phase-retrieval problem is characterized as image-based in the sense that a charge-coupled-device camera, preferably of scientific imaging quality, is used to collect image data where the optical system would normally form an image. In a variant of phase retrieval, denoted phase-diverse phase retrieval [which can include focus-diverse phase retrieval (in which various defocus planes are used)], an additional known aberration (or an equivalent diversity function) is superimposed as an aid in estimating unknown aberrations by use of an image-based wavefront-sensing algorithm. Image-based phase-retrieval differs from such other wavefront-sensing methods, such as interferometry, shearing interferometry, curvature wavefront sensing, and Shack-Hartmann sensing, all of which entail disadvantages in comparison with image-based methods. The main disadvantages of these non-image based methods are complexity of test equipment and the need for a wavefront reference.

Remote sensing image ship target detection method based on visual attention model

NASA Astrophysics Data System (ADS)

Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

2017-11-01

The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

Biomedical imaging and sensing using flatbed scanners.

PubMed

Göröcs, Zoltán; Ozcan, Aydogan

2014-09-07

In this Review, we provide an overview of flatbed scanner based biomedical imaging and sensing techniques. The extremely large imaging field-of-view (e.g., ~600-700 cm(2)) of these devices coupled with their cost-effectiveness provide unique opportunities for digital imaging of samples that are too large for regular optical microscopes, and for collection of large amounts of statistical data in various automated imaging or sensing tasks. Here we give a short introduction to the basic features of flatbed scanners also highlighting the key parameters for designing scientific experiments using these devices, followed by a discussion of some of the significant examples, where scanner-based systems were constructed to conduct various biomedical imaging and/or sensing experiments. Along with mobile phones and other emerging consumer electronics devices, flatbed scanners and their use in advanced imaging and sensing experiments might help us transform current practices of medicine, engineering and sciences through democratization of measurement science and empowerment of citizen scientists, science educators and researchers in resource limited settings.

Biomedical Imaging and Sensing using Flatbed Scanners

PubMed Central

Göröcs, Zoltán; Ozcan, Aydogan

2014-01-01

In this Review, we provide an overview of flatbed scanner based biomedical imaging and sensing techniques. The extremely large imaging field-of-view (e.g., ~600–700 cm2) of these devices coupled with their cost-effectiveness provide unique opportunities for digital imaging of samples that are too large for regular optical microscopes, and for collection of large amounts of statistical data in various automated imaging or sensing tasks. Here we give a short introduction to the basic features of flatbed scanners also highlighting the key parameters for designing scientific experiments using these devices, followed by a discussion of some of the significant examples, where scanner-based systems were constructed to conduct various biomedical imaging and/or sensing experiments. Along with mobile phones and other emerging consumer electronics devices, flatbed scanners and their use in advanced imaging and sensing experiments might help us transform current practices of medicine, engineering and sciences through democratization of measurement science and empowerment of citizen scientists, science educators and researchers in resource limited settings. PMID:24965011

High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

NASA Astrophysics Data System (ADS)

Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

2018-04-01

With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

High efficient optical remote sensing images acquisition for nano-satellite: reconstruction algorithms

NASA Astrophysics Data System (ADS)

Liu, Yang; Li, Feng; Xin, Lei; Fu, Jie; Huang, Puming

2017-10-01

Large amount of data is one of the most obvious features in satellite based remote sensing systems, which is also a burden for data processing and transmission. The theory of compressive sensing(CS) has been proposed for almost a decade, and massive experiments show that CS has favorable performance in data compression and recovery, so we apply CS theory to remote sensing images acquisition. In CS, the construction of classical sensing matrix for all sparse signals has to satisfy the Restricted Isometry Property (RIP) strictly, which limits applying CS in practical in image compression. While for remote sensing images, we know some inherent characteristics such as non-negative, smoothness and etc.. Therefore, the goal of this paper is to present a novel measurement matrix that breaks RIP. The new sensing matrix consists of two parts: the standard Nyquist sampling matrix for thumbnails and the conventional CS sampling matrix. Since most of sun-synchronous based satellites fly around the earth 90 minutes and the revisit cycle is also short, lots of previously captured remote sensing images of the same place are available in advance. This drives us to reconstruct remote sensing images through a deep learning approach with those measurements from the new framework. Therefore, we propose a novel deep convolutional neural network (CNN) architecture which takes in undersampsing measurements as input and outputs an intermediate reconstruction image. It is well known that the training procedure to the network costs long time, luckily, the training step can be done only once, which makes the approach attractive for a host of sparse recovery problems.

Current Status and Prospects for Microbubbles in Ultrasound Theranostics

PubMed Central

Martin, K. Heath

2013-01-01

Encapsulated microbubbles have been developed over the past two decades to provide both improvements in imaging as well as new therapeutic applications. Microbubble contrast agents are used currently for clinical imaging where increased sensitivity to blood flow is required, such as echocardiography. These compressible spheres oscillate in an acoustic field, producing nonlinear responses which can be uniquely distinguished from surrounding tissue, resulting in substantial enhancements in imaging signal-to-noise ratio. Furthermore, with sufficient acoustic energy the oscillation of microbubbles can mediate localized biological effects in tissue including the enhancement of membrane permeability or increased thermal energy deposition. Structurally, microbubbles are comprised of two principal components – an encapsulating shell and an inner gas core. This configuration enables microbubbles to be loaded with drugs or genes for additional therapeutic effect. Application of sufficient ultrasound energy can release this payload, resulting in site-specific delivery. Extensive pre-clinical studies illustrate that combining microbubbles and ultrasound can result in enhanced drug delivery or gene expression at spatially selective sites. Thus, microbbubles can be used for imaging, for therapy, or for both simultaneously. In this sense, microbubbles combined with acoustics may be one of the most universal theranostic tools. PMID:23504911

Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades.

PubMed

Orchard, Garrick; Jayawant, Ajinkya; Cohen, Gregory K; Thakor, Nitish

2015-01-01

Creating datasets for Neuromorphic Vision is a challenging task. A lack of available recordings from Neuromorphic Vision sensors means that data must typically be recorded specifically for dataset creation rather than collecting and labeling existing data. The task is further complicated by a desire to simultaneously provide traditional frame-based recordings to allow for direct comparison with traditional Computer Vision algorithms. Here we propose a method for converting existing Computer Vision static image datasets into Neuromorphic Vision datasets using an actuated pan-tilt camera platform. Moving the sensor rather than the scene or image is a more biologically realistic approach to sensing and eliminates timing artifacts introduced by monitor updates when simulating motion on a computer monitor. We present conversion of two popular image datasets (MNIST and Caltech101) which have played important roles in the development of Computer Vision, and we provide performance metrics on these datasets using spike-based recognition algorithms. This work contributes datasets for future use in the field, as well as results from spike-based algorithms against which future works can compare. Furthermore, by converting datasets already popular in Computer Vision, we enable more direct comparison with frame-based approaches.

Cross-comparison of the IRS-P6 AWiFS sensor with the L5 TM, L7 ETM+, & Terra MODIS sensors

USGS Publications Warehouse

Chander, G.; Xiong, X.; Angal, A.; Choi, T.; Malla, R.

2009-01-01

As scientists and decision makers increasingly rely on multiple Earth-observing satellites to address urgent global issues, it is imperative that they can rely on the accuracy of Earth-observing data products. This paper focuses on the crosscomparison of the Indian Remote Sensing (IRS-P6) Advanced Wide Field Sensor (AWiFS) with the Landsat 5 (L5) Thematic Mapper (TM), Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+), and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. The cross-comparison was performed using image statistics based on large common areas observed by the sensors within 30 minutes. Because of the limited availability of simultaneous observations between the AWiFS and the Landsat and MODIS sensors, only a few images were analyzed. These initial results are presented. Regression curves and coefficients of determination for the top-of-atmosphere (TOA) trends from these sensors were generated to quantify the uncertainty in these relationships and to provide an assessment of the calibration differences between these sensors. ?? 2009 SPIE.

Ocean-ice interaction in the marginal ice zone using synthetic aperture radar imagery

NASA Technical Reports Server (NTRS)

Liu, Antony K.; Peng, Chich Y.; Weingartner, Thomas J.

1994-01-01

Ocean-ice interaction processes in the marginal ice zone (MIZ) by wind, waves, and mesoscale features, such as up/downwelling and eddies are studied using Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) images and an ocean-ice interaction model. A sequence of seven SAR images of the MIZ in the Chukchi Sea with 3 or 6 days interval are investigated for ice edge advance/retreat. Simultaneous current measurements from the northeast Chukchi Sea, as well as the Barrow wind record, are used to interpret the MIZ dynamics. SAR spectra of waves in ice and ocean waves in the Bering and Chukchi Sea are compared for the study of wave propagation and dominant SAR imaging mechanism. By using the SAR-observed ice edge configuration and wind and wave field in the Chukchi Sea as inputs, a numerical simulation has been performed with the ocean-ice interaction model. After 3 days of wind and wave forcing the resulting ice edge configuration, eddy formation, and flow velocity field are shown to be consistent with SAR observations.

Comparison of AIS Versus TMS Data Collected over the Virginia Piedmont

NASA Technical Reports Server (NTRS)

Bell, R.; Evans, C. S.

1985-01-01

The Airborne Imaging Spectrometer (AIS, NS001 Thematic Mapper Simlulator (TMS), and Zeiss camera collected remotely sensed data simultaneously on October 27, 1983, at an altitude of 6860 meters (22,500 feet). AIS data were collected in 32 channels covering 1200 to 1500 nm. A simple atmospheric correction was applied to the AIS data, after which spectra for four cover types were plotted. Spectra for these ground cover classes showed a telescoping effect for the wavelength endpoints. Principal components were extracted from the shortwave region of the AIS (1200 to 1280 nm), full spectrum AIS (1200 to 1500 nm) and TMS (450 to 12,500 nm) to create three separate three-component color image composites. A comparison of the TMS band 5 (1000 to 1300 nm) to the six principal components from the shortwave AIS region (1200 to 1280 nm) showed improved visual discrimination of ground cover types. Contrast of color image composites created from principal components showed the AIS composites to exhibit a clearer demarcation between certain ground cover types but subtle differences within other regions of the imagery were not as readily seen.

Optimized computational imaging methods for small-target sensing in lens-free holographic microscopy

NASA Astrophysics Data System (ADS)

Xiong, Zhen; Engle, Isaiah; Garan, Jacob; Melzer, Jeffrey E.; McLeod, Euan

2018-02-01

Lens-free holographic microscopy is a promising diagnostic approach because it is cost-effective, compact, and suitable for point-of-care applications, while providing high resolution together with an ultra-large field-of-view. It has been applied to biomedical sensing, where larger targets like eukaryotic cells, bacteria, or viruses can be directly imaged without labels, and smaller targets like proteins or DNA strands can be detected via scattering labels like micro- or nano-spheres. Automated image processing routines can count objects and infer target concentrations. In these sensing applications, sensitivity and specificity are critically affected by image resolution and signal-to-noise ratio (SNR). Pixel super-resolution approaches have been shown to boost resolution and SNR by synthesizing a high-resolution image from multiple, partially redundant, low-resolution images. However, there are several computational methods that can be used to synthesize the high-resolution image, and previously, it has been unclear which methods work best for the particular case of small-particle sensing. Here, we quantify the SNR achieved in small-particle sensing using regularized gradient-descent optimization method, where the regularization is based on cardinal-neighbor differences, Bayer-pattern noise reduction, or sparsity in the image. In particular, we find that gradient-descent with sparsity-based regularization works best for small-particle sensing. These computational approaches were evaluated on images acquired using a lens-free microscope that we assembled from an off-the-shelf LED array and color image sensor. Compared to other lens-free imaging systems, our hardware integration, calibration, and sample preparation are particularly simple. We believe our results will help to enable the best performance in lens-free holographic sensing.

Images of a Loving God and Sense of Meaning in Life

ERIC Educational Resources Information Center

Stroope, Samuel; Draper, Scott; Whitehead, Andrew L.

2013-01-01

Although prior studies have documented a positive association between religiosity and sense of meaning in life, the role of specific religious beliefs is currently unclear. Past research on images of God suggests that loving images of God will positively correlate with a sense of meaning and purpose. Mechanisms for this hypothesized relationship…

Polarimetric and Indoor Imaging Fusion Based on Compressive Sensing

DTIC Science & Technology

2013-04-01

Signal Process., vol. 57, no. 6, pp. 2275-2284, 2009. [20] A. Gurbuz, J. McClellan, and W. Scott, Jr., "Compressive sensing for subsurface imaging using...SciTech Publishing, 2010, pp. 922- 938. [45] A. C. Gurbuz, J. H. McClellan, and W. R. Scott, Jr., "Compressive sensing for subsurface imaging using

Classification of high resolution remote sensing image based on geo-ontology and conditional random fields

NASA Astrophysics Data System (ADS)

Hong, Liang

2013-10-01

The availability of high spatial resolution remote sensing data provides new opportunities for urban land-cover classification. More geometric details can be observed in the high resolution remote sensing image, Also Ground objects in the high resolution remote sensing image have displayed rich texture, structure, shape and hierarchical semantic characters. More landscape elements are represented by a small group of pixels. Recently years, the an object-based remote sensing analysis methodology is widely accepted and applied in high resolution remote sensing image processing. The classification method based on Geo-ontology and conditional random fields is presented in this paper. The proposed method is made up of four blocks: (1) the hierarchical ground objects semantic framework is constructed based on geoontology; (2) segmentation by mean-shift algorithm, which image objects are generated. And the mean-shift method is to get boundary preserved and spectrally homogeneous over-segmentation regions ;(3) the relations between the hierarchical ground objects semantic and over-segmentation regions are defined based on conditional random fields framework ;(4) the hierarchical classification results are obtained based on geo-ontology and conditional random fields. Finally, high-resolution remote sensed image data -GeoEye, is used to testify the performance of the presented method. And the experimental results have shown the superiority of this method to the eCognition method both on the effectively and accuracy, which implies it is suitable for the classification of high resolution remote sensing image.

Specific coil design for SENSE: a six-element cardiac array.

PubMed

Weiger, M; Pruessmann, K P; Leussler, C; Röschmann, P; Boesiger, P

2001-03-01

In sensitivity encoding (SENSE), the effects of inhomogeneous spatial sensitivity of surface coils are utilized for signal localization in addition to common Fourier encoding using magnetic field gradients. Unlike standard Fourier MRI, SENSE images exhibit an inhomogeneous noise distribution, which crucially depends on the geometrical sensitivity relations of the coils used. Thus, for optimum signal-to-noise-ratio (SNR) and noise homogeneity, specialized coil configurations are called for. In this article we study the implications of SENSE imaging for coil layout by means of simulations and imaging experiments in a phantom and in vivo. New, specific design principles are identified. For SENSE imaging, the elements of a coil array should be smaller than for common phased-array imaging. Furthermore, adjacent coil elements should not overlap. Based on the findings of initial investigations, a configuration of six coils was designed and built specifically for cardiac applications. The in vivo evaluation of this array showed a considerable SNR increase in SENSE images, as compared with a conventional array. Magn Reson Med 45:495-504, 2001. Copyright 2001 Wiley-Liss, Inc.

Secure distribution for high resolution remote sensing images

NASA Astrophysics Data System (ADS)

Liu, Jin; Sun, Jing; Xu, Zheng Q.

2010-09-01

The use of remote sensing images collected by space platforms is becoming more and more widespread. The increasing value of space data and its use in critical scenarios call for adoption of proper security measures to protect these data against unauthorized access and fraudulent use. In this paper, based on the characteristics of remote sensing image data and application requirements on secure distribution, a secure distribution method is proposed, including users and regions classification, hierarchical control and keys generation, and multi-level encryption based on regions. The combination of the three parts can make that the same remote sensing images after multi-level encryption processing are distributed to different permission users through multicast, but different permission users can obtain different degree information after decryption through their own decryption keys. It well meets user access control and security needs in the process of high resolution remote sensing image distribution. The experimental results prove the effectiveness of the proposed method which is suitable for practical use in the secure transmission of remote sensing images including confidential information over internet.

Application of Convolutional Neural Network in Classification of High Resolution Agricultural Remote Sensing Images

NASA Astrophysics Data System (ADS)

Yao, C.; Zhang, Y.; Zhang, Y.; Liu, H.

2017-09-01

With the rapid development of Precision Agriculture (PA) promoted by high-resolution remote sensing, it makes significant sense in management and estimation of agriculture through crop classification of high-resolution remote sensing image. Due to the complex and fragmentation of the features and the surroundings in the circumstance of high-resolution, the accuracy of the traditional classification methods has not been able to meet the standard of agricultural problems. In this case, this paper proposed a classification method for high-resolution agricultural remote sensing images based on convolution neural networks(CNN). For training, a large number of training samples were produced by panchromatic images of GF-1 high-resolution satellite of China. In the experiment, through training and testing on the CNN under the toolbox of deep learning by MATLAB, the crop classification finally got the correct rate of 99.66 % after the gradual optimization of adjusting parameter during training. Through improving the accuracy of image classification and image recognition, the applications of CNN provide a reference value for the field of remote sensing in PA.

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

NASA Astrophysics Data System (ADS)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

Feasibility of 4D flow MR imaging of the brain with either Cartesian y-z radial sampling or k-t SENSE: comparison with 4D Flow MR imaging using SENSE.

PubMed

Sekine, Tetsuro; Amano, Yasuo; Takagi, Ryo; Matsumura, Yoshio; Murai, Yasuo; Kumita, Shinichiro

2014-01-01

A drawback of time-resolved 3-dimensional phase contrast magnetic resonance (4D Flow MR) imaging is its lengthy scan time for clinical application in the brain. We assessed the feasibility for flow measurement and visualization of 4D Flow MR imaging using Cartesian y-z radial sampling and that using k-t sensitivity encoding (k-t SENSE) by comparison with the standard scan using SENSE. Sixteen volunteers underwent 3 types of 4D Flow MR imaging of the brain using a 3.0-tesla scanner. As the standard scan, 4D Flow MR imaging with SENSE was performed first and then followed by 2 types of acceleration scan-with Cartesian y-z radial sampling and with k-t SENSE. We measured peak systolic velocity (PSV) and blood flow volume (BFV) in 9 arteries, and the percentage of particles arriving from the emitter plane at the target plane in 3 arteries, visually graded image quality in 9 arteries, and compared these quantitative and visual data between the standard scan and each acceleration scan. 4D Flow MR imaging examinations were completed in all but one volunteer, who did not undergo the last examination because of headache. Each acceleration scan reduced scan time by 50% compared with the standard scan. The k-t SENSE imaging underestimated PSV and BFV (P < 0.05). There were significant correlations for PSV and BFV between the standard scan and each acceleration scan (P < 0.01). The percentage of particles reaching the target plane did not differ between the standard scan and each acceleration scan. For visual assessment, y-z radial sampling deteriorated the image quality of the 3 arteries. Cartesian y-z radial sampling is feasible for measuring flow, and k-t SENSE offers sufficient flow visualization; both allow acquisition of 4D Flow MR imaging with shorter scan time.

Method and apparatus for the simultaneous display and correlation of independently generated images

DOEpatents

Vaitekunas, Jeffrey J.; Roberts, Ronald A.

1991-01-01

An apparatus and method for location by location correlation of multiple images from Non-Destructive Evaluation (NDE) and other sources. Multiple images of a material specimen are displayed on one or more monitors of an interactive graphics system. Specimen landmarks are located in each image and mapping functions from a reference image to each other image are calcuated using the landmark locations. A location selected by positioning a cursor in the reference image is mapped to the other images and location identifiers are simultaneously displayed in those images. Movement of the cursor in the reference image causes simultaneous movement of the location identifiers in the other images to positions corresponding to the location of the reference image cursor.

Simultaneous imaging of neural activity in three dimensions

PubMed Central

Quirin, Sean; Jackson, Jesse; Peterka, Darcy S.; Yuste, Rafael

2014-01-01

We introduce a scanless optical method to image neuronal activity in three dimensions simultaneously. Using a spatial light modulator and a custom-designed phase mask, we illuminate and collect light simultaneously from different focal planes and perform calcium imaging of neuronal activity in vitro and in vivo. This method, combining structured illumination with volume projection imaging, could be used as a technological platform for brain activity mapping. PMID:24772066

Global-scale Observations of the Limb and Disk (GOLD) Mission -Ultraviolet Remote Sensing of Earth's Space Environment from Geostationary Orbit

NASA Astrophysics Data System (ADS)

Burns, A. G.; Eastes, R.

2017-12-01

The GOLD mission of opportunity will fly a far ultraviolet imaging spectrograph in geostationary (GEO) orbit as a hosted payload. The mission is scheduled for launch in late January 2018 on SES-14, a commercial communications satellite that will be stationed over eastern South America at 47.5 degrees west longitude. GOLD is on schedule to be the first NASA science mission to fly as a hosted payload on a commercial communications satellite. The GOLD imager has two identical channels. Each channel can scan the full disk at a 30 minute cadence, making spectral images of Earth's UV emission from 132 to 162 nm, as well as make a measurement on the Earth's limb. Remote sensing techniques that have been proven on previous Low Earth Orbit (LEO) missions will be used to derive fundamental parameters for the neutral and ionized space environment. Parameters that will be derived include composition (O/N2 ratio) and temperature of the neutral atmosphere on the dayside disk. On the nightside, peak electron densities will be obtained in the low latitude ionosphere. Many of the algorithms developed for the mission are extensions of ones used on previous earth and planetary missions, with modifications for observations from geostationary orbit. All the algorithms have been tested using simulated observations based on the actual instrument performance. From geostationary orbit, GOLD can repeatedly image the same geographic locations over most of the hemisphere at a cadence comparable to that of the T-I system (order of an hour). Such time resolution and spatial coverage will allow the mission to track the changes due to geomagnetic storms, variations in solar extreme ultraviolet radiation, and forcing from the lower atmosphere. In addition to providing a new perspective by being able to repeatedly remotely sense the same hemisphere at a high cadence, GOLD's simultaneous measurements of not only composition but also temperatures across the disk will provide a valuable, new parameter for understanding of how the T-I system responds to forcing from both the sun and the lower atmosphere.

FAST: framework for heterogeneous medical image computing and visualization.

PubMed

Smistad, Erik; Bozorgi, Mohammadmehdi; Lindseth, Frank

2015-11-01

Computer systems are becoming increasingly heterogeneous in the sense that they consist of different processors, such as multi-core CPUs and graphic processing units. As the amount of medical image data increases, it is crucial to exploit the computational power of these processors. However, this is currently difficult due to several factors, such as driver errors, processor differences, and the need for low-level memory handling. This paper presents a novel FrAmework for heterogeneouS medical image compuTing and visualization (FAST). The framework aims to make it easier to simultaneously process and visualize medical images efficiently on heterogeneous systems. FAST uses common image processing programming paradigms and hides the details of memory handling from the user, while enabling the use of all processors and cores on a system. The framework is open-source, cross-platform and available online. Code examples and performance measurements are presented to show the simplicity and efficiency of FAST. The results are compared to the insight toolkit (ITK) and the visualization toolkit (VTK) and show that the presented framework is faster with up to 20 times speedup on several common medical imaging algorithms. FAST enables efficient medical image computing and visualization on heterogeneous systems. Code examples and performance evaluations have demonstrated that the toolkit is both easy to use and performs better than existing frameworks, such as ITK and VTK.

Multifunctional Catheters Combining Intracardiac Ultrasound Imaging and Electrophysiology Sensing

PubMed Central

Stephens, Douglas N.; Cannata, Jonathan; Liu, Ruibin; Zhao, Jian Zhong; Shung, K. Kirk; Nguyen, Hien; Chia, Raymond; Dentinger, Aaron; Wildes, Douglas; Thomenius, Kai E.; Mahajan, Aman; Shivkumar, Kalyanam; Kim, Kang; O’Donnell, Matthew; Nikoozadeh, Amin; Oralkan, Omer; Khuri-Yakub, Pierre T.; Sahn, David J.

2015-01-01

A family of 3 multifunctional intracardiac imaging and electrophysiology (EP) mapping catheters has been in development to help guide diagnostic and therapeutic intracardiac EP procedures. The catheter tip on the first device includes a 7.5 MHz, 64-element, side-looking phased array for high resolution sector scanning. The second device is a forward-looking catheter with a 24-element 14 MHz phased array. Both of these catheters operate on a commercial imaging system with standard software. Multiple EP mapping sensors were mounted as ring electrodes near the arrays for electrocardiographic synchronization of ultrasound images and used for unique integration with EP mapping technologies. To help establish the catheters’ ability for integration with EP interventional procedures, tests were performed in vivo in a porcine animal model to demonstrate both useful intracardiac echocardiographic (ICE) visualization and simultaneous 3-D positional information using integrated electroanatomical mapping techniques. The catheters also performed well in high frame rate imaging, color flow imaging, and strain rate imaging of atrial and ventricular structures. The companion paper of this work discusses the catheter design of the side-looking catheter with special attention to acoustic lens design. The third device in development is a 10 MHz forward-looking ring array that is to be mounted at the distal tip of a 9F catheter to permit use of the available catheter lumen for adjunctive therapy tools. PMID:18986948

Multifunctional catheters combining intracardiac ultrasound imaging and electrophysiology sensing.

PubMed

Stephens, D N; Cannata, J; Liu, Ruibin; Zhao, Jian Zhong; Shung, K K; Nguyen, Hien; Chia, R; Dentinger, A; Wildes, D; Thomenius, K E; Mahajan, A; Shivkumar, K; Kim, Kang; O'Donnell, M; Nikoozadeh, A; Oralkan, O; Khuri-Yakub, P T; Sahn, D J

2008-07-01

A family of 3 multifunctional intracardiac imaging and electrophysiology (EP) mapping catheters has been in development to help guide diagnostic and therapeutic intracardiac EP procedures. The catheter tip on the first device includes a 7.5 MHz, 64-element, side-looking phased array for high resolution sector scanning. The second device is a forward-looking catheter with a 24-element 14 MHz phased array. Both of these catheters operate on a commercial imaging system with standard software. Multiple EP mapping sensors were mounted as ring electrodes near the arrays for electrocardiographic synchronization of ultrasound images and used for unique integration with EP mapping technologies. To help establish the catheters' ability for integration with EP interventional procedures, tests were performed in vivo in a porcine animal model to demonstrate both useful intracardiac echocardiographic (ICE) visualization and simultaneous 3-D positional information using integrated electroanatomical mapping techniques. The catheters also performed well in high frame rate imaging, color flow imaging, and strain rate imaging of atrial and ventricular structures. The companion paper of this work discusses the catheter design of the side-looking catheter with special attention to acoustic lens design. The third device in development is a 10 MHz forward-looking ring array that is to be mounted at the distal tip of a 9F catheter to permit use of the available catheter lumen for adjunctive therapy tools.

Automatically assisting human memory: a SenseCam browser.

PubMed

Doherty, Aiden R; Moulin, Chris J A; Smeaton, Alan F

2011-10-01

SenseCams have many potential applications as tools for lifelogging, including the possibility of use as a memory rehabilitation tool. Given that a SenseCam can log hundreds of thousands of images per year, it is critical that these be presented to the viewer in a manner that supports the aims of memory rehabilitation. In this article we report a software browser constructed with the aim of using the characteristics of memory to organise SenseCam images into a form that makes the wealth of information stored on SenseCam more accessible. To enable a large amount of visual information to be easily and quickly assimilated by a user, we apply a series of automatic content analysis techniques to structure the images into "events", suggest their relative importance, and select representative images for each. This minimises effort when browsing and searching. We provide anecdotes on use of such a system and emphasise the need for SenseCam images to be meaningfully sorted using such a browser.

a Hadoop-Based Distributed Framework for Efficient Managing and Processing Big Remote Sensing Images

NASA Astrophysics Data System (ADS)

Wang, C.; Hu, F.; Hu, X.; Zhao, S.; Wen, W.; Yang, C.

2015-07-01

Various sensors from airborne and satellite platforms are producing large volumes of remote sensing images for mapping, environmental monitoring, disaster management, military intelligence, and others. However, it is challenging to efficiently storage, query and process such big data due to the data- and computing- intensive issues. In this paper, a Hadoop-based framework is proposed to manage and process the big remote sensing data in a distributed and parallel manner. Especially, remote sensing data can be directly fetched from other data platforms into the Hadoop Distributed File System (HDFS). The Orfeo toolbox, a ready-to-use tool for large image processing, is integrated into MapReduce to provide affluent image processing operations. With the integration of HDFS, Orfeo toolbox and MapReduce, these remote sensing images can be directly processed in parallel in a scalable computing environment. The experiment results show that the proposed framework can efficiently manage and process such big remote sensing data.

Glucose sensing in the peritoneal space offers faster kinetics than sensing in the subcutaneous space.

PubMed

Burnett, Daniel R; Huyett, Lauren M; Zisser, Howard C; Doyle, Francis J; Mensh, Brett D

2014-07-01

The paramount goal in the treatment of type 1 diabetes is the maintenance of normoglycemia. Continuous glucose monitoring (CGM) technologies enable frequent sensing of glucose to inform exogenous insulin delivery timing and dosages. The most commonly available CGMs are limited by the physiology of the subcutaneous space in which they reside. The very same advantages of this minimally invasive approach are disadvantages with respect to speed. Because subcutaneous blood flow is sensitive to local fluctuations (e.g., temperature, mechanical pressure), subcutaneous sensing can be slow and variable. We propose the use of a more central, physiologically stable body space for CGM: the intraperitoneal space. We compared the temporal response characteristics of simultaneously placed subcutaneous and intraperitoneal sensors during intravenous glucose tolerance tests in eight swine. Using compartmental modeling based on simultaneous intravenous sensing, blood draws, and intraarterial sensing, we found that intraperitoneal kinetics were more than twice as fast as subcutaneous kinetics (mean time constant of 5.6 min for intraperitoneal vs. 12.4 min for subcutaneous). Combined with the known faster kinetics of intraperitoneal insulin delivery over subcutaneous delivery, our findings suggest that artificial pancreas technologies may be optimized by sensing glucose and delivering insulin in the intraperitoneal space. © 2014 by the American Diabetes Association.

Glucose Sensing in the Peritoneal Space Offers Faster Kinetics Than Sensing in the Subcutaneous Space

PubMed Central

Burnett, Daniel R.; Huyett, Lauren M.; Zisser, Howard C.; Doyle, Francis J.

2014-01-01

The paramount goal in the treatment of type 1 diabetes is the maintenance of normoglycemia. Continuous glucose monitoring (CGM) technologies enable frequent sensing of glucose to inform exogenous insulin delivery timing and dosages. The most commonly available CGMs are limited by the physiology of the subcutaneous space in which they reside. The very same advantages of this minimally invasive approach are disadvantages with respect to speed. Because subcutaneous blood flow is sensitive to local fluctuations (e.g., temperature, mechanical pressure), subcutaneous sensing can be slow and variable. We propose the use of a more central, physiologically stable body space for CGM: the intraperitoneal space. We compared the temporal response characteristics of simultaneously placed subcutaneous and intraperitoneal sensors during intravenous glucose tolerance tests in eight swine. Using compartmental modeling based on simultaneous intravenous sensing, blood draws, and intraarterial sensing, we found that intraperitoneal kinetics were more than twice as fast as subcutaneous kinetics (mean time constant of 5.6 min for intraperitoneal vs. 12.4 min for subcutaneous). Combined with the known faster kinetics of intraperitoneal insulin delivery over subcutaneous delivery, our findings suggest that artificial pancreas technologies may be optimized by sensing glucose and delivering insulin in the intraperitoneal space. PMID:24622798

Information recovery through image sequence fusion under wavelet transformation

NASA Astrophysics Data System (ADS)

He, Qiang

2010-04-01

Remote sensing is widely applied to provide information of areas with limited ground access with applications such as to assess the destruction from natural disasters and to plan relief and recovery operations. However, the data collection of aerial digital images is constrained by bad weather, atmospheric conditions, and unstable camera or camcorder. Therefore, how to recover the information from the low-quality remote sensing images and how to enhance the image quality becomes very important for many visual understanding tasks, such like feature detection, object segmentation, and object recognition. The quality of remote sensing imagery can be improved through meaningful combination of the employed images captured from different sensors or from different conditions through information fusion. Here we particularly address information fusion to remote sensing images under multi-resolution analysis in the employed image sequences. The image fusion is to recover complete information by integrating multiple images captured from the same scene. Through image fusion, a new image with high-resolution or more perceptive for human and machine is created from a time series of low-quality images based on image registration between different video frames.

Atmospheric aerosol and gas sensing using Scheimpflug lidar

NASA Astrophysics Data System (ADS)

Mei, Liang; Brydegaard, Mikkel

2015-04-01

This work presents a new lidar technique for atmospheric remote sensing based on Scheimpflug principle, which describes the relationship between nonparallel image- and object-planes[1]. When a laser beam is transmitted into the atmosphere, the implication is that the backscattering echo of the entire illuminated probe volume can be in focus simultaneously without diminishing the aperture. The range-resolved backscattering echo can be retrieved by using a tilted line scan or two-dimensional CCD/CMOS camera. Rather than employing nanosecond-pulsed lasers, cascade detectors, and MHz signal sampling, all of high cost and complexity, we have developed a robust and inexpensive atmospheric lidar system based on compact laser diodes and array detectors. We present initial applications of the Scheimpflug lidar for atmospheric aerosol monitoring in bright sunlight, with a 3 W, 808 nm CW laser diode. Kilohertz sampling rates are also achieved with applications for wind speed and entomology [2]. Further, a proof-of-principle demonstration of differential absorption lidar (DIAL) based on the Scheimpflug lidar technique is presented [3]. By utilizing a 30 mW narrow band CW laser diode emitting at around 760 nm, the detailed shape of an oxygen absorption line can be resolved remotely with an integration time of 6 s and measurement cycle of 1 minute during night time. The promising results demonstrated in this work show potential for the Scheimpflug lidar technique for remote atmospheric aerosol and gas sensing, and renews hope for robust and realistic instrumentation for atmospheric lidar sensing. [1] F. Blais, "Review of 20 years of range sensor development," Journal of Electronic Imaging, vol. 13, pp. 231-243, Jan 2004. [2] M. Brydegaard, A. Gebru, and S. Svanberg, "Super resolution laser radar with blinking atmospheric particles - application to interacting flying insects " Progress In Electromagnetics Research, vol. 147, pp. 141-151, 2014. [3] L. Mei and M. Brydegaard, "Contineous-wave differential absorption lidar," Submitted to Laser and Photonics Reviews, 2014.

AXIOM: Advanced X-ray Imaging of the Magnetosphere

NASA Technical Reports Server (NTRS)

Branduardi-Raymont, G.; Sembay, S. F.; Eastwood, J. P.; Sibeck, D. G.; Abbey, A.; Brown, P.; Carter, J. A.; Carr, C. M.; Forsyth, C.; Kataria, D.;

AXIOM: Advanced X-Ray Imaging of the Magnetosphere

NASA Technical Reports Server (NTRS)

Branduardi-Raymont, G.; Sembay, S. F.; Eastwood, J. P.; Sibeck, D. G.; Abbey, A.; Brown, P.; Carter, J. A.; Carr, C. M.; Forsyth, C.; Kataria, D.;

Detecting bugweed (Solanum mauritianum) abundance in plantation forestry using multisource remote sensing

NASA Astrophysics Data System (ADS)

Peerbhay, Kabir; Mutanga, Onisimo; Lottering, Romano; Bangamwabo, Victor; Ismail, Riyad

2016-11-01

The invasive weed Solanum mauritianum (bugweed) has infested large areas of plantation forests in KwaZulu-Natal, South Africa. Bugweed often forms dense infestations and rapidly capitalises on available natural resources hindering the production of forest resources. Precise assessment of bugweed canopy cover, especially at low abundance cover, is essential to an effective weed management strategy. In this study, the utility of AISA Eagle airborne hyperspectral data (393-994 nm) with the new generation Worldview-2 multispectral sensor (427-908 nm) was compared to detect the abundance of bugweed cover within the Hodgsons Sappi forest plantation. Using sparse partial least squares discriminant analysis (SPLS-DA), the best detection results were obtained when performing discrimination using the remotely sensing images combined with LiDAR. Overall classification accuracies subsequently improved by 10% and 11.67% for AISA and Worldview-2 respectively, with improved detection accuracies for bugweed cover densities as low as 5%. The incorporation of LiDAR worked well within the SPLS-DA framework for detecting the abundance of bugweed cover using remotely sensed data. In addition, the algorithm performed simultaneous dimension reduction and variable selection successfully whereby wavelengths in the visible (393-670 nm) and red-edge regions (725-734 nm) of the spectrum were the most effective.

Magnetic Resonance-based Motion Correction for Quantitative PET in Simultaneous PET-MR Imaging.

PubMed

Rakvongthai, Yothin; El Fakhri, Georges

2017-07-01

Motion degrades image quality and quantitation of PET images, and is an obstacle to quantitative PET imaging. Simultaneous PET-MR offers a tool that can be used for correcting the motion in PET images by using anatomic information from MR imaging acquired concurrently. Motion correction can be performed by transforming a set of reconstructed PET images into the same frame or by incorporating the transformation into the system model and reconstructing the motion-corrected image. Several phantom and patient studies have validated that MR-based motion correction strategies have great promise for quantitative PET imaging in simultaneous PET-MR. Copyright © 2017 Elsevier Inc. All rights reserved.

A new hyperspectral image compression paradigm based on fusion

NASA Astrophysics Data System (ADS)

Guerra, Raúl; Melián, José; López, Sebastián.; Sarmiento, Roberto

2016-10-01

The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.

Active Damping of a Piezoelectric Tube Scanner using Self-Sensing Piezo Actuation

PubMed Central

Kuiper, S.; Schitter, G.

2010-01-01

In most Atomic Force Microscopes (AFM), a piezoelectric tube scanner is used to position the sample underneath the measurement probe. Oscillations stemming from the weakly damped resonances of the tube scanner are a major source of image distortion, putting a limitation on the achievable imaging speed. This paper demonstrates active damping of these oscillations in multiple scanning axes without the need for additional position sensors. By connecting the tube scanner in a capacitive bridge circuit the scanner oscillations can be measured in both scanning axes, using the same piezo material as an actuator and sensor simultaneously. In order to compensate for circuit imbalance caused by hysteresis in the piezo element, an adaptive balancing circuit is used. The obtained measurement signal is used for feedback control, reducing the resonance peaks in both scanning axes by 18 dB and the cross-coupling at those frequencies by 30 dB. Experimental results demonstrate a significant reduction in scanner oscillations when applying the typical triangular scanning signals, as well as a strong reduction in coupling induced oscillations. Recorded AFM images show a considerable reduction in image distortion due to the proposed control method, enabling artifact free AFM imaging at a speed of 122 lines per second with a standard piezoelectric tube scanner. PMID:26412944

Measuring spatial and temporal Ca2+ signals in Arabidopsis plants.

PubMed

Zhu, Xiaohong; Taylor, Aaron; Zhang, Shenyu; Zhang, Dayong; Feng, Ying; Liang, Gaimei; Zhu, Jian-Kang

2014-09-02

Developmental and environmental cues induce Ca(2+) fluctuations in plant cells. Stimulus-specific spatial-temporal Ca(2+) patterns are sensed by cellular Ca(2+) binding proteins that initiate Ca(2+) signaling cascades. However, we still know little about how stimulus specific Ca(2+) signals are generated. The specificity of a Ca(2+) signal may be attributed to the sophisticated regulation of the activities of Ca(2+) channels and/or transporters in response to a given stimulus. To identify these cellular components and understand their functions, it is crucial to use systems that allow a sensitive and robust recording of Ca(2+) signals at both the tissue and cellular levels. Genetically encoded Ca(2+) indicators that are targeted to different cellular compartments have provided a platform for live cell confocal imaging of cellular Ca(2+) signals. Here we describe instructions for the use of two Ca(2+) detection systems: aequorin based FAS (film adhesive seedlings) luminescence Ca(2+) imaging and case12 based live cell confocal fluorescence Ca(2+) imaging. Luminescence imaging using the FAS system provides a simple, robust and sensitive detection of spatial and temporal Ca(2+) signals at the tissue level, while live cell confocal imaging using Case12 provides simultaneous detection of cytosolic and nuclear Ca(2+) signals at a high resolution.

Mixed C18 and C1 modification on an optical fiber for chromatographic sensing.

PubMed

Zhou, Leiji; Wang, Kemin; Zuo, Xinbing; Choi, Martin M F; Chen, Yunqing; Huang, Shasheng

2003-09-01

An optical fiber-chromatographic sensor, aiming at simultaneous and selective response to multiple components following a chromatographic separation, is described. We report an improved approach for immobilization of octadecyl (C(18)) and methyl (C(1)) moieties as stationary phase on an optical fiber suitable as a sensing phase for organic solutes. By this approach, the stability and lifetime of the sensing layer as well as the detectability and retention behavior of the chromatographic sensor could be improved. Infrared spectroscopy was employed to confirm the presence of C(18) and C(1) moieties on the modified surface of the optical fiber. The chromatographic sensor was applied, with good sensitivity and chemical selectivity, to the simultaneous separation and detection of bromobenzene and toluene, using water as the mobile phase.

Hybrid Fabry-Perot interferometer for simultaneous liquid refractive index and temperature measurement.

PubMed

Xu, Ben; Yang, Yi; Jia, Zhenbao; Wang, D N

2017-06-26

A compact and high sensitivity sensor with a fiber-tip structure is proposed and demonstrated for simultaneously liquid refractive index (RI) and temperature sensing. The device is fabricated by inserting a tiny segment of capillary tube between single-mode fibers (SMFs) to form two cascaded Fabry-Perot interferometers (FPIs). The theoretical and experimental results demonstrate that the ambient liquid RI and temperature can be simultaneously determined by the intensity and shift of the resonant wavelength in the reflection spectrum. Our proposed device has the highest RI sensitivity of ~216.37 dB/RIU at the RI value of 1.30; a high spatial resolution owing to its compact size (with dimension <400 μm) makes it promising for high precision bio/chemical sensing applications.

Intelligent Detection of Structure from Remote Sensing Images Based on Deep Learning Method

NASA Astrophysics Data System (ADS)

Xin, L.

2018-04-01

Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sensing image samples and verifies the feasibility of building extraction via experiments.

A Dual Modality System for Simultaneous Fluorescence and Positron Emission Tomography Imaging of Small Animals

NASA Astrophysics Data System (ADS)

Liu, Shuangquan; Zhang, Bin; Wang, Xin; Li, Lin; Chen, Yan; Liu, Xin; Liu, Fei; Shan, Baoci; Bai, Jing

2011-02-01

A dual-modality imaging system for simultaneous fluorescence molecular tomography (FMT) and positron emission tomography (PET) of small animals has been developed. The system consists of a noncontact 360°-projection FMT module and a flat panel detector pair based PET module, which are mounted orthogonally for the sake of eliminating cross interference. The FMT images and PET data are simultaneously acquired by employing dynamic sampling mode. Phantom experiments, in which the localization and range of radioactive and fluorescence probes are exactly indicated, have been carried out to verify the feasibility of the system. An experimental tumor-bearing mouse is also scanned using the dual-modality simultaneous imaging system, the preliminary fluorescence tomographic images and PET images demonstrate the in vivo performance of the presented dual-modality system.

Advances in Fluorescence Sensing Systems for the Remote Assessment of Nitrogen Supply in Field Corn

NASA Technical Reports Server (NTRS)

Corp, L. A.; Chappelle, E. W.; McMurtrey, J. E.; Daughtry, C. S. T.; Kim, M. S.

2000-01-01

The studies described herein were conducted to better define changes in fluorescence properties of leaves from field grown corn (Zea mays L.) as they relate to varying levels of nitrogen (N) fertilization. This research was directed toward: 1) providing a remote non-destructive sensing technique to aid in the determination of optimal rates of N fertilization in corn crops and, 2) defining parameters for further development of fluorescence instrumentation to be operated remotely at field canopy levels. Fluorescence imaging bands centered in the blue (450 nm), green (525 nm), red (680 nm), and far-red (740 nm) and ratios of these bands were compared with the following plant parameters: rates of photosynthesis, N:C ratio, pigment concentrations, and grain yields. Both the fluorescence and physiological measures exhibited similar curvilinear responses to N fertilization level while significant linear correlations were obtained among fluorescence bands and band ratios to certain physiological measures of plant productivity. The red / blue, red / green, far-red / blue, far-red /green fluorescence ratios are well suited for remote observation and provided high correlations to grain yield, LAI, N:C, and chlorophyll contents. The results from this investigation indicate that fluorescence technology could aid in the determination of N fertilization requirements for corn. This discussion will also address design concepts and preliminary field trials of a mobile field-based Laser Induced Fluorescence Imaging System (LIFIS) capable of simultaneously acquiring images of four fluorescence emission bands from areas of plant canopies equaling 1 sq m and greater without interference of ambient solar radiation.

LORAKS Makes Better SENSE: Phase-Constrained Partial Fourier SENSE Reconstruction without Phase Calibration

PubMed Central

Kim, Tae Hyung; Setsompop, Kawin; Haldar, Justin P.

2016-01-01

Purpose Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. Theory and Methods The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly-accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely-used calibrationless uniformly-undersampled trajectories. Results Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. Conclusion The SENSE-LORAKS framework provides promising new opportunities for highly-accelerated MRI. PMID:27037836

Coding Strategies and Implementations of Compressive Sensing

NASA Astrophysics Data System (ADS)

Tsai, Tsung-Han

This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others. This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system. Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity. Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.

Digital sensing and sizing of vesicular stomatitis virus pseudotypes in complex media: a model for Ebola and Marburg detection.

PubMed

Daaboul, George G; Lopez, Carlos A; Chinnala, Jyothsna; Goldberg, Bennett B; Connor, John H; Ünlü, M Selim

2014-06-24

Rapid, sensitive, and direct label-free capture and characterization of nanoparticles from complex media such as blood or serum will broadly impact medicine and the life sciences. We demonstrate identification of virus particles in complex samples for replication-competent wild-type vesicular stomatitis virus (VSV), defective VSV, and Ebola- and Marburg-pseudotyped VSV with high sensitivity and specificity. Size discrimination of the imaged nanoparticles (virions) allows differentiation between modified viruses having different genome lengths and facilitates a reduction in the counting of nonspecifically bound particles to achieve a limit-of-detection (LOD) of 5 × 10(3) pfu/mL for the Ebola and Marburg VSV pseudotypes. We demonstrate the simultaneous detection of multiple viruses in a single sample (composed of serum or whole blood) for screening applications and uncompromised detection capabilities in samples contaminated with high levels of bacteria. By employing affinity-based capture, size discrimination, and a "digital" detection scheme to count single virus particles, we show that a robust and sensitive virus/nanoparticle sensing assay can be established for targets in complex samples. The nanoparticle microscopy system is termed the Single Particle Interferometric Reflectance Imaging Sensor (SP-IRIS) and is capable of high-throughput and rapid sizing of large numbers of biological nanoparticles on an antibody microarray for research and diagnostic applications.

REKRIATE: A Knowledge Representation System for Object Recognition and Scene Interpretation

NASA Astrophysics Data System (ADS)

Meystel, Alexander M.; Bhasin, Sanjay; Chen, X.

1990-02-01

What humans actually observe and how they comprehend this information is complex due to Gestalt processes and interaction of context in predicting the course of thinking and enforcing one idea while repressing another. How we extract the knowledge from the scene, what we get from the scene indeed and what we bring from our mechanisms of perception are areas separated by a thin, ill-defined line. The purpose of this paper is to present a system for Representing Knowledge and Recognizing and Interpreting Attention Trailed Entities dubbed as REKRIATE. It will be used as a tool for discovering the underlying principles involved in knowledge representation required for conceptual learning. REKRIATE has some inherited knowledge and is given a vocabulary which is used to form rules for identification of the object. It has various modalities of sensing and has the ability to measure the distance between the objects in the image as well as the similarity between different images of presumably the same object. All sensations received from matrix of different sensors put into an adequate form. The methodology proposed is applicable to not only the pictorial or visual world representation, but to any sensing modality. It is based upon the two premises: a) inseparability of all domains of the world representation including linguistic, as well as those formed by various sensor modalities. and b) representativity of the object at several levels of resolution simultaneously.

Slitless spectroscopy with the James Webb Space Telescope Near-Infrared Camera (JWST NIRCam)

NASA Astrophysics Data System (ADS)

Greene, Thomas P.; Chu, Laurie; Egami, Eiichi; Hodapp, Klaus W.; Kelly, Douglas M.; Leisenring, Jarron; Rieke, Marcia; Robberto, Massimo; Schlawin, Everett; Stansberry, John

2016-07-01

The James Webb Space Telescope near-infrared camera (JWST NIRCam) has two 2.02 x 2.02 fields of view that are capable of either imaging or spectroscopic observations. Either of two R ~ 1500 grisms with orthogonal dispersion directions can be used for slitless spectroscopy over λ = 2.4 - 5.0 μm in each module, and shorter wavelength observations of the same fields can be obtained simultaneously. We present the latest predicted grism sensitivities, saturation limits, resolving power, and wavelength coverage values based on component measurements, instrument tests, and end-to-end modeling. Short wavelength (0.6 - 2.3 μm) imaging observations of the 2.4 - 5.0 μm spectroscopic field can be performed in one of several different filter bands, either in-focus or defocused via weak lenses internal to NIRCam. Alternatively, the possibility of 1.0 - 2.0 μm spectroscopy (simultaneously with 2.4 - 5.0 μm) using dispersed Hartmann sensors (DHSs) is being explored. The grisms, weak lenses, and DHS elements were included in NIRCam primarily for wavefront sensing purposes, but all have significant science applications. Operational considerations including subarray sizes, and data volume limits are also discussed. Finally, we describe spectral simulation tools and illustrate potential scientific uses of the grisms by presenting simulated observations of deep extragalactic fields, galactic dark clouds, and transiting exoplanets.

The Malaysian Robotic Solar Observatory (P29)

NASA Astrophysics Data System (ADS)

Othman, M.; Asillam, M. F.; Ismail, M. K. H.

2006-11-01

Robotic observatory with small telescopes can make significant contributions to astronomy observation. They provide an encouraging environment for astronomers to focus on data analysis and research while at the same time reducing time and cost for observation. The observatory will house the primary 50cm robotic telescope in the main dome which will be used for photometry, spectroscopy and astrometry observation activities. The secondary telescope is a robotic multi-apochromatic refractor (maximum diameter: 15 cm) which will be housed in the smaller dome. This telescope set will be used for solar observation mainly in three different wavelengths simultaneously: the Continuum, H-Alpha and Calcium K-line. The observatory is also equipped with an automated weather station, cloud & rain sensor and all-sky camera to monitor the climatic condition, sense the clouds (before raining) as well as to view real time sky view above the observatory. In conjunction with the Langkawi All-Sky Camera, the observatory website will also display images from the Malaysia - Antarctica All-Sky Camera used to monitor the sky at Scott Base Antarctica. Both all-sky images can be displayed simultaneously to show the difference between the equatorial and Antarctica skies. This paper will describe the Malaysian Robotic Observatory including the systems available and method of access by other astronomers. We will also suggest possible collaboration with other observatories in this region.

Searches over graphs representing geospatial-temporal remote sensing data

DOEpatents

Brost, Randolph; Perkins, David Nikolaus

2018-03-06

Various technologies pertaining to identifying objects of interest in remote sensing images by searching over geospatial-temporal graph representations are described herein. Graphs are constructed by representing objects in remote sensing images as nodes, and connecting nodes with undirected edges representing either distance or adjacency relationships between objects and directed edges representing changes in time. Geospatial-temporal graph searches are made computationally efficient by taking advantage of characteristics of geospatial-temporal data in remote sensing images through the application of various graph search techniques.

A modified approach combining FNEA and watershed algorithms for segmenting remotely-sensed optical images

NASA Astrophysics Data System (ADS)

Liu, Likun

2018-01-01

In the field of remote sensing image processing, remote sensing image segmentation is a preliminary step for later analysis of remote sensing image processing and semi-auto human interpretation, fully-automatic machine recognition and learning. Since 2000, a technique of object-oriented remote sensing image processing method and its basic thought prevails. The core of the approach is Fractal Net Evolution Approach (FNEA) multi-scale segmentation algorithm. The paper is intent on the research and improvement of the algorithm, which analyzes present segmentation algorithms and selects optimum watershed algorithm as an initialization. Meanwhile, the algorithm is modified by modifying an area parameter, and then combining area parameter with a heterogeneous parameter further. After that, several experiments is carried on to prove the modified FNEA algorithm, compared with traditional pixel-based method (FCM algorithm based on neighborhood information) and combination of FNEA and watershed, has a better segmentation result.

Wide-Field Imaging Using Nitrogen Vacancies

NASA Technical Reports Server (NTRS)

Englund, Dirk Robert (Inventor); Trusheim, Matthew Edwin (Inventor)

2017-01-01

Nitrogen vacancies in bulk diamonds and nanodiamonds can be used to sense temperature, pressure, electromagnetic fields, and pH. Unfortunately, conventional sensing techniques use gated detection and confocal imaging, limiting the measurement sensitivity and precluding wide-field imaging. Conversely, the present sensing techniques do not require gated detection or confocal imaging and can therefore be used to image temperature, pressure, electromagnetic fields, and pH over wide fields of view. In some cases, wide-field imaging supports spatial localization of the NVs to precisions at or below the diffraction limit. Moreover, the measurement range can extend over extremely wide dynamic range at very high sensitivity.

Remote sensing: a tool for park planning and management

USGS Publications Warehouse

Draeger, William C.; Pettinger, Lawrence R.

1981-01-01

Remote sensing may be defined as the science of imaging or measuring objects from a distance. More commonly, however, the term is used in reference to the acquisition and use of photographs, photo-like images, and other data acquired from aircraft and satellites. Thus, remote sensing includes the use of such diverse materials as photographs taken by hand from a light aircraft, conventional aerial photographs obtained with a precision mapping camera, satellite images acquired with sophisticated scanning devices, radar images, and magnetic and gravimetric data that may not even be in image form. Remotely sensed images may be color or black and white, can vary in scale from those that cover only a few hectares of the earth's surface to those that cover tens of thousands of square kilometers, and they may be interpreted visually or with the assistance of computer systems. This article attempts to describe several of the commonly available types of remotely sensed data, to discuss approaches to data analysis, and to demonstrate (with image examples) typical applications that might interest managers of parks and natural areas.

Dual-Mode SERS-Fluorescence Immunoassay Using Graphene Quantum Dot Labeling on One-Dimensional Aligned Magnetoplasmonic Nanoparticles.

PubMed

Zou, Fengming; Zhou, Hongjian; Tan, Tran Van; Kim, Jeonghyo; Koh, Kwangnak; Lee, Jaebeom

2015-06-10

A novel dual-mode immunoassay based on surface-enhanced Raman scattering (SERS) and fluorescence was designed using graphene quantum dot (GQD) labels to detect a tuberculosis (TB) antigen, CFP-10, via a newly developed sensing platform of linearly aligned magnetoplasmonic (MagPlas) nanoparticles (NPs). The GQDs were excellent bilabeling materials for simultaneous Raman scattering and photoluminescence (PL). The one-dimensional (1D) alignment of MagPlas NPs simplified the immunoassay process and enabled fast, enhanced signal transduction. With a sandwich-type immunoassay using dual-mode nanoprobes, both SERS signals and fluorescence images were recognized in a highly sensitive and selective manner with a detection limit of 0.0511 pg mL(-1).

Elastico-mechanoluminescence in CaZr(PO4)2:Eu2+ with multiple trap levels.

PubMed

Zhang, Jun-Cheng; Xu, Chao-Nan; Long, Yun-Ze

2013-06-03

We report on a novel elastico-mechanoluminescence (EML) phosphor of CaZr(PO4)2:Eu2+ for simultaneous luminescent sensing and imaging to mechanical load by the light-emitting of Eu2+ ions. The EML properties of CaZr(PO4)2:Eu2+ show an intense luminance (above 15 mcd m(-2)), a low load threshold (below 5 N), a broad measurement range for the dynamic load (up to 2000 N), and an accurate linear relationship of EML intensity against the applied load. The excellent EML characteristics are considered to originate from the piezoelectric crystal structure and the multiple trap levels with appropriate depths. An EML mechanism based on the electrons as the main charge carriers is proposed.

Proceedings of the Scientific Data Compression Workshop

NASA Technical Reports Server (NTRS)

Ramapriyan, H. K. (Editor)

1989-01-01

Continuing advances in space and Earth science requires increasing amounts of data to be gathered from spaceborne sensors. NASA expects to launch sensors during the next two decades which will be capable of producing an aggregate of 1500 Megabits per second if operated simultaneously. Such high data rates cause stresses in all aspects of end-to-end data systems. Technologies and techniques are needed to relieve such stresses. Potential solutions to the massive data rate problems are: data editing, greater transmission bandwidths, higher density and faster media, and data compression. Through four subpanels on Science Payload Operations, Multispectral Imaging, Microwave Remote Sensing and Science Data Management, recommendations were made for research in data compression and scientific data applications to space platforms.

Remote-sensing image encryption in hybrid domains

NASA Astrophysics Data System (ADS)

Zhang, Xiaoqiang; Zhu, Guiliang; Ma, Shilong

2012-04-01

Remote-sensing technology plays an important role in military and industrial fields. Remote-sensing image is the main means of acquiring information from satellites, which always contain some confidential information. To securely transmit and store remote-sensing images, we propose a new image encryption algorithm in hybrid domains. This algorithm makes full use of the advantages of image encryption in both spatial domain and transform domain. First, the low-pass subband coefficients of image DWT (discrete wavelet transform) decomposition are sorted by a PWLCM system in transform domain. Second, the image after IDWT (inverse discrete wavelet transform) reconstruction is diffused with 2D (two-dimensional) Logistic map and XOR operation in spatial domain. The experiment results and algorithm analyses show that the new algorithm possesses a large key space and can resist brute-force, statistical and differential attacks. Meanwhile, the proposed algorithm has the desirable encryption efficiency to satisfy requirements in practice.

An L1-norm phase constraint for half-Fourier compressed sensing in 3D MR imaging.

PubMed

Li, Guobin; Hennig, Jürgen; Raithel, Esther; Büchert, Martin; Paul, Dominik; Korvink, Jan G; Zaitsev, Maxim

2015-10-01

In most half-Fourier imaging methods, explicit phase replacement is used. In combination with parallel imaging, or compressed sensing, half-Fourier reconstruction is usually performed in a separate step. The purpose of this paper is to report that integration of half-Fourier reconstruction into iterative reconstruction minimizes reconstruction errors. The L1-norm phase constraint for half-Fourier imaging proposed in this work is compared with the L2-norm variant of the same algorithm, with several typical half-Fourier reconstruction methods. Half-Fourier imaging with the proposed phase constraint can be seamlessly combined with parallel imaging and compressed sensing to achieve high acceleration factors. In simulations and in in-vivo experiments half-Fourier imaging with the proposed L1-norm phase constraint enables superior performance both reconstruction of image details and with regard to robustness against phase estimation errors. The performance and feasibility of half-Fourier imaging with the proposed L1-norm phase constraint is reported. Its seamless combination with parallel imaging and compressed sensing enables use of greater acceleration in 3D MR imaging.

Design of Restoration Method Based on Compressed Sensing and TwIST Algorithm

NASA Astrophysics Data System (ADS)

Zhang, Fei; Piao, Yan

2018-04-01

In order to improve the subjective and objective quality of degraded images at low sampling rates effectively,save storage space and reduce computational complexity at the same time, this paper proposes a joint restoration algorithm of compressed sensing and two step iterative threshold shrinkage (TwIST). The algorithm applies the TwIST algorithm which used in image restoration to the compressed sensing theory. Then, a small amount of sparse high-frequency information is obtained in frequency domain. The TwIST algorithm based on compressed sensing theory is used to accurately reconstruct the high frequency image. The experimental results show that the proposed algorithm achieves better subjective visual effects and objective quality of degraded images while accurately restoring degraded images.

Development of a fusion approach selection tool

NASA Astrophysics Data System (ADS)

Pohl, C.; Zeng, Y.

2015-06-01

During the last decades number and quality of available remote sensing satellite sensors for Earth observation has grown significantly. The amount of available multi-sensor images along with their increased spatial and spectral resolution provides new challenges to Earth scientists. With a Fusion Approach Selection Tool (FAST) the remote sensing community would obtain access to an optimized and improved image processing technology. Remote sensing image fusion is a mean to produce images containing information that is not inherent in the single image alone. In the meantime the user has access to sophisticated commercialized image fusion techniques plus the option to tune the parameters of each individual technique to match the anticipated application. This leaves the operator with an uncountable number of options to combine remote sensing images, not talking about the selection of the appropriate images, resolution and bands. Image fusion can be a machine and time-consuming endeavour. In addition it requires knowledge about remote sensing, image fusion, digital image processing and the application. FAST shall provide the user with a quick overview of processing flows to choose from to reach the target. FAST will ask for available images, application parameters and desired information to process this input to come out with a workflow to quickly obtain the best results. It will optimize data and image fusion techniques. It provides an overview on the possible results from which the user can choose the best. FAST will enable even inexperienced users to use advanced processing methods to maximize the benefit of multi-sensor image exploitation.

a Method for Simultaneous Aerial and Terrestrial Geodata Acquisition for Corridor Mapping

NASA Astrophysics Data System (ADS)

Molina, P.; Blázquez, M.; Sastre, J.; Colomina, I.

2015-08-01

In this paper, we present mapKITE, a new mobile, simultaneous terrestrial and aerial, geodata collection and post-processing method. On one side, the method combines a terrestrial mobile mapping system (TMMS) with an unmanned aerial mapping one, both equipped with remote sensing payloads (at least, a nadir-looking visible-band camera in the UA) by means of which aerial and terrestrial geodata are acquired simultaneously. This tandem geodata acquisition system is based on a terrestrial vehicle (TV) and on an unmanned aircraft (UA) linked by a 'virtual tether', that is, a mechanism based on the real-time supply of UA waypoints by the TV. By means of the TV-to-UA tether, the UA follows the TV keeping a specific relative TV-to-UA spatial configuration enabling the simultaneous operation of both systems to obtain highly redundant and complementary geodata. On the other side, mapKITE presents a novel concept for geodata post-processing favoured by the rich geometrical aspects derived from the mapKITE tandem simultaneous operation. The approach followed for sensor orientation and calibration of the aerial images captured by the UA inherits the principles of Integrated Sensor Orientation (ISO) and adds the pointing-and-scaling photogrammetric measurement of a distinctive element observed in every UA image, which is a coded target mounted on the roof of the TV. By means of the TV navigation system, the orientation of the TV coded target is performed and used in the post-processing UA image orientation approach as a Kinematic Ground Control Point (KGCP). The geometric strength of a mapKITE ISO network is therefore high as it counts with the traditional tie point image measurements, static ground control points, kinematic aerial control and the new point-and-scale measurements of the KGCPs. With such a geometry, reliable system and sensor orientation and calibration and eventual further reduction of the number of traditional ground control points is feasible. The different technical concepts, challenges and breakthroughs behind mapKITE are presented in this paper, such as the TV-to-UA virtual tether and the use of KGCP measurements for UA sensor orientation. In addition, the use in mapKITE of new European GNSS signals such as the Galileo E5 AltBOC is discussed. Because of the critical role of GNSS technologies and the potential impact on the corridor mapping market, the European Commission and the European GNSS Agency, in the frame of the European Union Framework Programme for Research and Innovation "Horizon 2020," have recently awarded the "mapKITE" project to an international consortium of organizations coordinated by GeoNumerics S.L.

Remote sensing, imaging, and signal engineering

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

Brase, J.M.

1993-03-01

This report discusses the Remote Sensing, Imaging, and Signal Engineering (RISE) trust area which has been very active in working to define new directions. Signal and image processing have always been important support for existing programs at Lawrence Livermore National Laboratory (LLNL), but now these technologies are becoming central to the formation of new programs. Exciting new applications such as high-resolution telescopes, radar remote sensing, and advanced medical imaging are allowing us to participate in the development of new programs.

Nonlinear Photonic Systems for V- and W-Band Antenna Remoting Applications

DTIC Science & Technology

2016-10-22

for commercial, academic, and military purposes delivering microwaves through fibers to remote areas for wireless sensing , imaging, and detection...academic, and military purposes, which use optical carriers to deliver microwave signals to remote areas for wireless sensing , imaging, and...and military purposes, which use optical carriers to deliver microwave signals to remote areas for wireless sensing , imaging, and detection

First results of ground-based LWIR hyperspectral imaging remote gas detection

NASA Astrophysics Data System (ADS)

Zheng, Wei-jian; Lei, Zheng-gang; Yu, Chun-chao; Wang, Hai-yang; Fu, Yan-peng; Liao, Ning-fang; Su, Jun-hong

2014-11-01

The new progress of ground-based long-wave infrared remote sensing is presented. The LWIR hyperspectral imaging by using the windowing spatial and temporal modulation Fourier spectroscopy, and the results of outdoor ether gas detection, verify the features of LWIR hyperspectral imaging remote sensing and technical approach. It provides a new technical means for ground-based gas remote sensing.

Fibre optic technique for simultaneous measurement of strain and temperature variations in composite materials

NASA Astrophysics Data System (ADS)

Michie, W. C.; Culshaw, Brian; Roberts, Scott S. J.; Davidson, Roger

1991-12-01

A technique based upon the differential sensitivities of dual mode and polarimetric sensing schemes is shown to be capable of resolving simultaneously temperature and strain variations to within 20 micro-epsilon and 1 K over a strain and temperature excursion of 2 micro-epsilon and 45 K. The technique is evaluated experimentally over an 80 cm sensing length of unembedded optical fiber and in an 8 ply unidirectional carbon/epoxide laminate subject to temperature and strain cycling. A comparative analysis of the performance of the embedded and the unembedded fiber sensors is presented.

Micro-optics for simultaneous multi-spectral imaging applied to chemical/biological and IED detection

NASA Astrophysics Data System (ADS)

Hinnrichs, Michele

2012-06-01

Using diffractive micro-lenses configured in an array and placed in close proximity to the focal plane array will enable a small compact simultaneous multispectral imaging camera. This approach can be applied to spectral regions from the ultraviolet (UV) to the long-wave infrared (LWIR). The number of simultaneously imaged spectral bands is determined by the number of individually configured diffractive optical micro-lenses (lenslet) in the array. Each lenslet images at a different wavelength determined by the blaze and set at the time of manufacturing based on application. In addition, modulation of the focal length of the lenslet array with piezoelectric or electro-static actuation will enable spectral band fill-in allowing hyperspectral imaging. Using the lenslet array with dual-band detectors will increase the number of simultaneous spectral images by a factor of two when utilizing multiple diffraction orders. Configurations and concept designs will be presented for detection application for biological/chemical agents, buried IED's and reconnaissance. The simultaneous detection of multiple spectral images in a single frame of data enhances the image processing capability by eliminating temporal differences between colors and enabling a handheld instrument that is insensitive to motion.

Technique development of 3D dynamic CS-EPSI for hyperpolarized 13 C pyruvate MR molecular imaging of human prostate cancer.

PubMed

Chen, Hsin-Yu; Larson, Peder E Z; Gordon, Jeremy W; Bok, Robert A; Ferrone, Marcus; van Criekinge, Mark; Carvajal, Lucas; Cao, Peng; Pauly, John M; Kerr, Adam B; Park, Ilwoo; Slater, James B; Nelson, Sarah J; Munster, Pamela N; Aggarwal, Rahul; Kurhanewicz, John; Vigneron, Daniel B

2018-03-25

The purpose of this study was to develop a new 3D dynamic carbon-13 compressed sensing echoplanar spectroscopic imaging (EPSI) MR sequence and test it in phantoms, animal models, and then in prostate cancer patients to image the metabolic conversion of hyperpolarized [1- 13 C]pyruvate to [1- 13 C]lactate with whole gland coverage at high spatial and temporal resolution. A 3D dynamic compressed sensing (CS)-EPSI sequence with spectral-spatial excitation was designed to meet the required spatial coverage, time and spatial resolution, and RF limitations of the 3T MR scanner for its clinical translation for prostate cancer patient imaging. After phantom testing, animal studies were performed in rats and transgenic mice with prostate cancers. For patient studies, a GE SPINlab polarizer (GE Healthcare, Waukesha, WI) was used to produce hyperpolarized sterile GMP [1- 13 C]pyruvate. 3D dynamic 13 C CS-EPSI data were acquired starting 5 s after injection throughout the gland with a spatial resolution of 0.5 cm 3 , 18 time frames, 2-s temporal resolution, and 36 s total acquisition time. Through preclinical testing, the 3D CS-EPSI sequence developed in this project was shown to provide the desired spectral, temporal, and spatial 5D HP 13 C MR data. In human studies, the 3D dynamic HP CS-EPSI approach provided first-ever simultaneously volumetric and dynamic images of the LDH-catalyzed conversion of [1- 13 C]pyruvate to [1- 13 C]lactate in a biopsy-proven prostate cancer patient with full gland coverage. The results demonstrate the feasibility to characterize prostate cancer metabolism in animals, and now patients using this new 3D dynamic HP MR technique to measure k PL , the kinetic rate constant of [1- 13 C]pyruvate to [1- 13 C]lactate conversion. © 2018 International Society for Magnetic Resonance in Medicine.

Cloud masking and removal in remote sensing image time series

NASA Astrophysics Data System (ADS)

Gómez-Chova, Luis; Amorós-López, Julia; Mateo-García, Gonzalo; Muñoz-Marí, Jordi; Camps-Valls, Gustau

2017-01-01

Automatic cloud masking of Earth observation images is one of the first required steps in optical remote sensing data processing since the operational use and product generation from satellite image time series might be hampered by undetected clouds. The high temporal revisit of current and forthcoming missions and the scarcity of labeled data force us to cast cloud screening as an unsupervised change detection problem in the temporal domain. We introduce a cloud screening method based on detecting abrupt changes along the time dimension. The main assumption is that image time series follow smooth variations over land (background) and abrupt changes will be mainly due to the presence of clouds. The method estimates the background surface changes using the information in the time series. In particular, we propose linear and nonlinear least squares regression algorithms that minimize both the prediction and the estimation error simultaneously. Then, significant differences in the image of interest with respect to the estimated background are identified as clouds. The use of kernel methods allows the generalization of the algorithm to account for higher-order (nonlinear) feature relations. After the proposed cloud masking and cloud removal, cloud-free time series at high spatial resolution can be used to obtain a better monitoring of land cover dynamics and to generate more elaborated products. The method is tested in a dataset with 5-day revisit time series from SPOT-4 at high resolution and with Landsat-8 time series. Experimental results show that the proposed method yields more accurate cloud masks when confronted with state-of-the-art approaches typically used in operational settings. In addition, the algorithm has been implemented in the Google Earth Engine platform, which allows us to access the full Landsat-8 catalog and work in a parallel distributed platform to extend its applicability to a global planetary scale.

A change detection method for remote sensing image based on LBP and SURF feature

NASA Astrophysics Data System (ADS)

Hu, Lei; Yang, Hao; Li, Jin; Zhang, Yun

2018-04-01

Finding the change in multi-temporal remote sensing image is important in many the image application. Because of the infection of climate and illumination, the texture of the ground object is more stable relative to the gray in high-resolution remote sensing image. And the texture features of Local Binary Patterns (LBP) and Speeded Up Robust Features (SURF) are outstanding in extracting speed and illumination invariance. A method of change detection for matched remote sensing image pair is present, which compares the similarity by LBP and SURF to detect the change and unchanged of the block after blocking the image. And region growing is adopted to process the block edge zone. The experiment results show that the method can endure some illumination change and slight texture change of the ground object.

Graphene-based aptamer logic gates and their application to multiplex detection.

PubMed

Wang, Li; Zhu, Jinbo; Han, Lei; Jin, Lihua; Zhu, Chengzhou; Wang, Erkang; Dong, Shaojun

2012-08-28

In this work, a GO/aptamer system was constructed to create multiplex logic operations and enable sensing of multiplex targets. 6-Carboxyfluorescein (FAM)-labeled adenosine triphosphate binding aptamer (ABA) and FAM-labeled thrombin binding aptamer (TBA) were first adsorbed onto graphene oxide (GO) to form a GO/aptamer complex, leading to the quenching of the fluorescence of FAM. We demonstrated that the unique GO/aptamer interaction and the specific aptamer-target recognition in the target/GO/aptamer system were programmable and could be utilized to regulate the fluorescence of FAM via OR and INHIBIT logic gates. The fluorescence changed according to different input combinations, and the integration of OR and INHIBIT logic gates provided an interesting approach for logic sensing applications where multiple target molecules were present. High-throughput fluorescence imagings that enabled the simultaneous processing of many samples by using the combinatorial logic gates were realized. The developed logic gates may find applications in further development of DNA circuits and advanced sensors for the identification of multiple targets in complex chemical environments.

Toward Simultaneous Real-Time Fluoroscopic and Nuclear Imaging in the Intervention Room.

PubMed

Beijst, Casper; Elschot, Mattijs; Viergever, Max A; de Jong, Hugo W A M

2016-01-01

To investigate the technical feasibility of hybrid simultaneous fluoroscopic and nuclear imaging. An x-ray tube, an x-ray detector, and a gamma camera were positioned in one line, enabling imaging of the same field of view. Since a straightforward combination of these elements would block the lines of view, a gamma camera setup was developed to be able to view around the x-ray tube. A prototype was built by using a mobile C-arm and a gamma camera with a four-pinhole collimator. By using the prototype, test images were acquired and sensitivity, resolution, and coregistration error were analyzed. Nuclear images (two frames per second) were acquired simultaneously with fluoroscopic images. Depending on the distance from point source to detector, the system resolution was 1.5-1.9-cm full width at half maximum, the sensitivity was (0.6-1.5) × 10(-5) counts per decay, and the coregistration error was -0.13 to 0.15 cm. With good spatial and temporal alignment of both modalities throughout the field of view, fluoroscopic images can be shown in grayscale and corresponding nuclear images in color overlay. Measurements obtained with the hybrid imaging prototype device that combines simultaneous fluoroscopic and nuclear imaging of the same field of view have demonstrated the feasibility of real-time simultaneous hybrid imaging in the intervention room. © RSNA, 2015

High Resolution Quantification of Cellular Forces for Rigidity Sensing

NASA Astrophysics Data System (ADS)

Liu, Shuaimin

This thesis describes a comprehensive study of understanding the mechanism of rigidity sensing by quantitative analysis using submicron pillar array substrates. From mechanobiology perspective, we explore and study molecular pathways involved in rigidity and force sensing at cell-matrix adhesions with regard to cancer, regeneration, and development by quantification methods. In Chapter 2 and 3, we developed fabrication and imaging techniques to enhance the performance of a submicron pillar device in terms of spatial and temporal measurement ability, and we discovered a correlation of rigidity sensing forces and corresponding proteins involved in the early rigidity sensing events. In Chapter 2, we introduced optical effect arising from submicron structure imaging, and we described a technique to identify the correct focal plane of pillar tip by fabricating a substrate with designed-offset pillars. From calibration result, we identified the correct focal plane that was previously overlooked, and verified our findings by other imaging techniques. In Chapter 3, we described several techniques to selectively functionalize elastomeric pillars top and compared these techniques in terms of purposes and fabrication complexity. Techniques introduced in this chapter included direct labeling, such as stamping of fluorescent substances (organic dye, nano-diamond, q-dot) to pillars top, as well as indirect labeling that selectively modify the surface of molds with either metal or fluorescent substances. In Chapter 4, we examined the characteristics of local contractility forces and identified the components formed a sarcomere like contractile unit (CU) that cells use to sense rigidity. CUs were found to be assembled at cell edge, contain myosin II, alpha-actinin, tropomodulin and tropomyosin (Tm), and resemble sarcomeres in size (˜2 mum) and function. Then we performed quantitative analysis of CUs to evaluate rigidity sensing activity over ˜8 hours time course and found that density of CUs decrease with time after spreading on stiff substrate. However addition of EGF dramatically increased local contraction activity such that about 30% of the total contractility was in the contraction units. This stimulatory effect was only observed on stiff substrate not on soft. Moreover, we find that in the early interactions of cells with rigid substrates that EGFR activity is needed for normal spreading and the assembly of local contraction units in media lacking serum and any soluble EGF. In Chapter 5, we performed high temporal- and spatial-resolution tracking of contractile forces exerted by cells on sub-micron elastomeric pillars. We found that actomyosin-based sarcomere-like CUs simultaneously moved opposing pillars in net steps of ˜2.5 nm, independent of rigidity. What correlated with rigidity was the number of steps taken to reach a force level that activated recruitment of alpha-actinin to the CUs. When we removed actomyosin restriction by depleting tropomyosin 2.1, we observed larger steps and higher forces that resulted in aberrant rigidity sensing and growth of non-transformed cells on soft matrices. Thus, we conclude that tropomyosin 2.1 acts as a suppressor of growth on soft matrices by supporting proper rigidity sensing.

Measurement of Respiration Rate and Depth Through Difference in Temperature Between Skin Surface and Nostril by Using Thermal Image.

PubMed

Jeong, Hieyong; Matsuura, Yutaka; Ohno, Yuko

2017-01-01

The purpose of the present study was to propose a method to measure a respiration rate (RR) and depth at once through difference in temperature between the skin surface and nostril by using a thermal image. Although there have been a lot of devices for contact RR monitoring, it was considered that the subjects could be inconvenienced by having the sensing device in contact with their body. Our algorithm enabled us to make a breathing periodic function (BPF) under the non-contact and non-invasive condition through temperature differences near the nostril during the breath. As a result, it was proved that our proposed method was able to classify differences in breathing pattern between normal, deep, and shallow breath (P < 0.001). These results lead us to conclude that the RR and depth is simultaneously measured by the proposed algorithm of BPF without any contact or invasive procedure.

Potential for application of an acoustic camera in particle tracking velocimetry.

PubMed

Wu, Fu-Chun; Shao, Yun-Chuan; Wang, Chi-Kuei; Liou, Jim

2008-11-01

We explored the potential and limitations for applying an acoustic camera as the imaging instrument of particle tracking velocimetry. The strength of the acoustic camera is its usability in low-visibility environments where conventional optical cameras are ineffective, while its applicability is limited by lower temporal and spatial resolutions. We conducted a series of experiments in which acoustic and optical cameras were used to simultaneously image the rotational motion of tracer particles, allowing for a comparison of the acoustic- and optical-based velocities. The results reveal that the greater fluctuations associated with the acoustic-based velocities are primarily attributed to the lower temporal resolution. The positive and negative biases induced by the lower spatial resolution are balanced, with the positive ones greater in magnitude but the negative ones greater in quantity. These biases reduce with the increase in the mean particle velocity and approach minimum as the mean velocity exceeds the threshold value that can be sensed by the acoustic camera.

Imaging IR spectrometer, phase 2

NASA Technical Reports Server (NTRS)

Gradie, Jonathan; Lewis, Ralph; Lundeen, Thomas; Wang, Shu-I

1990-01-01

The development is examined of a prototype multi-channel infrared imaging spectrometer. The design, construction and preliminary performance is described. This instrument is intended for use with JPL Table Mountain telescope as well as the 88 inch UH telescope on Mauna Kea. The instrument is capable of sampling simultaneously the spectral region of 0.9 to 2.6 um at an average spectral resolution of 1 percent using a cooled (77 K) optical bench, a concave holographic grating and a special order sorting filter to allow the acquisition of the full spectral range on a 128 x 128 HgCdTe infrared detector array. The field of view of the spectrometer is 0.5 arcsec/pixel in mapping mode and designed to be 5 arcsec/pixel in spot mode. The innovative optical design has resulted in a small, transportable spectrometer, capable of remote operation. Commercial applications of this spectrometer design include remote sensing from both space and aircraft platforms as well as groundbased astronomical observations.

Single-spin stochastic optical reconstruction microscopy

PubMed Central

Pfender, Matthias; Aslam, Nabeel; Waldherr, Gerald; Neumann, Philipp; Wrachtrup, Jörg

2014-01-01

We experimentally demonstrate precision addressing of single-quantum emitters by combined optical microscopy and spin resonance techniques. To this end, we use nitrogen vacancy (NV) color centers in diamond confined within a few ten nanometers as individually resolvable quantum systems. By developing a stochastic optical reconstruction microscopy (STORM) technique for NV centers, we are able to simultaneously perform sub–diffraction-limit imaging and optically detected spin resonance (ODMR) measurements on NV spins. This allows the assignment of spin resonance spectra to individual NV center locations with nanometer-scale resolution and thus further improves spatial discrimination. For example, we resolved formerly indistinguishable emitters by their spectra. Furthermore, ODMR spectra contain metrology information allowing for sub–diffraction-limit sensing of, for instance, magnetic or electric fields with inherently parallel data acquisition. As an example, we have detected nuclear spins with nanometer-scale precision. Finally, we give prospects of how this technique can evolve into a fully parallel quantum sensor for nanometer resolution imaging of delocalized quantum correlations. PMID:25267655

Mechanisms of Saturn's Near-Noon Transient Aurora: In Situ Evidence From Cassini Measurements

NASA Astrophysics Data System (ADS)

Yao, Z. H.; Radioti, A.; Rae, I. J.; Liu, J.; Grodent, D.; Ray, L. C.; Badman, S. V.; Coates, A. J.; Gérard, J.-C.; Waite, J. H.; Yates, J. N.; Shi, Q. Q.; Wei, Y.; Bonfond, B.; Dougherty, M. K.; Roussos, E.; Sergis, N.; Palmaerts, B.

2017-11-01

Although auroral emissions at giant planets have been observed for decades, the physical mechanisms of aurorae at giant planets remain unclear. One key reason is the lack of simultaneous measurements in the magnetosphere while remote sensing of the aurora. We report a dynamic auroral event identified with the Cassini Ultraviolet Imaging Spectrograph (UVIS) at Saturn on 13 July 2008 with coordinated measurements of the magnetic field and plasma in the magnetosphere. The auroral intensification was transient, only lasting for ˜30 min. The magnetic field and plasma are perturbed during the auroral intensification period. We suggest that this intensification was caused by wave mode conversion generated field-aligned currents, and we propose two potential mechanisms for the generation of this plasma wave and the transient auroral intensification. A survey of the Cassini UVIS database reveals that this type of transient auroral intensification is very common (10/11 time sequences, and ˜10% of the total images).

Standoff aircraft IR characterization with ABB dual-band hyper spectral imager

NASA Astrophysics Data System (ADS)

Prel, Florent; Moreau, Louis; Lantagne, Stéphane; Bullis, Ritchie D.; Roy, Claude; Vallières, Christian; Levesque, Luc

2012-09-01

Remote sensing infrared characterization of rapidly evolving events generally involves the combination of a spectro-radiometer and infrared camera(s) as separated instruments. Time synchronization, spatial coregistration, consistent radiometric calibration and managing several systems are important challenges to overcome; they complicate the target infrared characterization data processing and increase the sources of errors affecting the final radiometric accuracy. MR-i is a dual-band Hyperspectal imaging spectro-radiometer, that combines two 256 x 256 pixels infrared cameras and an infrared spectro-radiometer into one single instrument. This field instrument generates spectral datacubes in the MWIR and LWIR. It is designed to acquire the spectral signatures of rapidly evolving events. The design is modular. The spectrometer has two output ports configured with two simultaneously operated cameras to either widen the spectral coverage or to increase the dynamic range of the measured amplitudes. Various telescope options are available for the input port. Recent platform developments and field trial measurements performances will be presented for a system configuration dedicated to the characterization of airborne targets.

Common-Path Wavefront Sensing for Advanced Coronagraphs

NASA Technical Reports Server (NTRS)

Wallace, J. Kent; Serabyn, Eugene; Mawet, Dimitri

2012-01-01

Imaging of faint companions around nearby stars is not limited by either intrinsic resolution of a coronagraph/telescope system, nor is it strictly photon limited. Typically, it is both the magnitude and temporal variation of small phase and amplitude errors imparted to the electric field by elements in the optical system which will limit ultimate performance. Adaptive optics systems, particularly those with multiple deformable mirrors, can remove these errors, but they need to be sensed in the final image plane. If the sensing system is before the final image plane, which is typical for most systems, then the non-common path optics between the wavefront sensor and science image plane will lead to un-sensed errors. However, a new generation of high-performance coronagraphs naturally lend themselves to wavefront sensing in the final image plane. These coronagraphs and the wavefront sensing will be discussed, as well as plans for demonstrating this with a high-contrast system on the ground. Such a system will be a key system-level proof for a future space-based coronagraph mission, which will also be discussed.

Real-time Full-spectral Imaging and Affinity Measurements from 50 Microfluidic Channels using Nanohole Surface Plasmon Resonance†

PubMed Central

Lee, Si Hoon; Lindquist, Nathan C.; Wittenberg, Nathan J.; Jordan, Luke R.; Oh, Sang-Hyun

2012-01-01

With recent advances in high-throughput proteomics and systems biology, there is a growing demand for new instruments that can precisely quantify a wide range of receptor-ligand binding kinetics in a high-throughput fashion. Here we demonstrate a surface plasmon resonance (SPR) imaging spectroscopy instrument capable of extracting binding kinetics and affinities from 50 parallel microfluidic channels simultaneously. The instrument utilizes large-area (~cm2) metallic nanohole arrays as SPR sensing substrates and combines a broadband light source, a high-resolution imaging spectrometer and a low-noise CCD camera to extract spectral information from every channel in real time with a refractive index resolution of 7.7 × 10−6. To demonstrate the utility of our instrument for quantifying a wide range of biomolecular interactions, each parallel microfluidic channel is coated with a biomimetic supported lipid membrane containing ganglioside (GM1) receptors. The binding kinetics of cholera toxin b (CTX-b) to GM1 are then measured in a single experiment from 50 channels. By combining the highly parallel microfluidic device with large-area periodic nanohole array chips, our SPR imaging spectrometer system enables high-throughput, label-free, real-time SPR biosensing, and its full-spectral imaging capability combined with nanohole arrays could enable integration of SPR imaging with concurrent surface-enhanced Raman spectroscopy. PMID:22895607

Noninvasive measurement of pharmacokinetics by near-infrared fluorescence imaging in the eye of mice

NASA Astrophysics Data System (ADS)

Dobosz, Michael; Strobel, Steffen; Stubenrauch, Kay-Gunnar; Osl, Franz; Scheuer, Werner

2014-01-01

Purpose: For generating preclinical pharmacokinetics (PKs) of compounds, blood is drawn at different time points and levels are quantified by different analytical methods. In order to receive statistically meaningful data, 3 to 5 animals are used for each time point to get serum peak-level and half-life of the compound. Both characteristics are determined by data interpolation, which may influence the accuracy of these values. We provide a method that allows continuous monitoring of blood levels noninvasively by measuring the fluorescence intensity of labeled compounds in the eye and other body regions of anesthetized mice. Procedures: The method evaluation was performed with four different fluorescent compounds: (i) indocyanine green, a nontargeting dye; (ii) OsteoSense750, a bone targeting agent; (iii) tumor targeting Trastuzumab-Alexa750; and (iv) its F(-alxea750 fragment. The latter was used for a direct comparison between fluorescence imaging and classical blood analysis using enzyme-linked immunosorbent assay (ELISA). Results: We found an excellent correlation between blood levels measured by noninvasive eye imaging with the results generated by classical methods. A strong correlation between eye imaging and ELISA was demonstrated for the F( fragment. Whole body imaging revealed a compound accumulation in the expected regions (e.g., liver, bone). Conclusions: The combination of eye and whole body fluorescence imaging enables the simultaneous measurement of blood PKs and biodistribution of fluorescent-labeled compounds.

Comparison of simultaneous and sequential SPECT imaging for discrimination tasks in assessment of cardiac defects.

PubMed

Trott, C M; Ouyang, J; El Fakhri, G

2010-11-21

Simultaneous rest perfusion/fatty-acid metabolism studies have the potential to replace sequential rest/stress perfusion studies for the assessment of cardiac function. Simultaneous acquisition has the benefits of increased signal and lack of need for patient stress, but is complicated by cross-talk between the two radionuclide signals. We consider a simultaneous rest (99m)Tc-sestamibi/(123)I-BMIPP imaging protocol in place of the commonly used sequential rest/stress (99m)Tc-sestamibi protocol. The theoretical precision with which the severity of a cardiac defect and the transmural extent of infarct can be measured is computed for simultaneous and sequential SPECT imaging, and their performance is compared for discriminating (1) degrees of defect severity and (2) sub-endocardial from transmural defects. We consider cardiac infarcts for which reduced perfusion and metabolism are observed. From an information perspective, simultaneous imaging is found to yield comparable or improved performance compared with sequential imaging for discriminating both severity of defect and transmural extent of infarct, for three defects of differing location and size.

Multisource image fusion method using support value transform.

PubMed

Zheng, Sheng; Shi, Wen-Zhong; Liu, Jian; Zhu, Guang-Xi; Tian, Jin-Wen

2007-07-01

With the development of numerous imaging sensors, many images can be simultaneously pictured by various sensors. However, there are many scenarios where no one sensor can give the complete picture. Image fusion is an important approach to solve this problem and produces a single image which preserves all relevant information from a set of different sensors. In this paper, we proposed a new image fusion method using the support value transform, which uses the support value to represent the salient features of image. This is based on the fact that, in support vector machines (SVMs), the data with larger support values have a physical meaning in the sense that they reveal relative more importance of the data points for contributing to the SVM model. The mapped least squares SVM (mapped LS-SVM) is used to efficiently compute the support values of image. The support value analysis is developed by using a series of multiscale support value filters, which are obtained by filling zeros in the basic support value filter deduced from the mapped LS-SVM to match the resolution of the desired level. Compared with the widely used image fusion methods, such as the Laplacian pyramid, discrete wavelet transform methods, the proposed method is an undecimated transform-based approach. The fusion experiments are undertaken on multisource images. The results demonstrate that the proposed approach is effective and is superior to the conventional image fusion methods in terms of the pertained quantitative fusion evaluation indexes, such as quality of visual information (Q(AB/F)), the mutual information, etc.

LORAKS makes better SENSE: Phase-constrained partial fourier SENSE reconstruction without phase calibration.

PubMed

Kim, Tae Hyung; Setsompop, Kawin; Haldar, Justin P

2017-03-01

Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely used calibrationless uniformly undersampled trajectories. Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. The SENSE-LORAKS framework provides promising new opportunities for highly accelerated MRI. Magn Reson Med 77:1021-1035, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

A case study of comparing radiometrically calibrated reflectance of an image mosaic from unmanned aerial system with that of a single image from manned aircraft over a same area

USDA-ARS?s Scientific Manuscript database

Although conventional high-altitude airborne remote sensing and low-altitude unmanned aerial system (UAS) based remote sensing share many commonalities, one of the major differences between the two remote sensing platforms is that the latter has much smaller image footprint. To cover the same area o...

The mass remote sensing image data management based on Oracle InterMedia

NASA Astrophysics Data System (ADS)

Zhao, Xi'an; Shi, Shaowei

2013-07-01

With the development of remote sensing technology, getting the image data more and more, how to apply and manage the mass image data safely and efficiently has become an urgent problem to be solved. According to the methods and characteristics of the mass remote sensing image data management and application, this paper puts forward to a new method that takes Oracle Call Interface and Oracle InterMedia to store the image data, and then takes this component to realize the system function modules. Finally, it successfully takes the VC and Oracle InterMedia component to realize the image data storage and management.

Simultaneous Contact Sensing and Characterizing of Mechanical and Dynamic Heat Transfer Properties of Porous Polymeric Materials

PubMed Central

Yao, Bao-Guo; Peng, Yun-Liang; Zhang, De-Pin

2017-01-01

Porous polymeric materials, such as textile fabrics, are elastic and widely used in our daily life for garment and household products. The mechanical and dynamic heat transfer properties of porous polymeric materials, which describe the sensations during the contact process between porous polymeric materials and parts of the human body, such as the hand, primarily influence comfort sensations and aesthetic qualities of clothing. A multi-sensory measurement system and a new method were proposed to simultaneously sense the contact and characterize the mechanical and dynamic heat transfer properties of porous polymeric materials, such as textile fabrics in one instrument, with consideration of the interactions between different aspects of contact feels. The multi-sensory measurement system was developed for simulating the dynamic contact and psychological judgment processes during human hand contact with porous polymeric materials, and measuring the surface smoothness, compression resilience, bending and twisting, and dynamic heat transfer signals simultaneously. The contact sensing principle and the evaluation methods were presented. Twelve typical sample materials with different structural parameters were measured. The results of the experiments and the interpretation of the test results were described. An analysis of the variance and a capacity study were investigated to determine the significance of differences among the test materials and to assess the gage repeatability and reproducibility. A correlation analysis was conducted by comparing the test results of this measurement system with the results of Kawabata Evaluation System (KES) in separate instruments. This multi-sensory measurement system provides a new method for simultaneous contact sensing and characterizing of mechanical and dynamic heat transfer properties of porous polymeric materials. PMID:29084152

Simultaneous Contact Sensing and Characterizing of Mechanical and Dynamic Heat Transfer Properties of Porous Polymeric Materials.

PubMed

Yao, Bao-Guo; Peng, Yun-Liang; Zhang, De-Pin

2017-10-30

Porous polymeric materials, such as textile fabrics, are elastic and widely used in our daily life for garment and household products. The mechanical and dynamic heat transfer properties of porous polymeric materials, which describe the sensations during the contact process between porous polymeric materials and parts of the human body, such as the hand, primarily influence comfort sensations and aesthetic qualities of clothing. A multi-sensory measurement system and a new method were proposed to simultaneously sense the contact and characterize the mechanical and dynamic heat transfer properties of porous polymeric materials, such as textile fabrics in one instrument, with consideration of the interactions between different aspects of contact feels. The multi-sensory measurement system was developed for simulating the dynamic contact and psychological judgment processes during human hand contact with porous polymeric materials, and measuring the surface smoothness, compression resilience, bending and twisting, and dynamic heat transfer signals simultaneously. The contact sensing principle and the evaluation methods were presented. Twelve typical sample materials with different structural parameters were measured. The results of the experiments and the interpretation of the test results were described. An analysis of the variance and a capacity study were investigated to determine the significance of differences among the test materials and to assess the gage repeatability and reproducibility. A correlation analysis was conducted by comparing the test results of this measurement system with the results of Kawabata Evaluation System (KES) in separate instruments. This multi-sensory measurement system provides a new method for simultaneous contact sensing and characterizing of mechanical and dynamic heat transfer properties of porous polymeric materials.

Application of Compressive Sensing to Gravitational Microlensing Experiments

NASA Technical Reports Server (NTRS)

Korde-Patel, Asmita; Barry, Richard K.; Mohsenin, Tinoosh

2016-01-01

Compressive Sensing is an emerging technology for data compression and simultaneous data acquisition. This is an enabling technique for significant reduction in data bandwidth, and transmission power and hence, can greatly benefit spaceflight instruments. We apply this process to detect exoplanets via gravitational microlensing. We experiment with various impact parameters that describe microlensing curves to determine the effectiveness and uncertainty caused by Compressive Sensing. Finally, we describe implications for spaceflight missions.

Simultaneous two-photon imaging and two-photon optogenetics of cortical circuits in three dimensions

PubMed Central

Carrillo-Reid, Luis; Bando, Yuki; Peterka, Darcy S

2018-01-01

The simultaneous imaging and manipulating of neural activity could enable the functional dissection of neural circuits. Here we have combined two-photon optogenetics with simultaneous volumetric two-photon calcium imaging to measure and manipulate neural activity in mouse neocortex in vivo in three-dimensions (3D) with cellular resolution. Using a hybrid holographic approach, we simultaneously photostimulate more than 80 neurons over 150 μm in depth in layer 2/3 of the mouse visual cortex, while simultaneously imaging the activity of the surrounding neurons. We validate the usefulness of the method by photoactivating in 3D selected groups of interneurons, suppressing the response of nearby pyramidal neurons to visual stimuli in awake animals. Our all-optical approach could be used as a general platform to read and write neuronal activity. PMID:29412138

SenseCam improves memory for recent events and quality of life in a patient with memory retrieval difficulties.

PubMed

Browne, Georgina; Berry, Emma; Kapur, Narinder; Hodges, Steve; Smyth, Gavin; Watson, Peter; Wood, Ken

2011-10-01

A wearable camera that takes pictures automatically, SenseCam, was used to generate images for rehearsal, promoting consolidation and retrieval of memories for significant events in a patient with memory retrieval deficits. SenseCam images of recent events were systematically reviewed over a 2-week period. Memory for these events was assessed throughout and longer-term recall was tested up to 6 months later. A written diary control condition followed the same procedure. The SenseCam review procedure resulted in significantly more details of an event being recalled, with twice as many details recalled at 6 months follow up compared to the written diary method. Self-report measures suggested autobiographical recollection was triggered by the SenseCam condition but not by reviewing the written diary. Emotional and social wellbeing questionnaires indicated improved confidence and decreased anxiety as a result of memory rehearsal using SenseCam images. We propose that SenseCam images provide a powerful boost to autobiographical recall, with secondary benefits for quality of life.

Aerial Vehicle Surveys of other Planetary Atmospheres and Surfaces: Imaging, Remote-sensing, and Autonomy Technology Requirements

NASA Technical Reports Server (NTRS)

Young, Larry A.; Pisanich, Gregory; Ippolito, Corey; Alena, Rick

2005-01-01

The objective of this paper is to review the anticipated imaging and remote-sensing technology requirements for aerial vehicle survey missions to other planetary bodies in our Solar system that can support in-atmosphere flight. In the not too distant future such planetary aerial vehicle (a.k.a. aerial explorers) exploration missions will become feasible. Imaging and remote-sensing observations will be a key objective for these missions. Accordingly, it is imperative that optimal solutions in terms of imaging acquisition and real-time autonomous analysis of image data sets be developed for such vehicles.

HPT: A High Spatial Resolution Multispectral Sensor for Microsatellite Remote Sensing

PubMed Central

Takahashi, Yukihiro; Sakamoto, Yuji; Kuwahara, Toshinori

2018-01-01

Although nano/microsatellites have great potential as remote sensing platforms, the spatial and spectral resolutions of an optical payload instrument are limited. In this study, a high spatial resolution multispectral sensor, the High-Precision Telescope (HPT), was developed for the RISING-2 microsatellite. The HPT has four image sensors: three in the visible region of the spectrum used for the composition of true color images, and a fourth in the near-infrared region, which employs liquid crystal tunable filter (LCTF) technology for wavelength scanning. Band-to-band image registration methods have also been developed for the HPT and implemented in the image processing procedure. The processed images were compared with other satellite images, and proven to be useful in various remote sensing applications. Thus, LCTF technology can be considered an innovative tool that is suitable for future multi/hyperspectral remote sensing by nano/microsatellites. PMID:29463022

a Coarse-To Model for Airplane Detection from Large Remote Sensing Images Using Saliency Modle and Deep Learning

NASA Astrophysics Data System (ADS)

Song, Z. N.; Sui, H. G.

2018-04-01

High resolution remote sensing images are bearing the important strategic information, especially finding some time-sensitive-targets quickly, like airplanes, ships, and cars. Most of time the problem firstly we face is how to rapidly judge whether a particular target is included in a large random remote sensing image, instead of detecting them on a given image. The problem of time-sensitive-targets target finding in a huge image is a great challenge: 1) Complex background leads to high loss and false alarms in tiny object detection in a large-scale images. 2) Unlike traditional image retrieval, what we need to do is not just compare the similarity of image blocks, but quickly find specific targets in a huge image. In this paper, taking the target of airplane as an example, presents an effective method for searching aircraft targets in large scale optical remote sensing images. Firstly, we used an improved visual attention model utilizes salience detection and line segment detector to quickly locate suspected regions in a large and complicated remote sensing image. Then for each region, without region proposal method, a single neural network predicts bounding boxes and class probabilities directly from full images in one evaluation is adopted to search small airplane objects. Unlike sliding window and region proposal-based techniques, we can do entire image (region) during training and test time so it implicitly encodes contextual information about classes as well as their appearance. Experimental results show the proposed method is quickly identify airplanes in large-scale images.

Research on fast Fourier transforms algorithm of huge remote sensing image technology with GPU and partitioning technology.

PubMed

Yang, Xue; Li, Xue-You; Li, Jia-Guo; Ma, Jun; Zhang, Li; Yang, Jan; Du, Quan-Ye

2014-02-01

Fast Fourier transforms (FFT) is a basic approach to remote sensing image processing. With the improvement of capacity of remote sensing image capture with the features of hyperspectrum, high spatial resolution and high temporal resolution, how to use FFT technology to efficiently process huge remote sensing image becomes the critical step and research hot spot of current image processing technology. FFT algorithm, one of the basic algorithms of image processing, can be used for stripe noise removal, image compression, image registration, etc. in processing remote sensing image. CUFFT function library is the FFT algorithm library based on CPU and FFTW. FFTW is a FFT algorithm developed based on CPU in PC platform, and is currently the fastest CPU based FFT algorithm function library. However there is a common problem that once the available memory or memory is less than the capacity of image, there will be out of memory or memory overflow when using the above two methods to realize image FFT arithmetic. To address this problem, a CPU and partitioning technology based Huge Remote Fast Fourier Transform (HRFFT) algorithm is proposed in this paper. By improving the FFT algorithm in CUFFT function library, the problem of out of memory and memory overflow is solved. Moreover, this method is proved rational by experiment combined with the CCD image of HJ-1A satellite. When applied to practical image processing, it improves effect of the image processing, speeds up the processing, which saves the time of computation and achieves sound result.

The ultrasound brain helmet: early human feasibility study of multiple simultaneous 3D scans of cerebral vasculature

NASA Astrophysics Data System (ADS)

Lindsey, Brooks D.; Ivancevich, Nikolas M.; Whitman, John; Light, Edward; Fronheiser, Matthew; Nicoletto, Heather A.; Laskowitz, Daniel T.; Smith, Stephen W.

2009-02-01

We describe early stage experiments to test the feasibility of an ultrasound brain helmet to produce multiple simultaneous real-time 3D scans of the cerebral vasculature from temporal and suboccipital acoustic windows of the skull. The transducer hardware and software of the Volumetrics Medical Imaging real-time 3D scanner were modified to support dual 2.5 MHz matrix arrays of 256 transmit elements and 128 receive elements which produce two simultaneous 64° pyramidal scans. The real-time display format consists of two coronal B-mode images merged into a 128° sector, two simultaneous parasagittal images merged into a 128° × 64° C-mode plane, and a simultaneous 64° axial image. Real-time 3D color Doppler images acquired in initial clinical studies after contrast injection demonstrate flow in several representative blood vessels. An offline Doppler rendering of data from two transducers simultaneously scanning via the temporal windows provides an early visualization of the flow in vessels on both sides of the brain. The long-term goal is to produce real-time 3D ultrasound images of the cerebral vasculature from a portable unit capable of internet transmission, thus enabling interactive 3D imaging, remote diagnosis and earlier therapeutic intervention. We are motivated by the urgency for rapid diagnosis of stroke due to the short time window of effective therapeutic intervention.

The integrated design and archive of space-borne signal processing and compression coding

NASA Astrophysics Data System (ADS)

He, Qiang-min; Su, Hao-hang; Wu, Wen-bo

2017-10-01

With the increasing demand of users for the extraction of remote sensing image information, it is very urgent to significantly enhance the whole system's imaging quality and imaging ability by using the integrated design to achieve its compact structure, light quality and higher attitude maneuver ability. At this present stage, the remote sensing camera's video signal processing unit and image compression and coding unit are distributed in different devices. The volume, weight and consumption of these two units is relatively large, which unable to meet the requirements of the high mobility remote sensing camera. This paper according to the high mobility remote sensing camera's technical requirements, designs a kind of space-borne integrated signal processing and compression circuit by researching a variety of technologies, such as the high speed and high density analog-digital mixed PCB design, the embedded DSP technology and the image compression technology based on the special-purpose chips. This circuit lays a solid foundation for the research of the high mobility remote sensing camera.

MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification

NASA Astrophysics Data System (ADS)

Lin, Daoyu; Fu, Kun; Wang, Yang; Xu, Guangluan; Sun, Xian

2017-11-01

With the development of deep learning, supervised learning has frequently been adopted to classify remotely sensed images using convolutional networks (CNNs). However, due to the limited amount of labeled data available, supervised learning is often difficult to carry out. Therefore, we proposed an unsupervised model called multiple-layer feature-matching generative adversarial networks (MARTA GANs) to learn a representation using only unlabeled data. MARTA GANs consists of both a generative model $G$ and a discriminative model $D$. We treat $D$ as a feature extractor. To fit the complex properties of remote sensing data, we use a fusion layer to merge the mid-level and global features. $G$ can produce numerous images that are similar to the training data; therefore, $D$ can learn better representations of remotely sensed images using the training data provided by $G$. The classification results on two widely used remote sensing image databases show that the proposed method significantly improves the classification performance compared with other state-of-the-art methods.

Methods and potentials for using satellite image classification in school lessons

NASA Astrophysics Data System (ADS)

Voss, Kerstin; Goetzke, Roland; Hodam, Henryk

2011-11-01

The FIS project - FIS stands for Fernerkundung in Schulen (Remote Sensing in Schools) - aims at a better integration of the topic "satellite remote sensing" in school lessons. According to this, the overarching objective is to teach pupils basic knowledge and fields of application of remote sensing. Despite the growing significance of digital geomedia, the topic "remote sensing" is not broadly supported in schools. Often, the topic is reduced to a short reflection on satellite images and used only for additional illustration of issues relevant for the curriculum. Without addressing the issue of image data, this can hardly contribute to the improvement of the pupils' methodical competences. Because remote sensing covers more than simple, visual interpretation of satellite images, it is necessary to integrate remote sensing methods like preprocessing, classification and change detection. Dealing with these topics often fails because of confusing background information and the lack of easy-to-use software. Based on these insights, the FIS project created different simple analysis tools for remote sensing in school lessons, which enable teachers as well as pupils to be introduced to the topic in a structured way. This functionality as well as the fields of application of these analysis tools will be presented in detail with the help of three different classification tools for satellite image classification.

A Distributed Compressive Sensing Scheme for Event Capture in Wireless Visual Sensor Networks

NASA Astrophysics Data System (ADS)

Hou, Meng; Xu, Sen; Wu, Weiling; Lin, Fei

2018-01-01

Image signals which acquired by wireless visual sensor network can be used for specific event capture. This event capture is realized by image processing at the sink node. A distributed compressive sensing scheme is used for the transmission of these image signals from the camera nodes to the sink node. A measurement and joint reconstruction algorithm for these image signals are proposed in this paper. Make advantage of spatial correlation between images within a sensing area, the cluster head node which as the image decoder can accurately co-reconstruct these image signals. The subjective visual quality and the reconstruction error rate are used for the evaluation of reconstructed image quality. Simulation results show that the joint reconstruction algorithm achieves higher image quality at the same image compressive rate than the independent reconstruction algorithm.

Improving streamflow prediction using remotely-sensed soil moisture and snow depth

USDA-ARS?s Scientific Manuscript database

The monitoring of both cold and warm season hydrologic processes in headwater watersheds is critical for accurate water resource monitoring in many alpine regions. This work presents a new method that explores the simultaneous use of remotely sensed surface soil moisture (SM) and snow depth (SD) ret...

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters

PubMed Central

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

PubMed

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

a New Graduation Algorithm for Color Balance of Remote Sensing Image

NASA Astrophysics Data System (ADS)

Zhou, G.; Liu, X.; Yue, T.; Wang, Q.; Sha, H.; Huang, S.; Pan, Q.

2018-05-01

In order to expand the field of view to obtain more data and information when doing research on remote sensing image, workers always need to mosaicking images together. However, the image after mosaic always has the large color differences and produces the gap line. This paper based on the graduation algorithm of tarigonometric function proposed a new algorithm of Two Quarter-rounds Curves (TQC). The paper uses the Gaussian filter to solve the program about the image color noise and the gap line. The paper used one of Greenland compiled data acquired in 1963 from Declassified Intelligence Photography Project (DISP) by ARGON KH-5 satellite, and used the photography of North Gulf, China, by Landsat satellite to experiment. The experimental results show that the proposed method has improved the accuracy of the results in two parts: on the one hand, for the large color differences remote sensing image will become more balanced. On the other hands, the remote sensing image will achieve more smooth transition.

Enhancing the Teaching of Digital Processing of Remote Sensing Image Course through Geospatial Web Processing Services

NASA Astrophysics Data System (ADS)

di, L.; Deng, M.

2010-12-01

Remote sensing (RS) is an essential method to collect data for Earth science research. Huge amount of remote sensing data, most of them in the image form, have been acquired. Almost all geography departments in the world offer courses in digital processing of remote sensing images. Such courses place emphasis on how to digitally process large amount of multi-source images for solving real world problems. However, due to the diversity and complexity of RS images and the shortcomings of current data and processing infrastructure, obstacles for effectively teaching such courses still remain. The major obstacles include 1) difficulties in finding, accessing, integrating and using massive RS images by students and educators, and 2) inadequate processing functions and computing facilities for students to freely explore the massive data. Recent development in geospatial Web processing service systems, which make massive data, computing powers, and processing capabilities to average Internet users anywhere in the world, promises the removal of the obstacles. The GeoBrain system developed by CSISS is an example of such systems. All functions available in GRASS Open Source GIS have been implemented as Web services in GeoBrain. Petabytes of remote sensing images in NASA data centers, the USGS Landsat data archive, and NOAA CLASS are accessible transparently and processable through GeoBrain. The GeoBrain system is operated on a high performance cluster server with large disk storage and fast Internet connection. All GeoBrain capabilities can be accessed by any Internet-connected Web browser. Dozens of universities have used GeoBrain as an ideal platform to support data-intensive remote sensing education. This presentation gives a specific example of using GeoBrain geoprocessing services to enhance the teaching of GGS 588, Digital Remote Sensing taught at the Department of Geography and Geoinformation Science, George Mason University. The course uses the textbook "Introductory Digital Image Processing, A Remote Sensing Perspective" authored by John Jensen. The textbook is widely adopted in the geography departments around the world for training students on digital processing of remote sensing images. In the traditional teaching setting for the course, the instructor prepares a set of sample remote sensing images to be used for the course. Commercial desktop remote sensing software, such as ERDAS, is used for students to do the lab exercises. The students have to do the excurses in the lab and can only use the simple images. For this specific course at GMU, we developed GeoBrain-based lab excurses for the course. With GeoBrain, students now can explore petabytes of remote sensing images in the NASA, NOAA, and USGS data archives instead of dealing only with sample images. Students have a much more powerful computing facility available for their lab excurses. They can explore the data and do the excurses any time at any place they want as long as they can access the Internet through the Web Browser. The feedbacks from students are all very positive about the learning experience on the digital image processing with the help of GeoBrain web processing services. The teaching/lab materials and GeoBrain services are freely available to anyone at http://www.laits.gmu.edu.

Simultaneous measurement of temperature and strain using four connecting wires

NASA Technical Reports Server (NTRS)

Parker, Allen R., Jr.

1993-01-01

This paper describes a new signal-conditioning technique for measuring strain and temperature which uses fewer connecting wires than conventional techniques. Simultaneous measurement of temperature and strain has been achieved by using thermocouple wire to connect strain gages to signal conditioning. This signal conditioning uses a new method for demultiplexing sampled analog signals and the Anderson current loop circuit. Theory is presented along with data to confirm that strain gage resistance change is sensed without appreciable error because of thermoelectric effects. Furthermore, temperature is sensed without appreciable error because of voltage drops caused by strain gage excitation current flowing through the gage resistance.

A Sensing System for Simultaneous Detection of Urine and its Components Using Plastic Optical Fibers

NASA Astrophysics Data System (ADS)

Ejaz, Tahseen; Takemae, Tadashi; Egami, Chikara; Tsuboi, Naoyuki

A sensing system using plastic optical fibers and reagent papers was developed for the detection of urine and abnormal level of its components simultaneously. Among several components of urine the detection of two main components namely, protein and glucose was confirmed experimentally. Three states of the papers namely dry and wet with and without change in color, were taken into consideration. These three states were divided by setting the lower and upper threshold voltages at 2.2 V and 5.5 V, respectively. This system is considered to be simple in construction, easy to operate and cost-efficient.

Simultaneous Chemical and Refractive Index Sensing in the 1-2.5 μm Near-Infrared Wavelength Range on Nanoporous Gold Disks.

PubMed

Shih, Wei-Chuan; Santos, Greggy M; Zhao, Fusheng; Zenasni, Oussama; Arnob, Md Masud Parvez

2016-07-13

Near-infrared (NIR) absorption spectroscopy provides molecular and chemical information based on overtones and combination bands of the fundamental vibrational modes in the infrared wavelengths. However, the sensitivity of NIR absorption measurement is limited by the generally weak absorption and the relatively poor detector performance compared to other wavelength ranges. To overcome these barriers, we have developed a novel technique to simultaneously obtain chemical and refractive index sensing in 1-2.5 μm NIR wavelength range on nanoporous gold (NPG) disks, which feature high-density plasmonic hot-spots of localized electric field enhancement. For the first time, surface-enhanced near-infrared absorption (SENIRA) spectroscopy has been demonstrated for high sensitivity chemical detection. With a self-assembled monolayer (SAM) of octadecanethiol (ODT), an enhancement factor (EF) of up to ∼10(4) has been demonstrated for the first C-H combination band at 2400 nm using NPG disk with 600 nm diameter. Together with localized surface plasmon resonance (LSPR) extinction spectroscopy, simultaneous sensing of sample refractive index has been achieved for the first time. The performance of this technique has been evaluated using various hydrocarbon compounds and crude oil samples.

Verification technology of remote sensing camera satellite imaging simulation based on ray tracing

NASA Astrophysics Data System (ADS)

Gu, Qiongqiong; Chen, Xiaomei; Yang, Deyun

2017-08-01

Remote sensing satellite camera imaging simulation technology is broadly used to evaluate the satellite imaging quality and to test the data application system. But the simulation precision is hard to examine. In this paper, we propose an experimental simulation verification method, which is based on the test parameter variation comparison. According to the simulation model based on ray-tracing, the experiment is to verify the model precision by changing the types of devices, which are corresponding the parameters of the model. The experimental results show that the similarity between the imaging model based on ray tracing and the experimental image is 91.4%, which can simulate the remote sensing satellite imaging system very well.

Contrast-based sensorless adaptive optics for retinal imaging.

PubMed

Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T O; He, Zheng; Metha, Andrew

2015-09-01

Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes.

Compressive sensing method for recognizing cat-eye effect targets.

PubMed

Li, Li; Li, Hui; Dang, Ersheng; Liu, Bo

2013-10-01

This paper proposes a cat-eye effect target recognition method with compressive sensing (CS) and presents a recognition method (sample processing before reconstruction based on compressed sensing, or SPCS) for image processing. In this method, the linear projections of original image sequences are applied to remove dynamic background distractions and extract cat-eye effect targets. Furthermore, the corresponding imaging mechanism for acquiring active and passive image sequences is put forward. This method uses fewer images to recognize cat-eye effect targets, reduces data storage, and translates the traditional target identification, based on original image processing, into measurement vectors processing. The experimental results show that the SPCS method is feasible and superior to the shape-frequency dual criteria method.

Quadratic grating apodized photon sieves for simultaneous multiplane microscopy

NASA Astrophysics Data System (ADS)

Cheng, Yiguang; Zhu, Jiangping; He, Yu; Tang, Yan; Hu, Song; Zhao, Lixin

2017-10-01

We present a new type of imaging device, named quadratic grating apodized photon sieve (QGPS), used as the objective for simultaneous multiplane imaging in X-rays. The proposed QGPS is structured based on the combination of two concepts: photon sieves and quadratic gratings. Its design principles are also expounded in detail. Analysis of imaging properties of QGPS in terms of point-spread function shows that QGPS can image multiple layers within an object field onto a single image plane. Simulated and experimental results in visible light both demonstrate the feasibility of QGPS for simultaneous multiplane imaging, which is extremely promising to detect dynamic specimens by X-ray microscopy in the physical and life sciences.

Optical and Electric Multifunctional CMOS Image Sensors for On-Chip Biosensing Applications.

PubMed

Tokuda, Takashi; Noda, Toshihiko; Sasagawa, Kiyotaka; Ohta, Jun

2010-12-29

In this review, the concept, design, performance, and a functional demonstration of multifunctional complementary metal-oxide-semiconductor (CMOS) image sensors dedicated to on-chip biosensing applications are described. We developed a sensor architecture that allows flexible configuration of a sensing pixel array consisting of optical and electric sensing pixels, and designed multifunctional CMOS image sensors that can sense light intensity and electric potential or apply a voltage to an on-chip measurement target. We describe the sensors' architecture on the basis of the type of electric measurement or imaging functionalities.

The implementation of CMOS sensors within a real time digital mammography intelligent imaging system: The I-ImaS System

NASA Astrophysics Data System (ADS)

Esbrand, C.; Royle, G.; Griffiths, J.; Speller, R.

2009-07-01

The integration of technology with healthcare has undoubtedly propelled the medical imaging sector well into the twenty first century. The concept of digital imaging introduced during the 1970s has since paved the way for established imaging techniques where digital mammography, phase contrast imaging and CT imaging are just a few examples. This paper presents a prototype intelligent digital mammography system designed and developed by a European consortium. The final system, the I-ImaS system, utilises CMOS monolithic active pixel sensor (MAPS) technology promoting on-chip data processing, enabling the acts of data processing and image acquisition to be achieved simultaneously; consequently, statistical analysis of tissue is achievable in real-time for the purpose of x-ray beam modulation via a feedback mechanism during the image acquisition procedure. The imager implements a dual array of twenty 520 pixel × 40 pixel CMOS MAPS sensing devices with a 32μm pixel size, each individually coupled to a 100μm thick thallium doped structured CsI scintillator. This paper presents the first intelligent images of real breast tissue obtained from the prototype system of real excised breast tissue where the x-ray exposure was modulated via the statistical information extracted from the breast tissue itself. Conventional images were experimentally acquired where the statistical analysis of the data was done off-line, resulting in the production of simulated real-time intelligently optimised images. The results obtained indicate real-time image optimisation using the statistical information extracted from the breast as a means of a feedback mechanisms is beneficial and foreseeable in the near future.

Frequency Based Design Partitioning to Achieve Higher Throughput in Digital Cross Correlator for Aperture Synthesis Passive MMW Imager.

PubMed

Asif, Muhammad; Guo, Xiangzhou; Zhang, Jing; Miao, Jungang

2018-04-17

Digital cross-correlation is central to many applications including but not limited to Digital Image Processing, Satellite Navigation and Remote Sensing. With recent advancements in digital technology, the computational demands of such applications have increased enormously. In this paper we are presenting a high throughput digital cross correlator, capable of processing 1-bit digitized stream, at the rate of up to 2 GHz, simultaneously on 64 channels i.e., approximately 4 Trillion correlation and accumulation operations per second. In order to achieve higher throughput, we have focused on frequency based partitioning of our design and tried to minimize and localize high frequency operations. This correlator is designed for a Passive Millimeter Wave Imager intended for the detection of contraband items concealed on human body. The goals are to increase the system bandwidth, achieve video rate imaging, improve sensitivity and reduce the size. Design methodology is detailed in subsequent sections, elaborating the techniques enabling high throughput. The design is verified for Xilinx Kintex UltraScale device in simulation and the implementation results are given in terms of device utilization and power consumption estimates. Our results show considerable improvements in throughput as compared to our baseline design, while the correlator successfully meets the functional requirements.

The fusion of large scale classified side-scan sonar image mosaics.

PubMed

Reed, Scott; Tena, Ruiz Ioseba; Capus, Chris; Petillot, Yvan

2006-07-01

This paper presents a unified framework for the creation of classified maps of the seafloor from sonar imagery. Significant challenges in photometric correction, classification, navigation and registration, and image fusion are addressed. The techniques described are directly applicable to a range of remote sensing problems. Recent advances in side-scan data correction are incorporated to compensate for the sonar beam pattern and motion of the acquisition platform. The corrected images are segmented using pixel-based textural features and standard classifiers. In parallel, the navigation of the sonar device is processed using Kalman filtering techniques. A simultaneous localization and mapping framework is adopted to improve the navigation accuracy and produce georeferenced mosaics of the segmented side-scan data. These are fused within a Markovian framework and two fusion models are presented. The first uses a voting scheme regularized by an isotropic Markov random field and is applicable when the reliability of each information source is unknown. The Markov model is also used to inpaint regions where no final classification decision can be reached using pixel level fusion. The second model formally introduces the reliability of each information source into a probabilistic model. Evaluation of the two models using both synthetic images and real data from a large scale survey shows significant quantitative and qualitative improvement using the fusion approach.

Laser radar: from early history to new trends

NASA Astrophysics Data System (ADS)

Molebny, Vasyl; Kamerman, Gary; Steinvall, Ove

2010-10-01

The first steps of laser radar are discussed with the examples from range finding and designation. The followed successes in field tests and further fast development provided their wide use. Coherent laser radar, developed almost simultaneously, tried the ideas from microwaves including chirp technology for pulse compression, and Doppler mode of operation. This latter found a unique implementation in a cruise missile. In many applications, environmental studies very strongly rely upon the lidars sensing the wind, temperature, constituents, optical parameters. Lidars are used in the atmosphere and in the sea water measurements. Imaging and mapping is an important role prescribed to ladars. One of the prospective trends in laser radar development is incorporation of range and velocity data into the image information. Deep space program, even having not come to the finish, gave a lot for 3D imaging. Gated imaging, as one of the 3D techniques, demonstrated its prospects (seeing through scattering layers) for military and security usage. Synthetic aperture laser radar, which had a long incubation period, started to show first results, at least in modeling. Coherent laser radar baptized as the optical coherence tomography, along with the position sensitive laser radar, synthetic aperture laser radar, multispectral laser radar demonstrated very pragmatic results in the micro-scale applications.

Multipurpose spectral imager.

PubMed

Sigernes, F; Lorentzen, D A; Heia, K; Svenøe, T

2000-06-20

A small spectral imaging system is presented that images static or moving objects simultaneously as a function of wavelength. The main physical principle is outlined and demonstrated. The instrument is capable of resolving both spectral and spatial information from targets throughout the entire visible region. The spectral domain has a bandpass of 12 A. One can achieve the spatial domain by rotating the system's front mirror with a high-resolution stepper motor. The spatial resolution range from millimeters to several meters depends mainly on the front optics used and whether the target is fixed (static) or movable relative to the instrument. Different applications and examples are explored, including outdoor landscapes, industrial fish-related targets, and ground-level objects observed in the more traditional way from an airborne carrier (remote sensing). Through the examples, we found that the instrument correctly classifies whether a shrimp is peeled and whether it can disclose the spectral and spatial microcharacteristics of targets such as a fish nematode (parasite). In the macroregime, we were able to distinguish a marine vessel from the surrounding sea and sky. A study of the directional spectral albedo from clouds, mountains, snow cover, and vegetation has also been included. With the airborne experiment, the imager successfully classified snow cover, leads, and new and rafted ice, as seen from 10.000 ft (3.048 m).

Topological visual mapping in robotics.

PubMed

Romero, Anna; Cazorla, Miguel

2012-08-01

A key problem in robotics is the construction of a map from its environment. This map could be used in different tasks, like localization, recognition, obstacle avoidance, etc. Besides, the simultaneous location and mapping (SLAM) problem has had a lot of interest in the robotics community. This paper presents a new method for visual mapping, using topological instead of metric information. For that purpose, we propose prior image segmentation into regions in order to group the extracted invariant features in a graph so that each graph defines a single region of the image. Although others methods have been proposed for visual SLAM, our method is complete, in the sense that it makes all the process: it presents a new method for image matching; it defines a way to build the topological map; and it also defines a matching criterion for loop-closing. The matching process will take into account visual features and their structure using the graph transformation matching (GTM) algorithm, which allows us to process the matching and to remove out the outliers. Then, using this image comparison method, we propose an algorithm for constructing topological maps. During the experimentation phase, we will test the robustness of the method and its ability constructing topological maps. We have also introduced new hysteresis behavior in order to solve some problems found building the graph.

Method of determining forest production from remotely sensed forest parameters

DOEpatents

Corey, J.C.; Mackey, H.E. Jr.

1987-08-31

A method of determining forest production entirely from remotely sensed data in which remotely sensed multispectral scanner (MSS) data on forest 5 composition is combined with remotely sensed radar imaging data on forest stand biophysical parameters to provide a measure of forest production. A high correlation has been found to exist between the remotely sensed radar imaging data and on site measurements of biophysical 10 parameters such as stand height, diameter at breast height, total tree height, mean area per tree, and timber stand volume.

Application of Compressive Sensing to Gravitational Microlensing Experiments

NASA Astrophysics Data System (ADS)

Korde-Patel, Asmita; Barry, Richard K.; Mohsenin, Tinoosh

2017-06-01

Compressive Sensing is an emerging technology for data compression and simultaneous data acquisition. This is an enabling technique for significant reduction in data bandwidth, and transmission power and hence, can greatly benefit space-flight instruments. We apply this process to detect exoplanets via gravitational microlensing. We experiment with various impact parameters that describe microlensing curves to determine the effectiveness and uncertainty caused by Compressive Sensing. Finally, we describe implications for space-flight missions.

Multispectral remote sensing from unmanned aircraft: image processing workflows and applications for rangeland environments

USDA-ARS?s Scientific Manuscript database

Using unmanned aircraft systems (UAS) as remote sensing platforms offers the unique ability for repeated deployment for acquisition of high temporal resolution data at very high spatial resolution. Most image acquisitions from UAS have been in the visible bands, while multispectral remote sensing ap...

Satellites, Remote Sensing, and Classroom Geography for Canadian Teachers.

ERIC Educational Resources Information Center

Kirman, Joseph M.

1998-01-01

Argues that remote sensing images are a powerful tool for teaching geography. Discusses the use of remote sensing images in the classroom and provides a number of sources for them, some free, many on the World Wide Web. Reviews each source's usefulness for different grade levels and geographic topics. (DSK)

Reliable clarity automatic-evaluation method for optical remote sensing images

NASA Astrophysics Data System (ADS)

Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen

2015-10-01

Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.

Photogrammetric Processing of Planetary Linear Pushbroom Images Based on Approximate Orthophotos

NASA Astrophysics Data System (ADS)

Geng, X.; Xu, Q.; Xing, S.; Hou, Y. F.; Lan, C. Z.; Zhang, J. J.

2018-04-01

It is still a great challenging task to efficiently produce planetary mapping products from orbital remote sensing images. There are many disadvantages in photogrammetric processing of planetary stereo images, such as lacking ground control information and informative features. Among which, image matching is the most difficult job in planetary photogrammetry. This paper designs a photogrammetric processing framework for planetary remote sensing images based on approximate orthophotos. Both tie points extraction for bundle adjustment and dense image matching for generating digital terrain model (DTM) are performed on approximate orthophotos. Since most of planetary remote sensing images are acquired by linear scanner cameras, we mainly deal with linear pushbroom images. In order to improve the computational efficiency of orthophotos generation and coordinates transformation, a fast back-projection algorithm of linear pushbroom images is introduced. Moreover, an iteratively refined DTM and orthophotos scheme was adopted in the DTM generation process, which is helpful to reduce search space of image matching and improve matching accuracy of conjugate points. With the advantages of approximate orthophotos, the matching results of planetary remote sensing images can be greatly improved. We tested the proposed approach with Mars Express (MEX) High Resolution Stereo Camera (HRSC) and Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) images. The preliminary experimental results demonstrate the feasibility of the proposed approach.

Research Issues in Image Registration for Remote Sensing

NASA Technical Reports Server (NTRS)

Eastman, Roger D.; LeMoigne, Jacqueline; Netanyahu, Nathan S.

2007-01-01

Image registration is an important element in data processing for remote sensing with many applications and a wide range of solutions. Despite considerable investigation the field has not settled on a definitive solution for most applications and a number of questions remain open. This article looks at selected research issues by surveying the experience of operational satellite teams, application-specific requirements for Earth science, and our experiments in the evaluation of image registration algorithms with emphasis on the comparison of algorithms for subpixel accuracy. We conclude that remote sensing applications put particular demands on image registration algorithms to take into account domain-specific knowledge of geometric transformations and image content.

A simultaneous pressure and temperature sensor based on a superstructure fiber grating

NASA Astrophysics Data System (ADS)

Lin, Chia-Min; Liu, Wen-Fung; Fu, Ming-Yue; Sheng, Hao-Jan; Bor, Sheau-Shung; Tien, Chuen-Lin

2004-12-01

We demonstrated that a high-sensitivity fiber sensor based on a superstructure fiber grating (SFG) can simultaneously measure the pressure and temperature by encapsulating the grating in a polymer-half-filled metal cylinder, in which there are two openings on opposite sides of the wall filled with the polymer to sense the pressure. The mechanism of sensing pressure is to transfer the pressure into the axial extended-strain. According to the optical characteristics of an SFG composed of a fiber Bragg grating (FBG) and long period grating (LPG), the various pressure and temperature will cause the variation of the center-wavelength and reflection simultaneously. Thus, the sensor can be used for the measurement both of the pressure and temperature. The pressure sensitivity of 2.28×10-2MPa-1 and the temperature sensitivity both of 0.015nm/°C and -0.143dB/°C are obtained.

Processing ultrasound backscatter to monitor high-intensity focused ultrasound (HIFU) therapy

NASA Astrophysics Data System (ADS)

Kaczkowski, Peter J.; Anand, Ajay; Bailey, Michael R.

2005-09-01

The development of new noninvasive surgical methods such as HIFU for the treatment of cancer and internal bleeding requires simultaneous development of new sensing approaches to guide, monitor, and assess the therapy. Ultrasound imaging using echo amplitude has long been used to map tissue morphology for diagnostic interpretation by the clinician. New quantitative ultrasonic methods that rely on amplitude and phase processing for tissue characterization are being developed for monitoring of ablative therapy. We have been developing the use of full wave ultrasound backscattering for real-time temperature estimation, and to image changes in tissue backscatter spectrum as therapy progresses. Both approaches rely on differential processing of the backscatter signal in time, and precise measurement of phase differences. Noise and artifacts from motion and nonstationary speckle statistics are addressed by constraining inversions for tissue parameters with physical models. We present results of HIFU experiments with static point and scanned HIFU exposures in which temperature rise can be accurately mapped using a new heat transfer equation (HTE) model-constrained inverse approach. We also present results of a recently developed spectral imaging method that elucidates microbubble-mediated nonlinearity not visible as a change in backscatter amplitude. [Work supported by Army MRMC.

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

Leary, T.J.; Lamb, A.

The Department of Energy`s Office of Arms Control and Non-Proliferation (NN-20) has developed a suite of airborne remote sensing systems that simultaneously collect coincident data from a US Navy P-3 aircraft. The primary objective of the Airborne Multisensor Pod System (AMPS) Program is {open_quotes}to collect multisensor data that can be used for data research, both to reduce interpretation problems associated with data overload and to develop information products more complete than can be obtained from any single sensor.{close_quotes} The sensors are housed in wing-mounted pods and include: a Ku-Band Synthetic Aperture Radar; a CASI Hyperspectral Imager; a Daedalus 3600 Airbornemore » Multispectral Scanner; a Wild Heerbrugg RC-30 motion compensated large format camera; various high resolution, light intensified and thermal video cameras; and several experimental sensors (e.g. the Portable Hyperspectral Imager of Low-Light Spectroscopy (PHILLS)). Over the past year or so, the Coastal Marine Resource Assessment (CAMRA) group at the Florida Department of Environmental Protection`s Marine Research Institute (FMRI) has been working with the Department of Energy through the Naval Research Laboratory to develop applications and products from existing data. Considerable effort has been spent identifying image formats integration parameters. 2 refs., 3 figs., 2 tabs.« less

Augmented reality with image registration, vision correction and sunlight readability via liquid crystal devices.

PubMed

Wang, Yu-Jen; Chen, Po-Ju; Liang, Xiao; Lin, Yi-Hsin

2017-03-27

Augmented reality (AR), which use computer-aided projected information to augment our sense, has important impact on human life, especially for the elder people. However, there are three major challenges regarding the optical system in the AR system, which are registration, vision correction, and readability under strong ambient light. Here, we solve three challenges simultaneously for the first time using two liquid crystal (LC) lenses and polarizer-free attenuator integrated in optical-see-through AR system. One of the LC lens is used to electrically adjust the position of the projected virtual image which is so-called registration. The other LC lens with larger aperture and polarization independent characteristic is in charge of vision correction, such as myopia and presbyopia. The linearity of lens powers of two LC lenses is also discussed. The readability of virtual images under strong ambient light is solved by electrically switchable transmittance of the LC attenuator originating from light scattering and light absorption. The concept demonstrated in this paper could be further extended to other electro-optical devices as long as the devices exhibit the capability of phase modulations and amplitude modulations.

Enabling Technologies for High-accuracy Multiangle Spectropolarimetric Imaging from Space

NASA Technical Reports Server (NTRS)

Diner, David J.; Macenka, Steven A.; Seshndri, Suresh; Bruce, Carl E; Jau, Bruno; Chipman, Russell A.; Cairns, Brian; Christoph, Keller; Foo, Leslie D.

2004-01-01

Satellite remote sensing plays a major role in measuring the optical and radiative properties, environmental impact, and spatial and temporal distribution of tropospheric aerosols. In this paper, we envision a new generation of spaceborne imager that integrates the unique strengths of multispectral, multiangle, and polarimetric approaches, thereby achieving better accuracies in aerosol optical depth and particle properties than can be achieved using any one method by itself. Design goals include spectral coverage from the near-UV to the shortwave infrared; global coverage within a few days; intensity and polarimetric imaging simultaneously at multiple view angles; kilometer to sub-kilometer spatial resolution; and measurement of the degree of linear polarization for a subset of the spectral complement with an uncertainty of 0.5% or less. The latter requirement is technically the most challenging. In particular, an approach for dealing with inter-detector gain variations is essential to avoid false polarization signals. We propose using rapid modulation of the input polarization state to overcome this problem, using a high-speed variable retarder in the camera design. Technologies for rapid retardance modulation include mechanically rotating retarders, liquid crystals, and photoelastic modulators (PEMs). We conclude that the latter are the most suitable.

Systems approach to the design of the CCD sensors and camera electronics for the AIA and HMI instruments on solar dynamics observatory

NASA Astrophysics Data System (ADS)

Waltham, N.; Beardsley, S.; Clapp, M.; Lang, J.; Jerram, P.; Pool, P.; Auker, G.; Morris, D.; Duncan, D.

2017-11-01

Solar Dynamics Observatory (SDO) is imaging the Sun in many wavelengths near simultaneously and with a resolution ten times higher than the average high-definition television. In this paper we describe our innovative systems approach to the design of the CCD cameras for two of SDO's remote sensing instruments, the Atmospheric Imaging Assembly (AIA) and the Helioseismic and Magnetic Imager (HMI). Both instruments share use of a custom-designed 16 million pixel science-grade CCD and common camera readout electronics. A prime requirement was for the CCD to operate with significantly lower drive voltages than before, motivated by our wish to simplify the design of the camera readout electronics. Here, the challenge lies in the design of circuitry to drive the CCD's highly capacitive electrodes and to digitize its analogue video output signal with low noise and to high precision. The challenge is greatly exacerbated when forced to work with only fully space-qualified, radiation-tolerant components. We describe our systems approach to the design of the AIA and HMI CCD and camera electronics, and the engineering solutions that enabled us to comply with both mission and instrument science requirements.

Dynamic Liver Magnetic Resonance Imaging in Free-Breathing: Feasibility of a Cartesian T1-Weighted Acquisition Technique With Compressed Sensing and Additional Self-Navigation Signal for Hard-Gated and Motion-Resolved Reconstruction.

PubMed

Kaltenbach, Benjamin; Bucher, Andreas M; Wichmann, Julian L; Nickel, Dominik; Polkowski, Christoph; Hammerstingl, Renate; Vogl, Thomas J; Bodelle, Boris

2017-11-01

The aim of this study was to assess the feasibility of a free-breathing dynamic liver imaging technique using a prototype Cartesian T1-weighted volumetric interpolated breathhold examination (VIBE) sequence with compressed sensing and simultaneous acquisition of a navigation signal for hard-gated and motion state-resolved reconstruction. A total of 43 consecutive oncologic patients (mean age, 66 ± 11 years; 44% female) underwent free-breathing dynamic liver imaging for the evaluation of liver metastases from colorectal cancer using a prototype Cartesian VIBE sequence (field of view, 380 × 345 mm; image matrix, 320 × 218; echo time/repetition time, 1.8/3.76 milliseconds; flip angle, 10 degrees; slice thickness, 3.0 mm; acquisition time, 188 seconds) with continuous data sampling and additionally acquired self-navigation signal. Data were iteratively reconstructed using 2 different approaches: first, a hard-gated reconstruction only using data associated to the dominating motion state (CS VIBE, Compressed Sensing VIBE), and second, a motion-resolved reconstruction with 6 different motion states as additional image dimension (XD VIBE, eXtended dimension VIBE). Continuous acquired data were grouped in 16 subsequent time increments with 11.57 seconds each to resolve arterial and venous contrast phases. For image quality assessment, both CS VIBE and XD VIBE were compared with the patient's last staging dynamic liver magnetic resonance imaging including a breathhold (BH) VIBE as reference standard 4.5 ± 1.2 months before. Representative quality parameters including respiratory artifacts were evaluated for arterial and venous phase images independently, retrospectively and blindly by 3 experienced radiologists, with higher scores indicating better examination quality. To assess diagnostic accuracy, same readers evaluated the presence of metastatic lesions for XD VIBE and CS VIBE compared with reference BH examination in a second session. Compared with CS VIBE, XD VIBE showed significantly higher overall image quality for both arterial phase (4.2 ± 0.6 vs 3.8 ± 0.7, P = 0.008) and venous phase (4.7 ± 0.4 vs 4.3 ± 0.7, P < 0.001) imaging. There was no significant difference between XD VIBE and BH VIBE for overall image quality in the venous phase (4.7 ± 0.4 vs 4.8 ± 0.4, P = 0.834), whereas arterial phase images were scored slightly lower for XD VIBE (4.5 ± 0.6 vs 4.2 ± 0.6, P = 0.024). Both XD VIBE and BH VIBE were characterized by a very low level of respiratory artifacts with no significant difference between BH and motion-resolved free-breathing strategy (P = 0.505 for arterial phase; P = 0.496 for venous phase). Compared with CS VIBE, obvious quality improvement could be achieved for the extended XD VIBE reconstruction with significantly reduced motion artifacts for venous phase images (P = 0.007). Generally, arterial phase images were scored slightly lower compared with venous phase images when using the free-breathing protocol. Overall, 98% of all metastatic lesions were identified on XD VIBE images and 92% of all metastases were found on CS VIBE. Dynamic liver imaging using the proposed free-breathing Cartesian strategy is feasible in oncologic patients with excellent image quality, high respiratory motion robustness, and accurate lesion detection. Overall, XD VIBE was superior to CS VIBE in our study.

Biophotonic endoscopy: a review of clinical research techniques for optical imaging and sensing of early gastrointestinal cancer

PubMed Central

Coda, Sergio; Siersema, Peter D.; Stamp, Gordon W. H.; Thillainayagam, Andrew V.

2015-01-01

Detection, characterization, and staging constitute the fundamental elements in the endoscopic diagnosis of gastrointestinal diseases, but histology still remains the diagnostic gold standard. New developments in endoscopic techniques may challenge histopathology in the near future. An ideal endoscopic technique should combine a wide-field, “red flag” screening technique with an optical contrast or microscopy method for characterization and staging, all simultaneously available during the procedure. In theory, biophotonic advances have the potential to unite these elements to allow in vivo “optical biopsy.” These techniques may ultimately offer the potential to increase the rates of detection of high risk lesions and the ability to target biopsies and resections, and so reduce the need for biopsy, costs, and uncertainty for patients. However, their utility and sensitivity in clinical practice must be evaluated against those of conventional histopathology. This review describes some of the most recent applications of biophotonics in endoscopic optical imaging and metrology, along with their fundamental principles and the clinical experience that has been acquired in their deployment as tools for the endoscopist. Particular emphasis has been placed on translational label-free optical techniques, such as fluorescence spectroscopy, fluorescence lifetime imaging microscopy (FLIM), two-photon and multi-photon microscopy, second harmonic generation (SHG) and third harmonic generation (THG) imaging, optical coherence tomography (OCT), diffuse reflectance, Raman spectroscopy, and molecular imaging. PMID:26528489

Low SWaP multispectral sensors using dichroic filter arrays

NASA Astrophysics Data System (ADS)

Dougherty, John; Varghese, Ron

2015-06-01

The benefits of multispectral imaging are well established in a variety of applications including remote sensing, authentication, satellite and aerial surveillance, machine vision, biomedical, and other scientific and industrial uses. However, many of the potential solutions require more compact, robust, and cost-effective cameras to realize these benefits. The next generation of multispectral sensors and cameras needs to deliver improvements in size, weight, power, portability, and spectral band customization to support widespread deployment for a variety of purpose-built aerial, unmanned, and scientific applications. A novel implementation uses micro-patterning of dichroic filters1 into Bayer and custom mosaics, enabling true real-time multispectral imaging with simultaneous multi-band image acquisition. Consistent with color image processing, individual spectral channels are de-mosaiced with each channel providing an image of the field of view. This approach can be implemented across a variety of wavelength ranges and on a variety of detector types including linear, area, silicon, and InGaAs. This dichroic filter array approach can also reduce payloads and increase range for unmanned systems, with the capability to support both handheld and autonomous systems. Recent examples and results of 4 band RGB + NIR dichroic filter arrays in multispectral cameras are discussed. Benefits and tradeoffs of multispectral sensors using dichroic filter arrays are compared with alternative approaches - including their passivity, spectral range, customization options, and scalable production.

Accessing the exceptional points of parity-time symmetric acoustics

PubMed Central

Shi, Chengzhi; Dubois, Marc; Chen, Yun; Cheng, Lei; Ramezani, Hamidreza; Wang, Yuan; Zhang, Xiang

2016-01-01

Parity-time (PT) symmetric systems experience phase transition between PT exact and broken phases at exceptional point. These PT phase transitions contribute significantly to the design of single mode lasers, coherent perfect absorbers, isolators, and diodes. However, such exceptional points are extremely difficult to access in practice because of the dispersive behaviour of most loss and gain materials required in PT symmetric systems. Here we introduce a method to systematically tame these exceptional points and control PT phases. Our experimental demonstration hinges on an active acoustic element that realizes a complex-valued potential and simultaneously controls the multiple interference in the structure. The manipulation of exceptional points offers new routes to broaden applications for PT symmetric physics in acoustics, optics, microwaves and electronics, which are essential for sensing, communication and imaging. PMID:27025443

Encryption method based on pseudo random spatial light modulation for single-fibre data transmission

NASA Astrophysics Data System (ADS)

Kowalski, Marcin; Zyczkowski, Marek

2017-11-01

Optical cryptosystems can provide encryption and sometimes compression simultaneously. They are increasingly attractive for information securing especially for image encryption. Our studies shown that the optical cryptosystems can be used to encrypt optical data transmission. We propose and study a new method for securing fibre data communication. The paper presents a method for optical encryption of data transmitted with a single optical fibre. The encryption process relies on pseudo-random spatial light modulation, combination of two encryption keys and the Compressed Sensing framework. A linear combination of light pulses with pseudo-random patterns provides a required encryption performance. We propose an architecture to transmit the encrypted data through the optical fibre. The paper describes the method, presents the theoretical analysis, design of physical model and results of experiment.

5.8 X-ray Calorimeters

NASA Technical Reports Server (NTRS)

Porter, F. Scott

2008-01-01

X-ray calorimeter instruments for astrophysics have seen rapid development since they were invented in 1984. The prime instrument on all currently planned X-ray spectroscopic observatories is based on calorimeter technology. This relatively simple detection concept that senses the energy of an incident photon by measuring the temperature rise of an absorber material at very low temperatures, can form the basis of a very high performance, non-dispersive spectrometer. State-of-the-art calorimeter instruments have resolving powers of over 3000, large simultaneous band-passes, and near unit efficiency. This coupled with the intrinsic imaging capability of a pixilated x-ray calorimeter array, allows true spectral-spatial instruments to be constructed. In this chapter I briefly review the detection scheme, the state-of-the-art in X-ray calorimeter instruments and the future outlook for this technology.

Derivative Analysis of AVIRIS Hyperspectral Data for the Detection of Plant Stress

NASA Technical Reports Server (NTRS)

Estep, Lee; Berglund, Judith

2001-01-01

A remote sensing campaign was conducted over a U.S. Department of Agriculture test site at Shelton, Nebraska. The test field was set off in blocks that were differentially treated with nitrogen. Four replicates of 0-kg/ha to 200-kg/ha, in 50-kg/ha increments, were present. Low-altitude AVIRIS hyperspectral data were collected over the site in 224 spectral bands. Simultaneously, ground data were collected to support the airborne imagery. In an effort to evaluate published, derivative-based algorithms for the detection of plant stress, different derivative-based approaches were applied to the collected AVIRIS image cube. The results indicate that, given good quality hyperspectral imagery, derivative techniques compare favorably with simple, well known band ratio algorithms for detection of plant stress.

Label-Free Carbon-Dots-Based Ratiometric Fluorescence pH Nanoprobes for Intracellular pH Sensing.

PubMed

Shangguan, Jingfang; He, Dinggeng; He, Xiaoxiao; Wang, Kemin; Xu, Fengzhou; Liu, Jinquan; Tang, Jinlu; Yang, Xue; Huang, Jin

2016-08-02

Measuring pH in living cells is of great importance for better understanding cellular functions as well as providing pivotal assistance for early diagnosis of diseases. In this work, we report the first use of a novel kind of label-free carbon dots for intracellular ratiometric fluorescence pH sensing. By simple one-pot hydrothermal treatment of citric acid and basic fuchsin, the carbon dots showing dual emission bands at 475 and 545 nm under single-wavelength excitation were synthesized. It is demonstrated that the fluorescence intensities of the as-synthesized carbon dots at the two emissions are pH-sensitive simultaneously. The intensity ratio (I475 nm/I545 nm) is linear against pH values from 5.2 to 8.8 in buffer solution, affording the capability as ratiometric probes for intracellular pH sensing. It also displays that the carbon dots show excellent reversibility and photostability in pH measurements. With this nanoprobe, quantitative fluorescence imaging using the ratio of two emissions (I475 nm/I545 nm) for the detection of intracellular pH were successfully applied in HeLa cells. In contrast to most of the reported nanomaterials-based ratiometric pH sensors which rely on the attachment of additional dyes, these carbon-dots-based ratiometric probes are low in toxicity, easy to synthesize, and free from labels.

A multichannel smartphone optical biosensor for high-throughput point-of-care diagnostics.

PubMed

Wang, Li-Ju; Chang, Yu-Chung; Sun, Rongrong; Li, Lei

2017-01-15

Current reported smartphone spectrometers are only used to monitor or measure one sample at a time. For the first time, we demonstrate a multichannel smartphone spectrometer (MSS) as an optical biosensor that can simultaneously optical sense multiple samples. In this work, we developed a novel method to achieve the multichannel optical spectral sensing with nanometer resolution on a smartphone. A 3D printed cradle held the smartphone integrated with optical components. This optical sensor performed accurate and reliable spectral measurements by optical intensity changes at specific wavelength or optical spectral shifts. A custom smartphone multi-view App was developed to control the optical sensing parameters and to align each sample to the corresponding channel. The captured images were converted to the transmission spectra in the visible wavelength range from 400nm to 700nm with the high resolution of 0.2521nm per pixel. We validated the performance of this MSS via measuring the concentrations of protein and immunoassaying a type of human cancer biomarker. Compared to the standard laboratory instrument, the results sufficiently showed that this MSS can achieve the comparative analysis detection limits, accuracy and sensitivity. We envision that this multichannel smartphone optical biosensor will be useful in high-throughput point-of-care diagnostics with its minimizing size, light weight, low cost and data transmission function. Copyright © 2016 Elsevier B.V. All rights reserved.

Illumination invariant feature point matching for high-resolution planetary remote sensing images

NASA Astrophysics Data System (ADS)

Wu, Bo; Zeng, Hai; Hu, Han

2018-03-01

Despite its success with regular close-range and remote-sensing images, the scale-invariant feature transform (SIFT) algorithm is essentially not invariant to illumination differences due to the use of gradients for feature description. In planetary remote sensing imagery, which normally lacks sufficient textural information, salient regions are generally triggered by the shadow effects of keypoints, reducing the matching performance of classical SIFT. Based on the observation of dual peaks in a histogram of the dominant orientations of SIFT keypoints, this paper proposes an illumination-invariant SIFT matching method for high-resolution planetary remote sensing images. First, as the peaks in the orientation histogram are generally aligned closely with the sub-solar azimuth angle at the time of image collection, an adaptive suppression Gaussian function is tuned to level the histogram and thereby alleviate the differences in illumination caused by a changing solar angle. Next, the suppression function is incorporated into the original SIFT procedure for obtaining feature descriptors, which are used for initial image matching. Finally, as the distribution of feature descriptors changes after anisotropic suppression, and the ratio check used for matching and outlier removal in classical SIFT may produce inferior results, this paper proposes an improved matching procedure based on cross-checking and template image matching. The experimental results for several high-resolution remote sensing images from both the Moon and Mars, with illumination differences of 20°-180°, reveal that the proposed method retrieves about 40%-60% more matches than the classical SIFT method. The proposed method is of significance for matching or co-registration of planetary remote sensing images for their synergistic use in various applications. It also has the potential to be useful for flyby and rover images by integrating with the affine invariant feature detectors.

Earth view: A business guide to orbital remote sensing

NASA Technical Reports Server (NTRS)

Bishop, Peter C.

1990-01-01

The following subject areas are covered: Earth view - a guide to orbital remote sensing; current orbital remote sensing systems (LANDSAT, SPOT image, MOS-1, Soviet remote sensing systems); remote sensing satellite; and remote sensing organizations.

Modeling Habitat Suitability of Migratory Birds from Remote Sensing Images Using Convolutional Neural Networks.

PubMed

Su, Jin-He; Piao, Ying-Chao; Luo, Ze; Yan, Bao-Ping

2018-04-26

With the application of various data acquisition devices, a large number of animal movement data can be used to label presence data in remote sensing images and predict species distribution. In this paper, a two-stage classification approach for combining movement data and moderate-resolution remote sensing images was proposed. First, we introduced a new density-based clustering method to identify stopovers from migratory birds’ movement data and generated classification samples based on the clustering result. We split the remote sensing images into 16 × 16 patches and labeled them as positive samples if they have overlap with stopovers. Second, a multi-convolution neural network model is proposed for extracting the features from temperature data and remote sensing images, respectively. Then a Support Vector Machines (SVM) model was used to combine the features together and predict classification results eventually. The experimental analysis was carried out on public Landsat 5 TM images and a GPS dataset was collected on 29 birds over three years. The results indicated that our proposed method outperforms the existing baseline methods and was able to achieve good performance in habitat suitability prediction.

Measuring Effects Of Lightning On Power And Telephone Lines

NASA Technical Reports Server (NTRS)

Jafferis, William; Thompson, E. M.; Medelius, P.; Rubinstein, M.; Tzeng, A.

1992-01-01

Spherical antenna senses both horizontal and vertical fields simultaneously. Measures "fast" components of electric field used in conjunction with other equipment, including antenna measuring "slow" vertical component of electric field; microphone that senses thunder; cameras making visual records, which locate lightning; magnetic-field sensor; optical sensors; and instruments measuring speed and direction of wind.

An approach to improve the spatial resolution of a force mapping sensing system

NASA Astrophysics Data System (ADS)

Negri, Lucas Hermann; Manfron Schiefer, Elberth; Sade Paterno, Aleksander; Muller, Marcia; Luís Fabris, José

2016-02-01

This paper proposes a smart sensor system capable of detecting sparse forces applied to different positions of a metal plate. The sensing is performed with strain transducers based on fiber Bragg gratings (FBG) distributed under the plate. Forces actuating in nine squared regions of the plate, resulting from up to three different loads applied simultaneously to the plate, were monitored with seven transducers. The system determines the magnitude of the force/pressure applied on each specific area, even in the absence of a dedicated transducer for that area. The set of strain transducers with coupled responses and a compressive sensing algorithm are employed to solve the underdetermined inverse problem which emerges from mapping the force. In this configuration, experimental results have shown that the system is capable of recovering the value of the load distributed on the plate with a signal-to-noise ratio better than 12 dB, when the plate is submitted to three simultaneous test loads. The proposed method is a practical illustration of compressive sensing algorithms for the reduction of the number of FBG-based transducers used in a quasi-distributed configuration.

Usefulness of the dynamic gadolinium-enhanced magnetic resonance imaging with simultaneous acquisition of coronal and sagittal planes for detection of pituitary microadenomas.

PubMed

Lee, Han Bee; Kim, Sung Tae; Kim, Hyung-Jin; Kim, Keon Ha; Jeon, Pyoung; Byun, Hong Sik; Choi, Jin Wook

2012-03-01

Does dynamic gadolinium-enhanced imaging with simultaneous acquisition of coronal and sagittal planes improve diagnostic accuracy of pituitary microadenomas compared with coronal images alone? Fifty-six patients underwent 3-T sella MRI including dynamic simultaneous acquisition of coronal and sagittal planes after gadolinium injection. According to conspicuity, lesions were divided into four scores (0, no; 1, possible; 2, probable; 3, definite delayed enhancing lesion). Additional information on supplementary sagittal images compared with coronal ones was evaluated with a 4-point score (0, no; 1, possible; 2, probable; 3, definite additional information). Accuracy of tumour detection was calculated. Average scores for lesion detection of a combination of two planes, coronal, and sagittal images were 2.59, 2.32, and 2.18. 6/10 lesions negative on coronal images were detected on sagittal ones. Accuracy of a combination of two planes, of coronal and of sagittal images was 92.86%, 82.14% and 75%. Six patients had probable or definite additional information on supplementary sagittal images compared with coronal ones alone (10.71%). Dynamic MRI with combined coronal and sagittal planes was more accurate for detection of pituitary microadenomas than routinely used coronal images. Simultaneous dynamic enhanced acquisition can make study time fast and costs low. We present a new dynamic MRI technique for evaluating pituitary microadenomas • This technique provides simultaneous acquisition of contrast enhanced coronal and sagittal images. • This technique makes the diagnosis more accurate and reduces the examination time. • Such MR imaging only requires one single bolus of contrast agent.

System and method for object localization

NASA Technical Reports Server (NTRS)

Kelly, Alonzo J. (Inventor); Zhong, Yu (Inventor)

2005-01-01

A computer-assisted method for localizing a rack, including sensing an image of the rack, detecting line segments in the sensed image, recognizing a candidate arrangement of line segments in the sensed image indicative of a predetermined feature of the rack, generating a matrix of correspondence between the candidate arrangement of line segments and an expected position and orientation of the predetermined feature of the rack, and estimating a position and orientation of the rack based on the matrix of correspondence.

Researching on the process of remote sensing video imagery

NASA Astrophysics Data System (ADS)

Wang, He-rao; Zheng, Xin-qi; Sun, Yi-bo; Jia, Zong-ren; Wang, He-zhan

Unmanned air vehicle remotely-sensed imagery on the low-altitude has the advantages of higher revolution, easy-shooting, real-time accessing, etc. It's been widely used in mapping , target identification, and other fields in recent years. However, because of conditional limitation, the video images are unstable, the targets move fast, and the shooting background is complex, etc., thus it is difficult to process the video images in this situation. In other fields, especially in the field of computer vision, the researches on video images are more extensive., which is very helpful for processing the remotely-sensed imagery on the low-altitude. Based on this, this paper analyzes and summarizes amounts of video image processing achievement in different fields, including research purposes, data sources, and the pros and cons of technology. Meantime, this paper explores the technology methods more suitable for low-altitude video image processing of remote sensing.

A scene-analysis approach to remote sensing. [San Francisco, California

NASA Technical Reports Server (NTRS)

Tenenbaum, J. M. (Principal Investigator); Fischler, M. A.; Wolf, H. C.

1978-01-01

The author has identified the following significant results. Geometric correspondance between a sensed image and a symbolic map is established in an initial stage of processing by adjusting parameters of a sensed model so that the image features predicted from the map optimally match corresponding features extracted from the sensed image. Information in the map is then used to constrain where to look in an image, what to look for, and how to interpret what is seen. For simple monitoring tasks involving multispectral classification, these constraints significantly reduce computation, simplify interpretation, and improve the utility of the resulting information. Previously intractable tasks requiring spatial and textural analysis may become straightforward in the context established by the map knowledge. The use of map-guided image analysis in monitoring the volume of water in a reservoir, the number of boxcars in a railyard, and the number of ships in a harbor is demonstrated.

The edge-preservation multi-classifier relearning framework for the classification of high-resolution remotely sensed imagery

NASA Astrophysics Data System (ADS)

Han, Xiaopeng; Huang, Xin; Li, Jiayi; Li, Yansheng; Yang, Michael Ying; Gong, Jianya

2018-04-01

In recent years, the availability of high-resolution imagery has enabled more detailed observation of the Earth. However, it is imperative to simultaneously achieve accurate interpretation and preserve the spatial details for the classification of such high-resolution data. To this aim, we propose the edge-preservation multi-classifier relearning framework (EMRF). This multi-classifier framework is made up of support vector machine (SVM), random forest (RF), and sparse multinomial logistic regression via variable splitting and augmented Lagrangian (LORSAL) classifiers, considering their complementary characteristics. To better characterize complex scenes of remote sensing images, relearning based on landscape metrics is proposed, which iteratively quantizes both the landscape composition and spatial configuration by the use of the initial classification results. In addition, a novel tri-training strategy is proposed to solve the over-smoothing effect of relearning by means of automatic selection of training samples with low classification certainties, which always distribute in or near the edge areas. Finally, EMRF flexibly combines the strengths of relearning and tri-training via the classification certainties calculated by the probabilistic output of the respective classifiers. It should be noted that, in order to achieve an unbiased evaluation, we assessed the classification accuracy of the proposed framework using both edge and non-edge test samples. The experimental results obtained with four multispectral high-resolution images confirm the efficacy of the proposed framework, in terms of both edge and non-edge accuracy.

Airborne Remote Sensing of River Flow and Morphology

NASA Astrophysics Data System (ADS)

Zuckerman, S.; Anderson, S. P.; McLean, J.; Redford, R.

2014-12-01

River morphology, surface slope and flow are some of the fundamental measurements required for surface water monitoring and hydrodynamic research. This paper describes a method of combining bathymetric lidar with space-time processing of mid-wave infrared (MWIR) imagery to simultaneously measure bathymetry, currents and surface slope from an airborne platform. In May 2014, Areté installed a Pushbroom Imaging Lidar for Littoral Surveillance (PILLS) and a FLIR SC8000 MWIR imaging system sampling at 2 Hz in a small twin-engine aircraft. Data was collected over the lower Colorado River between Picacho Park and Parker. PILLS is a compact bathymetric lidar based on streak-tube sensor technology. It provides channel and bank topography and water surface elevation at 1 meter horizontal scales and 25 cm vertical accuracy. Surface currents are derived from the MWIR imagery by tracking surface features using a cross correlation algorithm. This approach enables the retrieval of currents along extended reaches at the forward speed of the aircraft with spatial resolutions down to 5 m with accuracy better than 10 cm/s. The fused airborne data captures current and depth variability on scales of meters over 10's of kilometers collected in just a few minutes. The airborne MWIR current retrievals are combined with the bathymetric lidar data to calculate river discharge which is then compared with real-time streamflow stations. The results highlight the potential for improving our understanding of complex river environments with simultaneous collections from multiple airborne sensors.

Design and Verification of Remote Sensing Image Data Center Storage Architecture Based on Hadoop

NASA Astrophysics Data System (ADS)

Tang, D.; Zhou, X.; Jing, Y.; Cong, W.; Li, C.

2018-04-01

The data center is a new concept of data processing and application proposed in recent years. It is a new method of processing technologies based on data, parallel computing, and compatibility with different hardware clusters. While optimizing the data storage management structure, it fully utilizes cluster resource computing nodes and improves the efficiency of data parallel application. This paper used mature Hadoop technology to build a large-scale distributed image management architecture for remote sensing imagery. Using MapReduce parallel processing technology, it called many computing nodes to process image storage blocks and pyramids in the background to improve the efficiency of image reading and application and sovled the need for concurrent multi-user high-speed access to remotely sensed data. It verified the rationality, reliability and superiority of the system design by testing the storage efficiency of different image data and multi-users and analyzing the distributed storage architecture to improve the application efficiency of remote sensing images through building an actual Hadoop service system.

Adaptive compressed sensing of remote-sensing imaging based on the sparsity prediction

NASA Astrophysics Data System (ADS)

Yang, Senlin; Li, Xilong; Chong, Xin

2017-10-01

The conventional compressive sensing works based on the non-adaptive linear projections, and the parameter of its measurement times is usually set empirically. As a result, the quality of image reconstruction is always affected. Firstly, the block-based compressed sensing (BCS) with conventional selection for compressive measurements was given. Then an estimation method for the sparsity of image was proposed based on the two dimensional discrete cosine transform (2D DCT). With an energy threshold given beforehand, the DCT coefficients were processed with both energy normalization and sorting in descending order, and the sparsity of the image can be achieved by the proportion of dominant coefficients. And finally, the simulation result shows that, the method can estimate the sparsity of image effectively, and provides an active basis for the selection of compressive observation times. The result also shows that, since the selection of observation times is based on the sparse degree estimated with the energy threshold provided, the proposed method can ensure the quality of image reconstruction.

Airborne imaging spectrometers developed in China

NASA Astrophysics Data System (ADS)

Wang, Jianyu; Xue, Yongqi

1998-08-01

Airborne imaging spectral technology, principle means in airborne remote sensing, has been developed rapidly both in the world and in China recently. This paper describes Modular Airborne Imaging Spectrometer (MAIS), Operational Modular Airborne Imaging Spectrometer (OMAIS) and Pushbroom Hyperspectral Imagery (PHI) that have been developed or are being developed in Airborne Remote Sensing Lab of Shanghai Institute of Technical Physics, CAS.

Designed Er(3+)-singly doped NaYF4 with double excitation bands for simultaneous deep macroscopic and microscopic upconverting bioimaging.

PubMed

Wen, Xuanyuan; Wang, Baoju; Wu, Ruitao; Li, Nana; He, Sailing; Zhan, Qiuqiang

2016-06-01

Simultaneous deep macroscopic imaging and microscopic imaging is in urgent demand, but is challenging to achieve experimentally due to the lack of proper fluorescent probes. Herein, we have designed and successfully synthesized simplex Er(3+)-doped upconversion nanoparticles (UCNPs) with double excitation bands for simultaneous deep macroscopic and microscopic imaging. The material structure and the excitation wavelength of Er(3+)-singly doped UCNPs were further optimized to enhance the upconversion emission efficiency. After optimization, we found that NaYF4:30%Er(3+)@NaYF4:2%Er(3+) could simultaneously achieve efficient two-photon excitation (2PE) macroscopic tissue imaging and three-photon excitation (3PE) deep microscopic when excited by 808 nm continuous wave (CW) and 1480 nm CW lasers, respectively. In vitro cell imaging and in vivo imaging have also been implemented to demonstrate the feasibility and potential of the proposed simplex Er(3+)-doped UCNPs as bioprobe.

Contrast-based sensorless adaptive optics for retinal imaging

PubMed Central

Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T.O.; He, Zheng; Metha, Andrew

2015-01-01

Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes. PMID:26417525

A real-time MTFC algorithm of space remote-sensing camera based on FPGA

NASA Astrophysics Data System (ADS)

Zhao, Liting; Huang, Gang; Lin, Zhe

2018-01-01

A real-time MTFC algorithm of space remote-sensing camera based on FPGA was designed. The algorithm can provide real-time image processing to enhance image clarity when the remote-sensing camera running on-orbit. The image restoration algorithm adopted modular design. The MTF measurement calculation module on-orbit had the function of calculating the edge extension function, line extension function, ESF difference operation, normalization MTF and MTFC parameters. The MTFC image filtering and noise suppression had the function of filtering algorithm and effectively suppressing the noise. The algorithm used System Generator to design the image processing algorithms to simplify the design structure of system and the process redesign. The image gray gradient dot sharpness edge contrast and median-high frequency were enhanced. The image SNR after recovery reduced less than 1 dB compared to the original image. The image restoration system can be widely used in various fields.

Visual Image Sensor Organ Replacement

NASA Technical Reports Server (NTRS)

Maluf, David A.

2014-01-01

This innovation is a system that augments human vision through a technique called "Sensing Super-position" using a Visual Instrument Sensory Organ Replacement (VISOR) device. The VISOR device translates visual and other sensors (i.e., thermal) into sounds to enable very difficult sensing tasks. Three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. Because the human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns, the translation of images into sounds reduces the risk of accidentally filtering out important clues. The VISOR device was developed to augment the current state-of-the-art head-mounted (helmet) display systems. It provides the ability to sense beyond the human visible light range, to increase human sensing resolution, to use wider angle visual perception, and to improve the ability to sense distances. It also allows compensation for movement by the human or changes in the scene being viewed.

Effect of Forest Canopy on Remote Sensing Soil Moisture at L-band

NASA Technical Reports Server (NTRS)

LeVine, D. M.; Lang, R. H.; Jackson, T. J.; Haken, M.

2005-01-01

Global maps of soil moisture are needed to improve understanding and prediction of the global water and energy cycles. Accuracy requirements imply the use of lower frequencies (L-band) to achieve adequate penetration into the soil and to minimize attenuation by the vegetation canopy and effects of surface roughness. Success has been demonstrated over agricultural areas, but canopies with high biomass (e.g. forests) still present a challenge. Examples from recent measurements over forests with the L-band radiometer, 2D-STAR, and its predecessor, ESTAR, will be presented to illustrate the problem. ESTAR and 2D-STAR are aircraft-based synthetic aperture radiometers developed to help resolve both the engineering and algorithm issues associated with future remote sensing of soil moisture. ESTAR, which does imaging across track, was developed to demonstrate the viability of aperture synthesis for remote sensing. The instrument has participated several soil moisture experiments (e.g. at the Little Washita Watershed in 1992 and the Southern Great Plains experiments in 1997 and 1999). In addition, measurements have been made at a forest site near Waverly, VA which contains conifer forests with a variety of biomass. These data have demonstrated the success of retrieving soil moisture at L-band over agricultural areas and the response of passive observations at L-band to biomass over forests. 2D-STAR is a second generation instrument that does aperture synthesis in two dimensions (along track and cross track) and is dual polarized. This instrument has the potential to provide measurements at L-band that simulate the measurements that will be made by the two L-band sensors currently being developed for future remote sensing of soil moisture from space: Hydros (conical scan and real aperture) and SMOS (multiple incidence angle and synthetic aperture). 2D-STAR participated in the SMEX-03 soil moisture experiment, providing images from the NASA P-3 aircraft. Preliminary results include images of the experiment site area near Huntsville, AL that included a mixture of forest and agriculture. Changes during a rain event further illustrate the issues presented by forests. Work is continuing to reduce the 2D-STAR data and to support the two future remote sensing missions. Among the goals is to process the 2D-STAR data to create multiple looks (at the same pixel) with different incidence angles. Data in this format can be used to test algorithms for retrieving soil moisture and biomass such as are planned for SMOS. Also, the data are being processed to provide images at constant incidence angles such as will be obtained by Hydros. Although Hydros will have only one incidence angle, it will also carry an L-band radar, The goal is to use the radar to improve spatial resolution, an issue for remote sensing from space at the long wavelengths. Simultaneous observations with active and passive sensors also offers interesting prospects for treating areas of high biomass (forests) and irregular terrain and may be the challenge for the future.

Optical and Electric Multifunctional CMOS Image Sensors for On-Chip Biosensing Applications

PubMed Central

Tokuda, Takashi; Noda, Toshihiko; Sasagawa, Kiyotaka; Ohta, Jun

2010-01-01

In this review, the concept, design, performance, and a functional demonstration of multifunctional complementary metal-oxide-semiconductor (CMOS) image sensors dedicated to on-chip biosensing applications are described. We developed a sensor architecture that allows flexible configuration of a sensing pixel array consisting of optical and electric sensing pixels, and designed multifunctional CMOS image sensors that can sense light intensity and electric potential or apply a voltage to an on-chip measurement target. We describe the sensors’ architecture on the basis of the type of electric measurement or imaging functionalities. PMID:28879978

Remote Distributed Vibration Sensing Through Opaque Media Using Permanent Magnets

DOE PAGES

Chen, Yi; Mazumdar, Anirban; Brooks, Carlton F.; ...

2018-04-05

Vibration sensing is critical for a variety of applications from structural fatigue monitoring to understanding the modes of airplane wings. In particular, remote sensing techniques are needed for measuring the vibrations of multiple points simultaneously, assessing vibrations inside opaque metal vessels, and sensing through smoke clouds and other optically challenging environments. Here, in this paper, we propose a method which measures high-frequency displacements remotely using changes in the magnetic field generated by permanent magnets. We leverage the unique nature of vibration tracking and use a calibrated local model technique developed specifically to improve the frequency-domain estimation accuracy. The results showmore » that two-dimensional local models surpass the dipole model in tracking high-frequency motions. A theoretical basis for understanding the effects of electronic noise and error due to correlated variables is generated in order to predict the performance of experiments prior to implementation. Simultaneous measurements of up to three independent vibrating components are shown. The relative accuracy of the magnet-based displacement tracking with respect to the video tracking ranges from 40 to 190 μm when the maximum displacements approach ±5 mm and when sensor-to-magnet distances vary from 25 to 36 mm. Finally, vibration sensing inside an opaque metal vessel and mode shape changes due to damage on an aluminum beam are also studied using the wireless permanent-magnet vibration sensing scheme.« less

Remote Distributed Vibration Sensing Through Opaque Media Using Permanent Magnets

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

Chen, Yi; Mazumdar, Anirban; Brooks, Carlton F.

Vibration sensing is critical for a variety of applications from structural fatigue monitoring to understanding the modes of airplane wings. In particular, remote sensing techniques are needed for measuring the vibrations of multiple points simultaneously, assessing vibrations inside opaque metal vessels, and sensing through smoke clouds and other optically challenging environments. Here, in this paper, we propose a method which measures high-frequency displacements remotely using changes in the magnetic field generated by permanent magnets. We leverage the unique nature of vibration tracking and use a calibrated local model technique developed specifically to improve the frequency-domain estimation accuracy. The results showmore » that two-dimensional local models surpass the dipole model in tracking high-frequency motions. A theoretical basis for understanding the effects of electronic noise and error due to correlated variables is generated in order to predict the performance of experiments prior to implementation. Simultaneous measurements of up to three independent vibrating components are shown. The relative accuracy of the magnet-based displacement tracking with respect to the video tracking ranges from 40 to 190 μm when the maximum displacements approach ±5 mm and when sensor-to-magnet distances vary from 25 to 36 mm. Finally, vibration sensing inside an opaque metal vessel and mode shape changes due to damage on an aluminum beam are also studied using the wireless permanent-magnet vibration sensing scheme.« less

Odyssey/White Rock

NASA Technical Reports Server (NTRS)

2002-01-01

These Mars Odyssey images show the 'White Rock' feature on Mars in both infrared (left) and visible (right) wavelengths. The images were acquired simultaneously on March 11, 2002. The box shows where the visible image is located in the infrared image. 'White Rock' is the unofficial name for this unusual landform that was first observed during the Mariner 9 mission in the early 1970's. The variations in brightness in the infrared image are due to differences in surface temperature, where dark is cool and bright is warm. The dramatic differences between the infrared and visible views of White Rock are the result of solar heating. The relatively bright surfaces observed at visible wavelengths reflect more solar energy than the darker surfaces, allowing them to stay cooler and thus they appear dark in the infrared image. The new thermal emission imaging system data will help to address the long standing question of whether the White Rock deposit was produced in an ancient crater lake or by dry processes of volcanic or wind deposition. The infrared image has a resolution of 100 meters (328 feet) per pixel and is 32 kilometers (20 miles) wide. The visible image has a resolution of 18 meters per pixel and is approximately 18 kilometers (11 miles) wide. The images are centered at 8.2 degrees south latitude and 24.9 degrees east longitude.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Multidirectional Image Sensing for Microscopy Based on a Rotatable Robot.

PubMed

Shen, Yajing; Wan, Wenfeng; Zhang, Lijun; Yong, Li; Lu, Haojian; Ding, Weili

2015-12-15

Image sensing at a small scale is essentially important in many fields, including microsample observation, defect inspection, material characterization and so on. However, nowadays, multi-directional micro object imaging is still very challenging due to the limited field of view (FOV) of microscopes. This paper reports a novel approach for multi-directional image sensing in microscopes by developing a rotatable robot. First, a robot with endless rotation ability is designed and integrated with the microscope. Then, the micro object is aligned to the rotation axis of the robot automatically based on the proposed forward-backward alignment strategy. After that, multi-directional images of the sample can be obtained by rotating the robot within one revolution under the microscope. To demonstrate the versatility of this approach, we view various types of micro samples from multiple directions in both optical microscopy and scanning electron microscopy, and panoramic images of the samples are processed as well. The proposed method paves a new way for the microscopy image sensing, and we believe it could have significant impact in many fields, especially for sample detection, manipulation and characterization at a small scale.

Hybrid fluorescence and electron cryo-microscopy for simultaneous electron and photon imaging.

PubMed

Iijima, Hirofumi; Fukuda, Yoshiyuki; Arai, Yoshihiro; Terakawa, Susumu; Yamamoto, Naoki; Nagayama, Kuniaki

2014-01-01

Integration of fluorescence light and transmission electron microscopy into the same device would represent an important advance in correlative microscopy, which traditionally involves two separate microscopes for imaging. To achieve such integration, the primary technical challenge that must be solved regards how to arrange two objective lenses used for light and electron microscopy in such a manner that they can properly focus on a single specimen. To address this issue, both lateral displacement of the specimen between two lenses and specimen rotation have been proposed. Such movement of the specimen allows sequential collection of two kinds of microscopic images of a single target, but prevents simultaneous imaging. This shortcoming has been made up by using a simple optical device, a reflection mirror. Here, we present an approach toward the versatile integration of fluorescence and electron microscopy for simultaneous imaging. The potential of simultaneous hybrid microscopy was demonstrated by fluorescence and electron sequential imaging of a fluorescent protein expressed in cells and cathodoluminescence imaging of fluorescent beads. Copyright © 2013 Elsevier Inc. All rights reserved.

Sensing Super-position: Visual Instrument Sensor Replacement

NASA Technical Reports Server (NTRS)

Maluf, David A.; Schipper, John F.

2006-01-01

The coming decade of fast, cheap and miniaturized electronics and sensory devices opens new pathways for the development of sophisticated equipment to overcome limitations of the human senses. This project addresses the technical feasibility of augmenting human vision through Sensing Super-position using a Visual Instrument Sensory Organ Replacement (VISOR). The current implementation of the VISOR device translates visual and other passive or active sensory instruments into sounds, which become relevant when the visual resolution is insufficient for very difficult and particular sensing tasks. A successful Sensing Super-position meets many human and pilot vehicle system requirements. The system can be further developed into cheap, portable, and low power taking into account the limited capabilities of the human user as well as the typical characteristics of his dynamic environment. The system operates in real time, giving the desired information for the particular augmented sensing tasks. The Sensing Super-position device increases the image resolution perception and is obtained via an auditory representation as well as the visual representation. Auditory mapping is performed to distribute an image in time. The three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. This paper details the approach of developing Sensing Super-position systems as a way to augment the human vision system by exploiting the capabilities of the human hearing system as an additional neural input. The human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns. The known capabilities of the human hearing system to learn and understand complicated auditory patterns provided the basic motivation for developing an image-to-sound mapping system.

Greedy algorithms for diffuse optical tomography reconstruction

NASA Astrophysics Data System (ADS)

Dileep, B. P. V.; Das, Tapan; Dutta, Pranab K.

2018-03-01

Diffuse optical tomography (DOT) is a noninvasive imaging modality that reconstructs the optical parameters of a highly scattering medium. However, the inverse problem of DOT is ill-posed and highly nonlinear due to the zig-zag propagation of photons that diffuses through the cross section of tissue. The conventional DOT imaging methods iteratively compute the solution of forward diffusion equation solver which makes the problem computationally expensive. Also, these methods fail when the geometry is complex. Recently, the theory of compressive sensing (CS) has received considerable attention because of its efficient use in biomedical imaging applications. The objective of this paper is to solve a given DOT inverse problem by using compressive sensing framework and various Greedy algorithms such as orthogonal matching pursuit (OMP), compressive sampling matching pursuit (CoSaMP), and stagewise orthogonal matching pursuit (StOMP), regularized orthogonal matching pursuit (ROMP) and simultaneous orthogonal matching pursuit (S-OMP) have been studied to reconstruct the change in the absorption parameter i.e, Δα from the boundary data. Also, the Greedy algorithms have been validated experimentally on a paraffin wax rectangular phantom through a well designed experimental set up. We also have studied the conventional DOT methods like least square method and truncated singular value decomposition (TSVD) for comparison. One of the main features of this work is the usage of less number of source-detector pairs, which can facilitate the use of DOT in routine applications of screening. The performance metrics such as mean square error (MSE), normalized mean square error (NMSE), structural similarity index (SSIM), and peak signal to noise ratio (PSNR) have been used to evaluate the performance of the algorithms mentioned in this paper. Extensive simulation results confirm that CS based DOT reconstruction outperforms the conventional DOT imaging methods in terms of computational efficiency. The main advantage of this study is that the forward diffusion equation solver need not be repeatedly solved.

Development of a generalized algorithm of satellite remote sensing using multi-wavelength and multi-pixel information (MWP method) for aerosol properties by satellite-borne imager

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Nakajima, T.; Morimoto, S.; Takenaka, H.

2014-12-01

We have developed a new satellite remote sensing algorithm to retrieve the aerosol optical characteristics using multi-wavelength and multi-pixel information of satellite imagers (MWP method). In this algorithm, the inversion method is a combination of maximum a posteriori (MAP) method (Rodgers, 2000) and the Phillips-Twomey method (Phillips, 1962; Twomey, 1963) as a smoothing constraint for the state vector. Furthermore, with the progress of computing technique, this method has being combined with the direct radiation transfer calculation numerically solved by each iteration step of the non-linear inverse problem, without using LUT (Look Up Table) with several constraints.Retrieved parameters in our algorithm are aerosol optical properties, such as aerosol optical thickness (AOT) of fine and coarse mode particles, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength. We simultaneously retrieve all the parameters that characterize pixels in each of horizontal sub-domains consisting the target area. Then we successively apply the retrieval method to all the sub-domains in the target area.We conducted numerical tests for the retrieval of aerosol properties and ground surface albedo for GOSAT/CAI imager data to test the algorithm for the land area. The result of the experiment showed that AOTs of fine mode and coarse mode, soot fraction and ground surface albedo are successfully retrieved within expected accuracy. We discuss the accuracy of the algorithm for various land surface types. Then, we applied this algorithm to GOSAT/CAI imager data, and we compared retrieved and surface-observed AOTs at the CAI pixel closest to an AERONET (Aerosol Robotic Network) or SKYNET site in each region. Comparison at several sites in urban area indicated that AOTs retrieved by our method are in agreement with surface-observed AOT within ±0.066.Our future work is to extend the algorithm for analysis of AGEOS-II/GLI and GCOM/C-SGLI data.

An Improved Otsu Threshold Segmentation Method for Underwater Simultaneous Localization and Mapping-Based Navigation

PubMed Central

Yuan, Xin; Martínez, José-Fernán; Eckert, Martina; López-Santidrián, Lourdes

2016-01-01

The main focus of this paper is on extracting features with SOund Navigation And Ranging (SONAR) sensing for further underwater landmark-based Simultaneous Localization and Mapping (SLAM). According to the characteristics of sonar images, in this paper, an improved Otsu threshold segmentation method (TSM) has been developed for feature detection. In combination with a contour detection algorithm, the foreground objects, although presenting different feature shapes, are separated much faster and more precisely than by other segmentation methods. Tests have been made with side-scan sonar (SSS) and forward-looking sonar (FLS) images in comparison with other four TSMs, namely the traditional Otsu method, the local TSM, the iterative TSM and the maximum entropy TSM. For all the sonar images presented in this work, the computational time of the improved Otsu TSM is much lower than that of the maximum entropy TSM, which achieves the highest segmentation precision among the four above mentioned TSMs. As a result of the segmentations, the centroids of the main extracted regions have been computed to represent point landmarks which can be used for navigation, e.g., with the help of an Augmented Extended Kalman Filter (AEKF)-based SLAM algorithm. The AEKF-SLAM approach is a recursive and iterative estimation-update process, which besides a prediction and an update stage (as in classical Extended Kalman Filter (EKF)), includes an augmentation stage. During navigation, the robot localizes the centroids of different segments of features in sonar images, which are detected by our improved Otsu TSM, as point landmarks. Using them with the AEKF achieves more accurate and robust estimations of the robot pose and the landmark positions, than with those detected by the maximum entropy TSM. Together with the landmarks identified by the proposed segmentation algorithm, the AEKF-SLAM has achieved reliable detection of cycles in the map and consistent map update on loop closure, which is shown in simulated experiments. PMID:27455279

A device for real-time live-cell microscopy during dynamic dual-modal mechanostimulation

NASA Astrophysics Data System (ADS)

Lorusso, D.; Nikolov, H. N.; Chmiel, T.; Beach, R. J.; Sims, S. M.; Dixon, S. J.; Holdsworth, D. W.

2017-03-01

Mechanotransduction - the process by which cells sense and respond to mechanical stimuli - is essential for several physiological processes including skeletal homeostasis. Mammalian cells are thought to be sensitive to different modes of mechanical stimuli, including vibration and fluid shear. To better understand the mechanisms underlying the early stages of mechanotransduction, we describe the development of devices for mechanostimulation (by vibration and fluid shear) of live cells that can be integrated with real-time optical microscopy. The integrated system can deliver up to 3 Pa of fluid shear simultaneous with high-frequency sinusoidal vibrations up to 1 g. Stimuli can be applied simultaneously or independently to cells during real-time microscopic imaging. A custom microfluidic chamber was prepared from polydimethylsiloxane on a glass-bottom cell culture dish. Fluid flow was applied with a syringe pump to induce shear stress. This device is compatible with a custom-designed motion control vibration system. A voice coil actuates the system that is suspended on linear air bushings. Accelerations produced by the system were monitored with an on-board accelerometer. Displacement was validated optically using particle tracking digital high-speed imaging (1200 frames per second). During operation at nominally 45 Hz and 0.3 g, displacements were observed to be within 3.56% of the expected value. MC3T3-E1 osteoblast like cells were seeded into the microfluidic device and loaded with the calcium sensitive fluorescent probe fura-2, then mounted onto the dual-modal mechanostimulation platform. Cells were then imaged and monitored for fluorescence emission. In summary, we have developed a system to deliver physiologically relevant vibrations and fluid shear to live cells during real-time imaging and photometry. Monitoring the behavior of live cells loaded with appropriate fluorescent probes will enable characterization of the signals activated during the initial stages of mechanotransduction.

An Improved Otsu Threshold Segmentation Method for Underwater Simultaneous Localization and Mapping-Based Navigation.

PubMed

Yuan, Xin; Martínez, José-Fernán; Eckert, Martina; López-Santidrián, Lourdes

2016-07-22

The main focus of this paper is on extracting features with SOund Navigation And Ranging (SONAR) sensing for further underwater landmark-based Simultaneous Localization and Mapping (SLAM). According to the characteristics of sonar images, in this paper, an improved Otsu threshold segmentation method (TSM) has been developed for feature detection. In combination with a contour detection algorithm, the foreground objects, although presenting different feature shapes, are separated much faster and more precisely than by other segmentation methods. Tests have been made with side-scan sonar (SSS) and forward-looking sonar (FLS) images in comparison with other four TSMs, namely the traditional Otsu method, the local TSM, the iterative TSM and the maximum entropy TSM. For all the sonar images presented in this work, the computational time of the improved Otsu TSM is much lower than that of the maximum entropy TSM, which achieves the highest segmentation precision among the four above mentioned TSMs. As a result of the segmentations, the centroids of the main extracted regions have been computed to represent point landmarks which can be used for navigation, e.g., with the help of an Augmented Extended Kalman Filter (AEKF)-based SLAM algorithm. The AEKF-SLAM approach is a recursive and iterative estimation-update process, which besides a prediction and an update stage (as in classical Extended Kalman Filter (EKF)), includes an augmentation stage. During navigation, the robot localizes the centroids of different segments of features in sonar images, which are detected by our improved Otsu TSM, as point landmarks. Using them with the AEKF achieves more accurate and robust estimations of the robot pose and the landmark positions, than with those detected by the maximum entropy TSM. Together with the landmarks identified by the proposed segmentation algorithm, the AEKF-SLAM has achieved reliable detection of cycles in the map and consistent map update on loop closure, which is shown in simulated experiments.

Simultaneous image reproduction on CRT screen: Moves ultrasonic sectional view and electrocardiogram curves

NASA Technical Reports Server (NTRS)

1978-01-01

A method for simultaneous reproduction of images, requiring different amounts of time to reproduce, on a cathode ray tube (CRT) screen is disclosed. Ultrasonic sectional views and electrocardiogram curves are simultaneously reproduced on the CRT screen by producing the images on different areas of a screen with two phosphors having different persistence times and luminous colors, within the times required for the appearance of the images. In front of the area on which is produced the image requiring the shorter time is a color filter which is permeable to the color of the phosphor with the shorter persistence time by which absorbs the color of the other phosphor.

Stage Cylindrical Immersive Display

NASA Technical Reports Server (NTRS)

Abramyan, Lucy; Norris, Jeffrey S.; Powell, Mark W.; Mittman, David S.; Shams, Khawaja S.

2011-01-01

Panoramic images with a wide field of view intend to provide a better understanding of an environment by placing objects of the environment on one seamless image. However, understanding the sizes and relative positions of the objects in a panorama is not intuitive and prone to errors because the field of view is unnatural to human perception. Scientists are often faced with the difficult task of interpreting the sizes and relative positions of objects in an environment when viewing an image of the environment on computer monitors or prints. A panorama can display an object that appears to be to the right of the viewer when it is, in fact, behind the viewer. This misinterpretation can be very costly, especially when the environment is remote and/or only accessible by unmanned vehicles. A 270 cylindrical display has been developed that surrounds the viewer with carefully calibrated panoramic imagery that correctly engages their natural kinesthetic senses and provides a more accurate awareness of the environment. The cylindrical immersive display offers a more natural window to the environment than a standard cubic CAVE (Cave Automatic Virtual Environment), and the geometry allows multiple collocated users to simultaneously view data and share important decision-making tasks. A CAVE is an immersive virtual reality environment that allows one or more users to absorb themselves in a virtual environment. A common CAVE setup is a room-sized cube where the cube sides act as projection planes. By nature, all cubic CAVEs face a problem with edge matching at edges and corners of the display. Modern immersive displays have found ways to minimize seams by creating very tight edges, and rely on the user to ignore the seam. One significant deficiency of flat-walled CAVEs is that the sense of orientation and perspective within the scene is broken across adjacent walls. On any single wall, parallel lines properly converge at their vanishing point as they should, and the sense of perspective within the scene contained on only one wall has integrity. Unfortunately, parallel lines that lie on adjacent walls do not necessarily remain parallel. This results in inaccuracies in the scene that can distract the viewer and subtract from the immersive experience of the CAVE.

Accurate reconstruction of hyperspectral images from compressive sensing measurements

NASA Astrophysics Data System (ADS)

Greer, John B.; Flake, J. C.

2013-05-01

The emerging field of Compressive Sensing (CS) provides a new way to capture data by shifting the heaviest burden of data collection from the sensor to the computer on the user-end. This new means of sensing requires fewer measurements for a given amount of information than traditional sensors. We investigate the efficacy of CS for capturing HyperSpectral Imagery (HSI) remotely. We also introduce a new family of algorithms for constructing HSI from CS measurements with Split Bregman Iteration [Goldstein and Osher,2009]. These algorithms combine spatial Total Variation (TV) with smoothing in the spectral dimension. We examine models for three different CS sensors: the Coded Aperture Snapshot Spectral Imager-Single Disperser (CASSI-SD) [Wagadarikar et al.,2008] and Dual Disperser (CASSI-DD) [Gehm et al.,2007] cameras, and a hypothetical random sensing model closer to CS theory, but not necessarily implementable with existing technology. We simulate the capture of remotely sensed images by applying the sensor forward models to well-known HSI scenes - an AVIRIS image of Cuprite, Nevada and the HYMAP Urban image. To measure accuracy of the CS models, we compare the scenes constructed with our new algorithm to the original AVIRIS and HYMAP cubes. The results demonstrate the possibility of accurately sensing HSI remotely with significantly fewer measurements than standard hyperspectral cameras.

QR-decomposition based SENSE reconstruction using parallel architecture.

PubMed

Ullah, Irfan; Nisar, Habab; Raza, Haseeb; Qasim, Malik; Inam, Omair; Omer, Hammad

2018-04-01

Magnetic Resonance Imaging (MRI) is a powerful medical imaging technique that provides essential clinical information about the human body. One major limitation of MRI is its long scan time. Implementation of advance MRI algorithms on a parallel architecture (to exploit inherent parallelism) has a great potential to reduce the scan time. Sensitivity Encoding (SENSE) is a Parallel Magnetic Resonance Imaging (pMRI) algorithm that utilizes receiver coil sensitivities to reconstruct MR images from the acquired under-sampled k-space data. At the heart of SENSE lies inversion of a rectangular encoding matrix. This work presents a novel implementation of GPU based SENSE algorithm, which employs QR decomposition for the inversion of the rectangular encoding matrix. For a fair comparison, the performance of the proposed GPU based SENSE reconstruction is evaluated against single and multicore CPU using openMP. Several experiments against various acceleration factors (AFs) are performed using multichannel (8, 12 and 30) phantom and in-vivo human head and cardiac datasets. Experimental results show that GPU significantly reduces the computation time of SENSE reconstruction as compared to multi-core CPU (approximately 12x speedup) and single-core CPU (approximately 53x speedup) without any degradation in the quality of the reconstructed images. Copyright © 2018 Elsevier Ltd. All rights reserved.

Vision 20/20: Simultaneous CT-MRI — Next chapter of multimodality imaging

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

Wang, Ge, E-mail: wangg6@rpi.edu; Xi, Yan; Gjesteby, Lars

Multimodality imaging systems such as positron emission tomography-computed tomography (PET-CT) and MRI-PET are widely available, but a simultaneous CT-MRI instrument has not been developed. Synergies between independent modalities, e.g., CT, MRI, and PET/SPECT can be realized with image registration, but such postprocessing suffers from registration errors that can be avoided with synchronized data acquisition. The clinical potential of simultaneous CT-MRI is significant, especially in cardiovascular and oncologic applications where studies of the vulnerable plaque, response to cancer therapy, and kinetic and dynamic mechanisms of targeted agents are limited by current imaging technologies. The rationale, feasibility, and realization of simultaneous CT-MRImore » are described in this perspective paper. The enabling technologies include interior tomography, unique gantry designs, open magnet and RF sequences, and source and detector adaptation. Based on the experience with PET-CT, PET-MRI, and MRI-LINAC instrumentation where hardware innovation and performance optimization were instrumental to construct commercial systems, the authors provide top-level concepts for simultaneous CT-MRI to meet clinical requirements and new challenges. Simultaneous CT-MRI fills a major gap of modality coupling and represents a key step toward the so-called “omnitomography” defined as the integration of all relevant imaging modalities for systems biology and precision medicine.« less

Shearlet Features for Registration of Remotely Sensed Multitemporal Images

NASA Technical Reports Server (NTRS)

Murphy, James M.; Le Moigne, Jacqueline

2015-01-01

We investigate the role of anisotropic feature extraction methods for automatic image registration of remotely sensed multitemporal images. Building on the classical use of wavelets in image registration, we develop an algorithm based on shearlets, a mathematical generalization of wavelets that offers increased directional sensitivity. Initial experimental results on LANDSAT images are presented, which indicate superior performance of the shearlet algorithm when compared to classical wavelet algorithms.

System design and implementation of digital-image processing using computational grids

NASA Astrophysics Data System (ADS)

Shen, Zhanfeng; Luo, Jiancheng; Zhou, Chenghu; Huang, Guangyu; Ma, Weifeng; Ming, Dongping

2005-06-01

As a special type of digital image, remotely sensed images are playing increasingly important roles in our daily lives. Because of the enormous amounts of data involved, and the difficulties of data processing and transfer, an important issue for current computer and geo-science experts is developing internet technology to implement rapid remotely sensed image processing. Computational grids are able to solve this problem effectively. These networks of computer workstations enable the sharing of data and resources, and are used by computer experts to solve imbalances of network resources and lopsided usage. In China, computational grids combined with spatial-information-processing technology have formed a new technology: namely, spatial-information grids. In the field of remotely sensed images, spatial-information grids work more effectively for network computing, data processing, resource sharing, task cooperation and so on. This paper focuses mainly on the application of computational grids to digital-image processing. Firstly, we describe the architecture of digital-image processing on the basis of computational grids, its implementation is then discussed in detail with respect to the technology of middleware. The whole network-based intelligent image-processing system is evaluated on the basis of the experimental analysis of remotely sensed image-processing tasks; the results confirm the feasibility of the application of computational grids to digital-image processing.

Quality assessment of remote sensing image fusion using feature-based fourth-order correlation coefficient

NASA Astrophysics Data System (ADS)

Ma, Dan; Liu, Jun; Chen, Kai; Li, Huali; Liu, Ping; Chen, Huijuan; Qian, Jing

2016-04-01

In remote sensing fusion, the spatial details of a panchromatic (PAN) image and the spectrum information of multispectral (MS) images will be transferred into fused images according to the characteristics of the human visual system. Thus, a remote sensing image fusion quality assessment called feature-based fourth-order correlation coefficient (FFOCC) is proposed. FFOCC is based on the feature-based coefficient concept. Spatial features related to spatial details of the PAN image and spectral features related to the spectrum information of MS images are first extracted from the fused image. Then, the fourth-order correlation coefficient between the spatial and spectral features is calculated and treated as the assessment result. FFOCC was then compared with existing widely used indices, such as Erreur Relative Globale Adimensionnelle de Synthese, and quality assessed with no reference. Results of the fusion and distortion experiments indicate that the FFOCC is consistent with subjective evaluation. FFOCC significantly outperforms the other indices in evaluating fusion images that are produced by different fusion methods and that are distorted in spatial and spectral features by blurring, adding noise, and changing intensity. All the findings indicate that the proposed method is an objective and effective quality assessment for remote sensing image fusion.

The new frontiers of multimodality and multi-isotope imaging

NASA Astrophysics Data System (ADS)

Behnam Azad, Babak; Nimmagadda, Sridhar

2014-06-01

Technological advances in imaging systems and the development of target specific imaging tracers has been rapidly growing over the past two decades. Recent progress in "all-in-one" imaging systems that allow for automated image coregistration has significantly added to the growth of this field. These developments include ultra high resolution PET and SPECT scanners that can be integrated with CT or MR resulting in PET/CT, SPECT/CT, SPECT/PET and PET/MRI scanners for simultaneous high resolution high sensitivity anatomical and functional imaging. These technological developments have also resulted in drastic enhancements in image quality and acquisition time while eliminating cross compatibility issues between modalities. Furthermore, the most cutting edge technology, though mostly preclinical, also allows for simultaneous multimodality multi-isotope image acquisition and image reconstruction based on radioisotope decay characteristics. These scientific advances, in conjunction with the explosion in the development of highly specific multimodality molecular imaging agents, may aid in realizing simultaneous imaging of multiple biological processes and pave the way towards more efficient diagnosis and improved patient care.

Hypothesis on human eye perceiving optical spectrum rather than an image

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Szu, Harold

2015-05-01

It is a common knowledge that we see the world because our eyes can perceive an optical image. A digital camera seems a good example of simulating the eye imaging system. However, the signal sensing and imaging on human retina is very complicated. There are at least five layers (of neurons) along the signal pathway: photoreceptors (cones and rods), bipolar, horizontal, amacrine and ganglion cells. To sense an optical image, it seems that photoreceptors (as sensors) plus ganglion cells (converting to electrical signals for transmission) are good enough. Image sensing does not require ununiformed distribution of photoreceptors like fovea. There are some challenging questions, for example, why don't we feel the "blind spots" (never fibers exiting the eyes)? Similar situation happens to glaucoma patients who do not feel their vision loss until 50% or more nerves died. Now our hypothesis is that human retina initially senses optical (i.e., Fourier) spectrum rather than optical image. Due to the symmetric property of Fourier spectrum the signal loss from a blind spot or the dead nerves (for glaucoma patients) can be recovered. Eye logarithmic response to input light intensity much likes displaying Fourier magnitude. The optics and structures of human eyes satisfy the needs of optical Fourier spectrum sampling. It is unsure that where and how inverse Fourier transform is performed in human vision system to obtain an optical image. Phase retrieval technique in compressive sensing domain enables image reconstruction even without phase inputs. The spectrum-based imaging system can potentially tolerate up to 50% of bad sensors (pixels), adapt to large dynamic range (with logarithmic response), etc.

Criteria for the optimal selection of remote sensing optical images to map event landslides

NASA Astrophysics Data System (ADS)

Fiorucci, Federica; Giordan, Daniele; Santangelo, Michele; Dutto, Furio; Rossi, Mauro; Guzzetti, Fausto

2018-01-01

Landslides leave discernible signs on the land surface, most of which can be captured in remote sensing images. Trained geomorphologists analyse remote sensing images and map landslides through heuristic interpretation of photographic and morphological characteristics. Despite a wide use of remote sensing images for landslide mapping, no attempt to evaluate how the image characteristics influence landslide identification and mapping exists. This paper presents an experiment to determine the effects of optical image characteristics, such as spatial resolution, spectral content and image type (monoscopic or stereoscopic), on landslide mapping. We considered eight maps of the same landslide in central Italy: (i) six maps obtained through expert heuristic visual interpretation of remote sensing images, (ii) one map through a reconnaissance field survey, and (iii) one map obtained through a real-time kinematic (RTK) differential global positioning system (dGPS) survey, which served as a benchmark. The eight maps were compared pairwise and to a benchmark. The mismatch between each map pair was quantified by the error index, E. Results show that the map closest to the benchmark delineation of the landslide was obtained using the higher resolution image, where the landslide signature was primarily photographical (in the landslide source and transport area). Conversely, where the landslide signature was mainly morphological (in the landslide deposit) the best mapping result was obtained using the stereoscopic images. Albeit conducted on a single landslide, the experiment results are general, and provide useful information to decide on the optimal imagery for the production of event, seasonal and multi-temporal landslide inventory maps.

Reducing acquisition time in clinical MRI by data undersampling and compressed sensing reconstruction

NASA Astrophysics Data System (ADS)

Hollingsworth, Kieren Grant

2015-11-01

MRI is often the most sensitive or appropriate technique for important measurements in clinical diagnosis and research, but lengthy acquisition times limit its use due to cost and considerations of patient comfort and compliance. Once an image field of view and resolution is chosen, the minimum scan acquisition time is normally fixed by the amount of raw data that must be acquired to meet the Nyquist criteria. Recently, there has been research interest in using the theory of compressed sensing (CS) in MR imaging to reduce scan acquisition times. The theory argues that if our target MR image is sparse, having signal information in only a small proportion of pixels (like an angiogram), or if the image can be mathematically transformed to be sparse then it is possible to use that sparsity to recover a high definition image from substantially less acquired data. This review starts by considering methods of k-space undersampling which have already been incorporated into routine clinical imaging (partial Fourier imaging and parallel imaging), and then explains the basis of using compressed sensing in MRI. The practical considerations of applying CS to MRI acquisitions are discussed, such as designing k-space undersampling schemes, optimizing adjustable parameters in reconstructions and exploiting the power of combined compressed sensing and parallel imaging (CS-PI). A selection of clinical applications that have used CS and CS-PI prospectively are considered. The review concludes by signposting other imaging acceleration techniques under present development before concluding with a consideration of the potential impact and obstacles to bringing compressed sensing into routine use in clinical MRI.

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1985-01-01

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

Remote Sensing of Landscapes with Spectral Images

NASA Astrophysics Data System (ADS)

Adams, John B.; Gillespie, Alan R.

2006-05-01

Remote Sensing of Landscapes with Spectral Images describes how to process and interpret spectral images using physical models to bridge the gap between the engineering and theoretical sides of remote-sensing and the world that we encounter when we venture outdoors. The emphasis is on the practical use of images rather than on theory and mathematical derivations. Examples are drawn from a variety of landscapes and interpretations are tested against the reality seen on the ground. The reader is led through analysis of real images (using figures and explanations); the examples are chosen to illustrate important aspects of the analytic framework. This textbook will form a valuable reference for graduate students and professionals in a variety of disciplines including ecology, forestry, geology, geography, urban planning, archeology and civil engineering. It is supplemented by a web-site hosting digital color versions of figures in the book as well as ancillary images (www.cambridge.org/9780521662214). Presents a coherent view of practical remote sensing, leading from imaging and field work to the generation of useful thematic maps Explains how to apply physical models to help interpret spectral images Supplemented by a website hosting digital colour versions of figures in the book, as well as additional colour figures

Hyperspectral remote sensing image retrieval system using spectral and texture features.

PubMed

Zhang, Jing; Geng, Wenhao; Liang, Xi; Li, Jiafeng; Zhuo, Li; Zhou, Qianlan

2017-06-01

Although many content-based image retrieval systems have been developed, few studies have focused on hyperspectral remote sensing images. In this paper, a hyperspectral remote sensing image retrieval system based on spectral and texture features is proposed. The main contributions are fourfold: (1) considering the "mixed pixel" in the hyperspectral image, endmembers as spectral features are extracted by an improved automatic pixel purity index algorithm, then the texture features are extracted with the gray level co-occurrence matrix; (2) similarity measurement is designed for the hyperspectral remote sensing image retrieval system, in which the similarity of spectral features is measured with the spectral information divergence and spectral angle match mixed measurement and in which the similarity of textural features is measured with Euclidean distance; (3) considering the limited ability of the human visual system, the retrieval results are returned after synthesizing true color images based on the hyperspectral image characteristics; (4) the retrieval results are optimized by adjusting the feature weights of similarity measurements according to the user's relevance feedback. The experimental results on NASA data sets can show that our system can achieve comparable superior retrieval performance to existing hyperspectral analysis schemes.

Linear- and Repetitive Feature Detection Within Remotely Sensed Imagery

DTIC Science & Technology

2017-04-01

applicable to Python or other pro- gramming languages with image- processing capabilities. 4.1 Classification machine learning The first methodology uses...remotely sensed images that are in panchromatic or true-color formats. Image- processing techniques, in- cluding Hough transforms, machine learning, and...data fusion .................................................................................................... 44 6.3 Context-based processing

Distributed Compressive Sensing vs. Dynamic Compressive Sensing: Improving the Compressive Line Sensing Imaging System through Their Integration

DTIC Science & Technology

2015-01-01

streak tube imaging Lidar [15]. Nevertheless, instead of one- dimensional (1D) fan beam, a laser source modulates the digital micromirror device DMD and...Trans. Inform. Theory, vol. 52, pp. 1289-1306, 2006. [10] D. Dudley, W. Duncan and J. Slaughter, "Emerging Digital Micromirror Device (DMD) Applications

Remote sensing fire and fuels in southern California

Treesearch

Philip Riggan; Lynn Wolden; Bob Tissell; David Weise; J. Coen

2011-01-01

Airborne remote sensing at infrared wavelengths has the potential to quantify large-fire properties related to energy release or intensity, residence time, fuel-consumption rate, rate of spread, and soil heating. Remote sensing at a high temporal rate can track fire-line outbreaks and acceleration and spotting ahead of a fire front. Yet infrared imagers and imaging...

Sensing textile seam-line for wearable multimodal physiological monitoring.

PubMed

McKnight, M; Agcayazi, T; Kausche, H; Ghosh, T; Bozkurt, A

2016-08-01

This paper investigates a novel multimodal sensing method by forming seam-lines of conductive textile fibers into commercially available fabrics. The proposed ultra-low cost micro-electro-mechanical sensor would provide, wearable, flexible, textile based biopotential signal recording, wetness detection and tactile sensing simultaneously. Three types of fibers are evaluated for their array-based sensing capability, including a 3D printed conductive fiber, a multiwall carbon nanotube based fiber, and a commercially available stainless steel conductive thread. The sensors were shown to have a correlation between capacitance and pressure; impedance and wetness; and recorded potential and ECG waveforms.

Number Sense Mediated by Mathematics Self-Concept in Impacting Middle School Mathematics Achievement

ERIC Educational Resources Information Center

Geronime, Lara K.

2012-01-01

The purpose of the current study was to extend the research on number sense to the middle school level and to simultaneously consider socioemotional elements related to the construct at this developmental stage. Its genesis was initially rooted in an ongoing and dramatic emphasis by U.S. policymakers, researchers, and educators on improving…

A simultaneous beta and coincidence-gamma imaging system for plant leaves

NASA Astrophysics Data System (ADS)

Ranjbar, Homayoon; Wen, Jie; Mathews, Aswin J.; Komarov, Sergey; Wang, Qiang; Li, Ke; O'Sullivan, Joseph A.; Tai, Yuan-Chuan

2016-05-01

Positron emitting isotopes, such as 11C, 13N, and 18F, can be used to label molecules. The tracers, such as 11CO2, are delivered to plants to study their biological processes, particularly metabolism and photosynthesis, which may contribute to the development of plants that have a higher yield of crops and biomass. Measurements and resulting images from PET scanners are not quantitative in young plant structures or in plant leaves due to poor positron annihilation in thin objects. To address this problem we have designed, assembled, modeled, and tested a nuclear imaging system (simultaneous beta-gamma imager). The imager can simultaneously detect positrons ({β+} ) and coincidence-gamma rays (γ). The imaging system employs two planar detectors; one is a regular gamma detector which has a LYSO crystal array, and the other is a phoswich detector which has an additional BC-404 plastic scintillator for beta detection. A forward model for positrons is proposed along with a joint image reconstruction formulation to utilize the beta and coincidence-gamma measurements for estimating radioactivity distribution in plant leaves. The joint reconstruction algorithm first reconstructs beta and gamma images independently to estimate the thickness component of the beta forward model and afterward jointly estimates the radioactivity distribution in the object. We have validated the physics model and reconstruction framework through a phantom imaging study and imaging a tomato leaf that has absorbed 11CO2. The results demonstrate that the simultaneously acquired beta and coincidence-gamma data, combined with our proposed joint reconstruction algorithm, improved the quantitative accuracy of estimating radioactivity distribution in thin objects such as leaves. We used the structural similarity (SSIM) index for comparing the leaf images from the simultaneous beta-gamma imager with the ground truth image. The jointly reconstructed images yield SSIM indices of 0.69 and 0.63, whereas the separately reconstructed beta alone and gamma alone images had indices of 0.33 and 0.52, respectively.

A simultaneous beta and coincidence-gamma imaging system for plant leaves.

PubMed

Ranjbar, Homayoon; Wen, Jie; Mathews, Aswin J; Komarov, Sergey; Wang, Qiang; Li, Ke; O'Sullivan, Joseph A; Tai, Yuan-Chuan

2016-05-07

Positron emitting isotopes, such as (11)C, (13)N, and (18)F, can be used to label molecules. The tracers, such as (11)CO2, are delivered to plants to study their biological processes, particularly metabolism and photosynthesis, which may contribute to the development of plants that have a higher yield of crops and biomass. Measurements and resulting images from PET scanners are not quantitative in young plant structures or in plant leaves due to poor positron annihilation in thin objects. To address this problem we have designed, assembled, modeled, and tested a nuclear imaging system (simultaneous beta-gamma imager). The imager can simultaneously detect positrons ([Formula: see text]) and coincidence-gamma rays (γ). The imaging system employs two planar detectors; one is a regular gamma detector which has a LYSO crystal array, and the other is a phoswich detector which has an additional BC-404 plastic scintillator for beta detection. A forward model for positrons is proposed along with a joint image reconstruction formulation to utilize the beta and coincidence-gamma measurements for estimating radioactivity distribution in plant leaves. The joint reconstruction algorithm first reconstructs beta and gamma images independently to estimate the thickness component of the beta forward model and afterward jointly estimates the radioactivity distribution in the object. We have validated the physics model and reconstruction framework through a phantom imaging study and imaging a tomato leaf that has absorbed (11)CO2. The results demonstrate that the simultaneously acquired beta and coincidence-gamma data, combined with our proposed joint reconstruction algorithm, improved the quantitative accuracy of estimating radioactivity distribution in thin objects such as leaves. We used the structural similarity (SSIM) index for comparing the leaf images from the simultaneous beta-gamma imager with the ground truth image. The jointly reconstructed images yield SSIM indices of 0.69 and 0.63, whereas the separately reconstructed beta alone and gamma alone images had indices of 0.33 and 0.52, respectively.

Self-Referenced Smartphone-Based Nanoplasmonic Imaging Platform for Colorimetric Biochemical Sensing.

PubMed

Wang, Xinhao; Chang, Te-Wei; Lin, Guohong; Gartia, Manas Ranjan; Liu, Gang Logan

2017-01-03

Colorimetric sensors usually suffer due to errors from variation in light source intensity, the type of light source, the Bayer filter algorithm, and the sensitivity of the camera to incoming light. Here, we demonstrate a self-referenced portable smartphone-based plasmonic sensing platform integrated with an internal reference sample along with an image processing method to perform colorimetric sensing. Two sensing principles based on unique nanoplasmonics enabled phenomena from a nanostructured plasmonic sensor, named as nanoLCA (nano Lycurgus cup array), were demonstrated here for colorimetric biochemical sensing: liquid refractive index sensing and optical absorbance enhancement sensing. Refractive indices of colorless liquids were measured by simple smartphone imaging and color analysis. Optical absorbance enhancement in the colorimetric biochemical assay was achieved by matching the plasmon resonance wavelength with the chromophore's absorbance peak wavelength. Such a sensing mechanism improved the limit of detection (LoD) by 100 times in a microplate reader format. Compared with a traditional colorimetric assay such as urine testing strips, a smartphone plasmon enhanced colorimetric sensing system provided 30 times improvement in the LoD. The platform was applied for simulated urine testing to precisely identify the samples with higher protein concentration, which showed potential point-of-care and early detection of kidney disease with the smartphone plasmonic resonance sensing system.

Compressive Sensing Based Bio-Inspired Shape Feature Detection CMOS Imager

NASA Technical Reports Server (NTRS)

Duong, Tuan A. (Inventor)

2015-01-01

A CMOS imager integrated circuit using compressive sensing and bio-inspired detection is presented which integrates novel functions and algorithms within a novel hardware architecture enabling efficient on-chip implementation.

Machine processing of remotely sensed data - quantifying global process: Models, sensor systems, and analytical methods; Proceedings of the Eleventh International Symposium, Purdue University, West Lafayette, IN, June 25-27, 1985

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

Mengel, S.K.; Morrison, D.B.

1985-01-01

Consideration is given to global biogeochemical issues, image processing, remote sensing of tropical environments, global processes, geology, landcover hydrology, and ecosystems modeling. Topics discussed include multisensor remote sensing strategies, geographic information systems, radars, and agricultural remote sensing. Papers are presented on fast feature extraction; a computational approach for adjusting TM imagery terrain distortions; the segmentation of a textured image by a maximum likelihood classifier; analysis of MSS Landsat data; sun angle and background effects on spectral response of simulated forest canopies; an integrated approach for vegetation/landcover mapping with digital Landsat images; geological and geomorphological studies using an image processing technique;more » and wavelength intensity indices in relation to tree conditions and leaf-nutrient content.« less

The ultrasound brain helmet: feasibility study of multiple simultaneous 3D scans of cerebral vasculature.

PubMed

Smith, Stephen W; Ivancevich, Nikolas M; Lindsey, Brooks D; Whitman, John; Light, Edward; Fronheiser, Matthew; Nicoletto, Heather A; Laskowitz, Daniel T

2009-02-01

We describe early stage experiments to test the feasibility of an ultrasound brain helmet to produce multiple simultaneous real-time three-dimensional (3D) scans of the cerebral vasculature from temporal and suboccipital acoustic windows of the skull. The transducer hardware and software of the Volumetrics Medical Imaging (Durham, NC, USA) real-time 3D scanner were modified to support dual 2.5 MHz matrix arrays of 256 transmit elements and 128 receive elements which produce two simultaneous 64 degrees pyramidal scans. The real-time display format consists of two coronal B-mode images merged into a 128 degrees sector, two simultaneous parasagittal images merged into a 128 degrees x 64 degrees C-mode plane and a simultaneous 64 degrees axial image. Real-time 3D color Doppler scans from a skull phantom with latex blood vessel were obtained after contrast agent injection as a proof of concept. The long-term goal is to produce real-time 3D ultrasound images of the cerebral vasculature from a portable unit capable of internet transmission thus enabling interactive 3D imaging, remote diagnosis and earlier therapeutic intervention. We are motivated by the urgency for rapid diagnosis of stroke due to the short time window of effective therapeutic intervention.

Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application.

PubMed

Chen, Pengyun; Zhang, Yichen; Jia, Zhenhong; Yang, Jie; Kasabov, Nikola

2017-06-06

Traditional image change detection based on a non-subsampled contourlet transform always ignores the neighborhood information's relationship to the non-subsampled contourlet coefficients, and the detection results are susceptible to noise interference. To address these disadvantages, we propose a denoising method based on the non-subsampled contourlet transform domain that uses the Hidden Markov Tree model (NSCT-HMT) for change detection of remote sensing images. First, the ENVI software is used to calibrate the original remote sensing images. After that, the mean-ratio operation is adopted to obtain the difference image that will be denoised by the NSCT-HMT model. Then, using the Fuzzy Local Information C-means (FLICM) algorithm, the difference image is divided into the change area and unchanged area. The proposed algorithm is applied to a real remote sensing data set. The application results show that the proposed algorithm can effectively suppress clutter noise, and retain more detailed information from the original images. The proposed algorithm has higher detection accuracy than the Markov Random Field-Fuzzy C-means (MRF-FCM), the non-subsampled contourlet transform-Fuzzy C-means clustering (NSCT-FCM), the pointwise approach and graph theory (PA-GT), and the Principal Component Analysis-Nonlocal Means (PCA-NLM) denosing algorithm. Finally, the five algorithms are used to detect the southern boundary of the Gurbantunggut Desert in Xinjiang Uygur Autonomous Region of China, and the results show that the proposed algorithm has the best effect on real remote sensing image change detection.

Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application

PubMed Central

Chen, Pengyun; Zhang, Yichen; Jia, Zhenhong; Yang, Jie; Kasabov, Nikola

2017-01-01

Traditional image change detection based on a non-subsampled contourlet transform always ignores the neighborhood information’s relationship to the non-subsampled contourlet coefficients, and the detection results are susceptible to noise interference. To address these disadvantages, we propose a denoising method based on the non-subsampled contourlet transform domain that uses the Hidden Markov Tree model (NSCT-HMT) for change detection of remote sensing images. First, the ENVI software is used to calibrate the original remote sensing images. After that, the mean-ratio operation is adopted to obtain the difference image that will be denoised by the NSCT-HMT model. Then, using the Fuzzy Local Information C-means (FLICM) algorithm, the difference image is divided into the change area and unchanged area. The proposed algorithm is applied to a real remote sensing data set. The application results show that the proposed algorithm can effectively suppress clutter noise, and retain more detailed information from the original images. The proposed algorithm has higher detection accuracy than the Markov Random Field-Fuzzy C-means (MRF-FCM), the non-subsampled contourlet transform-Fuzzy C-means clustering (NSCT-FCM), the pointwise approach and graph theory (PA-GT), and the Principal Component Analysis-Nonlocal Means (PCA-NLM) denosing algorithm. Finally, the five algorithms are used to detect the southern boundary of the Gurbantunggut Desert in Xinjiang Uygur Autonomous Region of China, and the results show that the proposed algorithm has the best effect on real remote sensing image change detection. PMID:28587299

Synchronized computational architecture for generalized bilateral control of robot arms

NASA Technical Reports Server (NTRS)

Szakaly, Zoltan F. (Inventor)

1991-01-01

A master six degree of freedom Force Reflecting Hand Controller (FRHC) is available at a master site where a received image displays, in essentially real time, a remote robotic manipulator which is being controlled in the corresponding six degree freedom by command signals which are transmitted to the remote site in accordance with the movement of the FRHC at the master site. Software is user-initiated at the master site in order to establish the basic system conditions, and then a physical movement of the FRHC in Cartesean space is reflected at the master site by six absolute numbers that are sensed, translated and computed as a difference signal relative to the earlier position. The change in position is then transmitted in that differential signal form over a high speed synchronized bilateral communication channel which simultaneously returns robot-sensed response information to the master site as forces applied to the FRHC so that the FRHC reflects the feel of what is taking place at the remote site. A system wide clock rate is selected at a sufficiently high rate that the operator at the master site experiences the Force Reflecting operation in real time.

A compressive sensing based secure watermark detection and privacy preserving storage framework.

PubMed

Qia Wang; Wenjun Zeng; Jun Tian

2014-03-01

Privacy is a critical issue when the data owners outsource data storage or processing to a third party computing service, such as the cloud. In this paper, we identify a cloud computing application scenario that requires simultaneously performing secure watermark detection and privacy preserving multimedia data storage. We then propose a compressive sensing (CS)-based framework using secure multiparty computation (MPC) protocols to address such a requirement. In our framework, the multimedia data and secret watermark pattern are presented to the cloud for secure watermark detection in a CS domain to protect the privacy. During CS transformation, the privacy of the CS matrix and the watermark pattern is protected by the MPC protocols under the semi-honest security model. We derive the expected watermark detection performance in the CS domain, given the target image, watermark pattern, and the size of the CS matrix (but without the CS matrix itself). The correctness of the derived performance has been validated by our experiments. Our theoretical analysis and experimental results show that secure watermark detection in the CS domain is feasible. Our framework can also be extended to other collaborative secure signal processing and data-mining applications in the cloud.

Development of a remote sensing algorithm to retrieve atmospheric aerosol properties using multiwavelength and multipixel information

NASA Astrophysics Data System (ADS)

Hashimoto, Makiko; Nakajima, Teruyuki

2017-06-01

We developed a satellite remote sensing algorithm to retrieve the aerosol optical properties using satellite-received radiances for multiple wavelengths and pixels. Our algorithm utilizes spatial inhomogeneity of surface reflectance to retrieve aerosol properties, and the main target is urban aerosols. This algorithm can simultaneously retrieve aerosol optical thicknesses (AOT) for fine- and coarse-mode aerosols, soot volume fraction in fine-mode aerosols (SF), and surface reflectance over heterogeneous surfaces such as urban areas that are difficult to obtain by conventional pixel-by-pixel methods. We applied this algorithm to radiances measured by the Greenhouse Gases Observing Satellite/Thermal and Near Infrared Sensor for Carbon Observations-Cloud and Aerosol Image (GOSAT/TANSO-CAI) at four wavelengths and were able to retrieve the aerosol parameters in several urban regions and other surface types. A comparison of the retrieved AOTs with those from the Aerosol Robotic Network (AERONET) indicated retrieval accuracy within ±0.077 on average. It was also found that the column-averaged SF and the aerosol single scattering albedo (SSA) underwent seasonal changes as consistent with the ground surface measurements of SSA and black carbon at Beijing, China.

Monitoring volcanic ash cloud top height through simultaneous retrieval of optical data from polar orbiting and geostationary satellites

NASA Astrophysics Data System (ADS)

Zakšek, K.; Hort, M.; Zaletelj, J.; Langmann, B.

2012-09-01

Volcanic ash cloud top height (ACTH) can be monitored on the global level using satellite remote sensing. Here we propose a photogrammetric method based on the parallax between data retrieved from geostationary and polar orbiting satellites to overcome some limitations of the existing methods of ACTH retrieval. SEVIRI HRV band and MODIS band 1 are a good choice because of their high resolution. The procedure works well if the data from both satellites are retrieved nearly simultaneously. MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. The proposed method was tested for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach over 30 km which implies ACTH of more than 12 km in the beginning of the eruption. In the end of April eruption ACTH of 3-4 km is observed. The accuracy of ACTH was estimated to be 0.6 km.

Monitoring volcanic ash cloud top height through simultaneous retrieval of optical data from polar orbiting and geostationary satellites

NASA Astrophysics Data System (ADS)

Zakšek, K.; Hort, M.; Zaletelj, J.; Langmann, B.

2013-03-01

Volcanic ash cloud-top height (ACTH) can be monitored on the global level using satellite remote sensing. Here we propose a photogrammetric method based on the parallax between data retrieved from geostationary and polar orbiting satellites to overcome some limitations of the existing methods of ACTH retrieval. SEVIRI HRV band and MODIS band 1 are a good choice because of their high resolution. The procedure works well if the data from both satellites are retrieved nearly simultaneously. MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. The proposed method was tested for the case of the Eyjafjallajökull eruption in April 2010. The parallax between MODIS and SEVIRI data can reach 30 km, which implies an ACTH of approximately 12 km at the beginning of the eruption. At the end of April eruption an ACTH of 3-4 km is observed. The accuracy of ACTH was estimated to be 0.6 km.

The quantitative control and matching of an optical false color composite imaging system

NASA Astrophysics Data System (ADS)

Zhou, Chengxian; Dai, Zixin; Pan, Xizhe; Li, Yinxi

1993-10-01

Design of an imaging system for optical false color composite (OFCC) capable of high-precision density-exposure time control and color balance is presented. The system provides high quality FCC image data that can be analyzed using a quantitative calculation method. The quality requirement to each part of the image generation system is defined, and the distribution of satellite remote sensing image information is analyzed. The proposed technology makes it possible to present the remote sensing image data more effectively and accurately.

Thematic Conference on Remote Sensing for Exploration Geology, 6th, Houston, TX, May 16-19, 1988, Proceedings. Volumes 1 & 2

NASA Technical Reports Server (NTRS)

1988-01-01

Papers concerning remote sensing applications for exploration geology are presented, covering topics such as remote sensing technology, data availability, frontier exploration, and exploration in mature basins. Other topics include offshore applications, geobotany, mineral exploration, engineering and environmental applications, image processing, and prospects for future developments in remote sensing for exploration geology. Consideration is given to the use of data from Landsat, MSS, TM, SAR, short wavelength IR, the Geophysical Environmental Research Airborne Scanner, gas chromatography, sonar imaging, the Airborne Visible-IR Imaging Spectrometer, field spectrometry, airborne thermal IR scanners, SPOT, AVHRR, SIR, the Large Format camera, and multitimephase satellite photographs.

Geometry correction Algorithm for UAV Remote Sensing Image Based on Improved Neural Network

NASA Astrophysics Data System (ADS)

Liu, Ruian; Liu, Nan; Zeng, Beibei; Chen, Tingting; Yin, Ninghao

2018-03-01

Aiming at the disadvantage of current geometry correction algorithm for UAV remote sensing image, a new algorithm is proposed. Adaptive genetic algorithm (AGA) and RBF neural network are introduced into this algorithm. And combined with the geometry correction principle for UAV remote sensing image, the algorithm and solving steps of AGA-RBF are presented in order to realize geometry correction for UAV remote sensing. The correction accuracy and operational efficiency is improved through optimizing the structure and connection weight of RBF neural network separately with AGA and LMS algorithm. Finally, experiments show that AGA-RBF algorithm has the advantages of high correction accuracy, high running rate and strong generalization ability.

Onboard utilization of ground control points for image correction. Volume 2: Analysis and simulation results

NASA Technical Reports Server (NTRS)

1981-01-01

An approach to remote sensing that meets future mission requirements was investigated. The deterministic acquisition of data and the rapid correction of data for radiometric effects and image distortions are the most critical limitations of remote sensing. The following topics are discussed: onboard image correction systems, GCP navigation system simulation, GCP analysis, and image correction analysis measurement.

Use of self-actuating and self-sensing cantilevers for imaging biological samples in fluid

PubMed Central

Barbero, R J; Deutschinger, A; Todorov, V; Gray, D S; Belcher, A M; Rangelow, I W; Youcef-Toumi, K

2014-01-01

In this paper, we present a detailed investigation into the suitability of atomic force microscopy (AFM) cantilevers with integrated deflection sensor and micro-actuator for imaging of soft biological samples in fluid. The Si cantilevers are actuated using a micro-heater at the bottom end of the cantilever. Sensing is achieved through p-doped resistors connected in a Wheatstone bridge. We investigated the influence of the water on the cantilever dynamics, the actuation and the sensing mechanisms, as well as the crosstalk between sensing and actuation. Successful imaging of yeast cells in water using the integrated sensor and actuator shows the potential of the combination of this actuation and sensing method. This constitutes a major step towards the automation and miniaturization required to establish AFM in routine biomedical diagnostics and in vivo applications. PMID:19801750

3D sensitivity encoded ellipsoidal MR spectroscopic imaging of gliomas at 3T☆

PubMed Central

Ozturk-Isik, Esin; Chen, Albert P.; Crane, Jason C.; Bian, Wei; Xu, Duan; Han, Eric T.; Chang, Susan M.; Vigneron, Daniel B.; Nelson, Sarah J.

2010-01-01

Purpose The goal of this study was to implement time efficient data acquisition and reconstruction methods for 3D magnetic resonance spectroscopic imaging (MRSI) of gliomas at a field strength of 3T using parallel imaging techniques. Methods The point spread functions, signal to noise ratio (SNR), spatial resolution, metabolite intensity distributions and Cho:NAA ratio of 3D ellipsoidal, 3D sensitivity encoding (SENSE) and 3D combined ellipsoidal and SENSE (e-SENSE) k-space sampling schemes were compared with conventional k-space data acquisition methods. Results The 3D SENSE and e-SENSE methods resulted in similar spectral patterns as the conventional MRSI methods. The Cho:NAA ratios were highly correlated (P<.05 for SENSE and P<.001 for e-SENSE) with the ellipsoidal method and all methods exhibited significantly different spectral patterns in tumor regions compared to normal appearing white matter. The geometry factors ranged between 1.2 and 1.3 for both the SENSE and e-SENSE spectra. When corrected for these factors and for differences in data acquisition times, the empirical SNRs were similar to values expected based upon theoretical grounds. The effective spatial resolution of the SENSE spectra was estimated to be same as the corresponding fully sampled k-space data, while the spectra acquired with ellipsoidal and e-SENSE k-space samplings were estimated to have a 2.36–2.47-fold loss in spatial resolution due to the differences in their point spread functions. Conclusion The 3D SENSE method retained the same spatial resolution as full k-space sampling but with a 4-fold reduction in scan time and an acquisition time of 9.28 min. The 3D e-SENSE method had a similar spatial resolution as the corresponding ellipsoidal sampling with a scan time of 4:36 min. Both parallel imaging methods provided clinically interpretable spectra with volumetric coverage and adequate SNR for evaluating Cho, Cr and NAA. PMID:19766422

Watermarking techniques for electronic delivery of remote sensing images

NASA Astrophysics Data System (ADS)

Barni, Mauro; Bartolini, Franco; Magli, Enrico; Olmo, Gabriella

2002-09-01

Earth observation missions have recently attracted a growing interest, mainly due to the large number of possible applications capable of exploiting remotely sensed data and images. Along with the increase of market potential, the need arises for the protection of the image products. Such a need is a very crucial one, because the Internet and other public/private networks have become preferred means of data exchange. A critical issue arising when dealing with digital image distribution is copyright protection. Such a problem has been largely addressed by resorting to watermarking technology. A question that obviously arises is whether the requirements imposed by remote sensing imagery are compatible with existing watermarking techniques. On the basis of these motivations, the contribution of this work is twofold: assessment of the requirements imposed by remote sensing applications on watermark-based copyright protection, and modification of two well-established digital watermarking techniques to meet such constraints. More specifically, the concept of near-lossless watermarking is introduced and two possible algorithms matching such a requirement are presented. Experimental results are shown to measure the impact of watermark introduction on a typical remote sensing application, i.e., unsupervised image classification.

Construction of an unmanned aerial vehicle remote sensing system for crop monitoring

NASA Astrophysics Data System (ADS)

Jeong, Seungtaek; Ko, Jonghan; Kim, Mijeong; Kim, Jongkwon

2016-04-01

We constructed a lightweight unmanned aerial vehicle (UAV) remote sensing system and determined the ideal method for equipment setup, image acquisition, and image processing. Fields of rice paddy (Oryza sativa cv. Unkwang) grown under three different nitrogen (N) treatments of 0, 50, or 115 kg/ha were monitored at Chonnam National University, Gwangju, Republic of Korea, in 2013. A multispectral camera was used to acquire UAV images from the study site. Atmospheric correction of these images was completed using the empirical line method, and three-point (black, gray, and white) calibration boards were used as pseudo references. Evaluation of our corrected UAV-based remote sensing data revealed that correction efficiency and root mean square errors ranged from 0.77 to 0.95 and 0.01 to 0.05, respectively. The time series maps of simulated normalized difference vegetation index (NDVI) produced using the UAV images reproduced field variations of NDVI reasonably well, both within and between the different N treatments. We concluded that the UAV-based remote sensing technology utilized in this study is potentially an easy and simple way to quantitatively obtain reliable two-dimensional remote sensing information on crop growth.

Ratiometric, visual, dual-signal fluorescent sensing and imaging of pH/copper ions in real samples based on carbon dots-fluorescein isothiocyanate composites.

PubMed

Zhu, Xinxin; Jin, Hui; Gao, Cuili; Gui, Rijun; Wang, Zonghua

2017-01-01

In this article, a facile aqueous synthesis of carbon dots (CDs) was developed by using natural kelp as a new carbon source. Through hydrothermal carbonization of kelp juice, fluorescent CDs were prepared and the CDs' surface was modified with polyethylenimine (PEI). The PEI-modified CDs were conjugated with fluorescein isothiocyanate (FITC) to fabricate CDs-FITC composites. To exploit broad applications, the CDs-FITC composites were developed as fluorescent sensing or imaging platforms of pH and Cu 2+ . Analytical performances of the composites-based fluorescence (FL) sensors were evaluated, including visual FL imaging of pH in glass bottle, ratiometric FL sensing of pH in yogurt samples, visual FL latent fingerprint and leaf imaging detection of [Cu 2+ ], dual-signal FL sensing of [Cu 2+ ] in yogurt and human serum samples. Experimental results from ratiometric, visual, dual-signal FL sensing and imaging applications confirmed the high feasibility, accuracy, stabilization and simplicity of CDs-FITC composites-based FL sensors for the detection of pH and Cu 2+ ions in real samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Sensing Super-Position: Human Sensing Beyond the Visual Spectrum

NASA Technical Reports Server (NTRS)

Maluf, David A.; Schipper, John F.

2007-01-01

The coming decade of fast, cheap and miniaturized electronics and sensory devices opens new pathways for the development of sophisticated equipment to overcome limitations of the human senses. This paper addresses the technical feasibility of augmenting human vision through Sensing Super-position by mixing natural Human sensing. The current implementation of the device translates visual and other passive or active sensory instruments into sounds, which become relevant when the visual resolution is insufficient for very difficult and particular sensing tasks. A successful Sensing Super-position meets many human and pilot vehicle system requirements. The system can be further developed into cheap, portable, and low power taking into account the limited capabilities of the human user as well as the typical characteristics of his dynamic environment. The system operates in real time, giving the desired information for the particular augmented sensing tasks. The Sensing Super-position device increases the image resolution perception and is obtained via an auditory representation as well as the visual representation. Auditory mapping is performed to distribute an image in time. The three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. This paper details the approach of developing Sensing Super-position systems as a way to augment the human vision system by exploiting the capabilities of Lie human hearing system as an additional neural input. The human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns. The known capabilities of the human hearing system to learn and understand complicated auditory patterns provided the basic motivation for developing an image-to-sound mapping system. The human brain is superior to most existing computer systems in rapidly extracting relevant information from blurred, noisy, and redundant images. From a theoretical viewpoint, this means that the available bandwidth is not exploited in an optimal way. While image-processing techniques can manipulate, condense and focus the information (e.g., Fourier Transforms), keeping the mapping as direct and simple as possible might also reduce the risk of accidentally filtering out important clues. After all, especially a perfect non-redundant sound representation is prone to loss of relevant information in the non-perfect human hearing system. Also, a complicated non-redundant image-to-sound mapping may well be far more difficult to learn and comprehend than a straightforward mapping, while the mapping system would increase in complexity and cost. This work will demonstrate some basic information processing for optimal information capture for headmounted systems.

Copyright protection of remote sensing imagery by means of digital watermarking

NASA Astrophysics Data System (ADS)

Barni, Mauro; Bartolini, Franco; Cappellini, Vito; Magli, Enrico; Olmo, Gabriella; Zanini, R.

2001-12-01

The demand for remote sensing data has increased dramatically mainly due to the large number of possible applications capable to exploit remotely sensed data and images. As in many other fields, along with the increase of market potential and product diffusion, the need arises for some sort of protection of the image products from unauthorized use. Such a need is a very crucial one even because the Internet and other public/private networks have become preferred and effective means of data exchange. An important issue arising when dealing with digital image distribution is copyright protection. Such a problem has been largely addressed by resorting to watermarking technology. Before applying watermarking techniques developed for multimedia applications to remote sensing applications, it is important that the requirements imposed by remote sensing imagery are carefully analyzed to investigate whether they are compatible with existing watermarking techniques. On the basis of these motivations, the contribution of this work is twofold: (1) assessment of the requirements imposed by the characteristics of remotely sensed images on watermark-based copyright protection; (2) discussion of a case study where the performance of two popular, state-of-the-art watermarking techniques are evaluated by the light of the requirements at the previous point.

Radarsat Satellite Images: A New Geography Tool for Upper Elementary Classrooms.

ERIC Educational Resources Information Center

Kirman, Joseph M.

1999-01-01

Describes the Canadian Radarsat Satellite and remote sensing in order to demonstrate that teachers can incorporate this technology into the classroom. Maintains that third, fourth, fifth, and sixth grade students can understand and interpret remote sensing images and Landsat images. Provides a list of teaching resources other than the expensive…

Multifunctional PHPMA-Derived Polymer for Ratiometric pH Sensing, Fluorescence Imaging, and Magnetic Resonance Imaging.

PubMed

Su, Fengyu; Agarwal, Shubhangi; Pan, Tingting; Qiao, Yuan; Zhang, Liqiang; Shi, Zhengwei; Kong, Xiangxing; Day, Kevin; Chen, Meiwan; Meldrum, Deirdre; Kodibagkar, Vikram D; Tian, Yanqing

2018-01-17

In this paper, we report synthesis and characterization of a novel multimodality (MRI/fluorescence) probe for pH sensing and imaging. A multifunctional polymer was derived from poly(N-(2-hydroxypropyl)methacrylamide) (PHPMA) and integrated with a naphthalimide-based-ratiometric fluorescence probe and a gadolinium-1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid complex (Gd-DOTA complex). The polymer was characterized using UV-vis absorption spectrophotometry, fluorescence spectrofluorophotometry, magnetic resonance imaging (MRI), and confocal microscopy for optical and MRI-based pH sensing and cellular imaging. In vitro labeling of macrophage J774 and esophageal CP-A cell lines shows the polymer's ability to be internalized in the cells. The transverse relaxation time (T 2 ) of the polymer was observed to be pH-dependent, whereas the spin-lattice relaxation time (T 1 ) was not. The pH probe in the polymer shows a strong fluorescence-based ratiometric pH response with emission window changes, exhibiting blue emission under acidic conditions and green emission under basic conditions, respectively. This study provides new materials with multimodalities for pH sensing and imaging.

Simultaneous multi-headed imager geometry calibration method

DOEpatents

Tran, Vi-Hoa [Newport News, VA; Meikle, Steven Richard [Penshurst, AU; Smith, Mark Frederick [Yorktown, VA

2008-02-19

A method for calibrating multi-headed high sensitivity and high spatial resolution dynamic imaging systems, especially those useful in the acquisition of tomographic images of small animals. The method of the present invention comprises: simultaneously calibrating two or more detectors to the same coordinate system; and functionally correcting for unwanted detector movement due to gantry flexing.

Design of an imaging spectrometer for earth observation using freeform mirrors

NASA Astrophysics Data System (ADS)

Peschel, T.; Damm, C.; Beier, M.; Gebhardt, A.; Risse, S.; Walter, I.; Sebastian, I.; Krutz, D.

2017-09-01

In 2017 the new hyperspectral DLR Earth Sensing Imaging Spectrometer (DESIS) will be integrated in the Multi-User-System for Earth Sensing (MUSES) platform [1] installed on the International Space Station (ISS).

Research on simulation technology of full-path infrared tail flame tracking of photoelectric theodolite in complicated environment

NASA Astrophysics Data System (ADS)

Wu, Hai-ying; Zhang, San-xi; Liu, Biao; Yue, Peng; Weng, Ying-hui

2018-02-01

The photoelectric theodolite is an important scheme to realize the tracking, detection, quantitative measurement and performance evaluation of weapon systems in ordnance test range. With the improvement of stability requirements for target tracking in complex environment, infrared scene simulation with high sense of reality and complex interference has become an indispensable technical way to evaluate the track performance of photoelectric theodolite. And the tail flame is the most important infrared radiation source of the weapon system. The dynamic tail flame with high reality is a key element for the photoelectric theodolite infrared scene simulation and imaging tracking test. In this paper, an infrared simulation method for the full-path tracking of tail flame by photoelectric theodolite is proposed aiming at the faint boundary, irregular, multi-regulated points. In this work, real tail images are employed. Simultaneously, infrared texture conversion technology is used to generate DDS texture for a particle system map. Thus, dynamic real-time tail flame simulation results with high fidelity from the theodolite perspective can be gained in the tracking process.

The Slope Imaging Multi-Polarization Photon-Counting Lidar: Development and Performance Results

NASA Technical Reports Server (NTRS)

Dabney, Phillip

2010-01-01

The Slope Imaging Multi-polarization Photon-counting Lidar is an airborne instrument developed to demonstrate laser altimetry measurement methods that will enable more efficient observations of topography and surface properties from space. The instrument was developed through the NASA Earth Science Technology Office Instrument Incubator Program with a focus on cryosphere remote sensing. The SIMPL transmitter is an 11 KHz, 1064 nm, plane-polarized micropulse laser transmitter that is frequency doubled to 532 nm and split into four push-broom beams. The receiver employs single-photon, polarimetric ranging at 532 and 1064 nm using Single Photon Counting Modules in order to achieve simultaneous sampling of surface elevation, slope, roughness and depolarizing scattering properties, the latter used to differentiate surface types. Data acquired over ice-covered Lake Erie in February, 2009 are documenting SIMPL s measurement performance and capabilities, demonstrating differentiation of open water and several ice cover types. ICESat-2 will employ several of the technologies advanced by SIMPL, including micropulse, single photon ranging in a multi-beam, push-broom configuration operating at 532 nm.

Measurements of OH(X2pi) in the stratosphere by high resolution UV spectroscopy

NASA Technical Reports Server (NTRS)

Torr, D. G.; Swift, W.; Fennelly, J.; Liu, G.; Torr, M. R.

1987-01-01

This paper reports the first results obtained using high spectral resolution imaging ultraviolet spectroscopy to observe multiple rotational lines of OH A2 Sigma-X2pi (0-0) band. A 9.2 A spectral segment from 3075.8 A to 3085.0 A is imaged at 0.08 A FWHM spectral resolution, allowing the simultaneous acquisition of six of the brightest OH resonance fluorescence emission lines. The high spectral resolution and low scattered light design of the instrument allows these lines to be detected above the Rayleigh scattered sunlight background. The technique permits remote sensing of stratospheric OH from a high altitude instrument. The instrument was flown to an altitude of 40 km on Aug. 25, 1983, and again on June 12, 1986, on scientific balloons from Palestine, TX. The OH profiles inverted from the limb scans made during these flights are reported here. These profiles represent the first measurements of the temporal variation of OH over an extended height range. The results demonstrate that the technique can be used to monitor OH from orbit.

Micropillar displacements by cell traction forces are mechanically correlated with nuclear dynamics

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

Li, Qingsen; Makhija, Ekta; Hameed, F.M.

2015-05-29

Cells sense physical cues at the level of focal adhesions and transduce them to the nucleus by biochemical and mechanical pathways. While the molecular intermediates in the mechanical links have been well studied, their dynamic coupling is poorly understood. In this study, fibroblast cells were adhered to micropillar arrays to probe correlations in the physical coupling between focal adhesions and nucleus. For this, we used novel imaging setup to simultaneously visualize micropillar deflections and EGFP labeled chromatin structure at high spatial and temporal resolution. We observed that micropillar deflections, depending on their relative positions, were positively or negatively correlated tomore » nuclear and heterochromatin movements. Our results measuring the time scales between micropillar deflections and nucleus centroid displacement are suggestive of a strong elastic coupling that mediates differential force transmission to the nucleus. - Highlights: • Correlation between focal adhesions and nucleus studied using novel imaging setup. • Micropillar and nuclear displacements were measured at high resolution. • Correlation timescales show strong elastic coupling between cell edge and nucleus.« less

Remote sensing of submerged aquatic vegetation in lower Chesapeake Bay - A comparison of Landsat MSS to TM imagery

NASA Technical Reports Server (NTRS)

Ackleson, S. G.; Klemas, V.

1987-01-01

Landsat MSS and TM imagery, obtained simultaneously over Guinea Marsh, VA, as analyzed and compares for its ability to detect submerged aquatic vegetation (SAV). An unsupervised clustering algorithm was applied to each image, where the input classification parameters are defined as functions of apparent sensor noise. Class confidence and accuracy were computed for all water areas by comparing the classified images, pixel-by-pixel, to rasterized SAV distributions derived from color aerial photography. To illustrate the effect of water depth on classification error, areas of depth greater than 1.9 m were masked, and class confidence and accuracy recalculated. A single-scattering radiative-transfer model is used to illustrate how percent canopy cover and water depth affect the volume reflectance from a water column containing SAV. For a submerged canopy that is morphologically and optically similar to Zostera marina inhabiting Lower Chesapeake Bay, dense canopies may be isolated by masking optically deep water. For less dense canopies, the effect of increasing water depth is to increase the apparent percent crown cover, which may result in classification error.

Hyperspectral imaging to monitor simultaneously multiple protein subtypes and live track their spatial dynamics: a new platform to screen drugs for CNS diseases

NASA Astrophysics Data System (ADS)

Labrecque, S.; Sylvestre, J.-P.; Marcet, S.; Mangiarini, F.; Verhaegen, M.; De Koninck, P.; Blais-Ouellette, S.

2015-03-01

In the past decade, the efficacy of existing therapies and the discovery of innovative treatments for Central Nervous System (CNS) diseases have been limited by the lack of appropriate methods to investigate complex molecular processes at the synaptic level. In order to better understand the fundamental mechanisms that regulate diseases of the CNS, a fast fluorescence hyperspectral imaging platform was designed to track simultaneously various neurotransmitter receptors trafficking in and out of synapses. With this hyperspectral imaging platform, it was possible to image simultaneously five different synaptic proteins, including subtypes of glutamate receptors (mGluR, NMDAR, AMPAR), postsynaptic density proteins, and signaling proteins. This new imaging platform allows fast simultaneous acquisitions of at least five fluorescent markers in living neurons with a high spatial resolution. This technique provides an effective method to observe several synaptic proteins at the same time, thus study how drugs for CNS impact the spatial dynamics of these proteins.

Human visual system consistent quality assessment for remote sensing image fusion

NASA Astrophysics Data System (ADS)

Liu, Jun; Huang, Junyi; Liu, Shuguang; Li, Huali; Zhou, Qiming; Liu, Junchen

2015-07-01

Quality assessment for image fusion is essential for remote sensing application. Generally used indices require a high spatial resolution multispectral (MS) image for reference, which is not always readily available. Meanwhile, the fusion quality assessments using these indices may not be consistent with the Human Visual System (HVS). As an attempt to overcome this requirement and inconsistency, this paper proposes an HVS-consistent image fusion quality assessment index at the highest resolution without a reference MS image using Gaussian Scale Space (GSS) technology that could simulate the HVS. The spatial details and spectral information of original and fused images are first separated in GSS, and the qualities are evaluated using the proposed spatial and spectral quality index respectively. The overall quality is determined without a reference MS image by a combination of the proposed two indices. Experimental results on various remote sensing images indicate that the proposed index is more consistent with HVS evaluation compared with other widely used indices that may or may not require reference images.

Design and characterization of a handheld multimodal imaging device for the assessment of oral epithelial lesions

NASA Astrophysics Data System (ADS)

Higgins, Laura M.; Pierce, Mark C.

2014-08-01

A compact handpiece combining high resolution fluorescence (HRF) imaging with optical coherence tomography (OCT) was developed to provide real-time assessment of oral lesions. This multimodal imaging device simultaneously captures coregistered en face images with subcellular detail alongside cross-sectional images of tissue microstructure. The HRF imaging acquires a 712×594 μm2 field-of-view at the sample with a spatial resolution of 3.5 μm. The OCT images were acquired to a depth of 1.5 mm with axial and lateral resolutions of 9.3 and 8.0 μm, respectively. HRF and OCT images are simultaneously displayed at 25 fps. The handheld device was used to image a healthy volunteer, demonstrating the potential for in vivo assessment of the epithelial surface for dysplastic and neoplastic changes at the cellular level, while simultaneously evaluating submucosal involvement. We anticipate potential applications in real-time assessment of oral lesions for improved surveillance and surgical guidance.

Remote Sensing Image Classification Applied to the First National Geographical Information Census of China

NASA Astrophysics Data System (ADS)

Yu, Xin; Wen, Zongyong; Zhu, Zhaorong; Xia, Qiang; Shun, Lan

2016-06-01

Image classification will still be a long way in the future, although it has gone almost half a century. In fact, researchers have gained many fruits in the image classification domain, but there is still a long distance between theory and practice. However, some new methods in the artificial intelligence domain will be absorbed into the image classification domain and draw on the strength of each to offset the weakness of the other, which will open up a new prospect. Usually, networks play the role of a high-level language, as is seen in Artificial Intelligence and statistics, because networks are used to build complex model from simple components. These years, Bayesian Networks, one of probabilistic networks, are a powerful data mining technique for handling uncertainty in complex domains. In this paper, we apply Tree Augmented Naive Bayesian Networks (TAN) to texture classification of High-resolution remote sensing images and put up a new method to construct the network topology structure in terms of training accuracy based on the training samples. Since 2013, China government has started the first national geographical information census project, which mainly interprets geographical information based on high-resolution remote sensing images. Therefore, this paper tries to apply Bayesian network to remote sensing image classification, in order to improve image interpretation in the first national geographical information census project. In the experiment, we choose some remote sensing images in Beijing. Experimental results demonstrate TAN outperform than Naive Bayesian Classifier (NBC) and Maximum Likelihood Classification Method (MLC) in the overall classification accuracy. In addition, the proposed method can reduce the workload of field workers and improve the work efficiency. Although it is time consuming, it will be an attractive and effective method for assisting office operation of image interpretation.

Detection of mesoscale zones of atmospheric instabilities using remote sensing and weather forecasting model data

NASA Astrophysics Data System (ADS)

Winnicki, I.; Jasinski, J.; Kroszczynski, K.; Pietrek, S.

2009-04-01

The paper presents elements of research conducted in the Faculty of Civil Engineering and Geodesy of the Military University of Technology, Warsaw, Poland, concerning application of mesoscale models and remote sensing data to determining meteorological conditions of aircraft flight directly related with atmospheric instabilities. The quality of meteorological support of aviation depends on prompt and effective forecasting of weather conditions changes. The paper presents a computer module for detecting and monitoring zones of cloud cover, precipitation and turbulence along the aircraft flight route. It consists of programs and scripts for managing, processing and visualizing meteorological and remote sensing databases. The application was developed in Matlab® for Windows®. The module uses products of COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) mesoscale non-hydrostatic model of the atmosphere developed by the US Naval Research Laboratory, satellite images acquisition system from the MSG-2 (Meteosat Second Generation) of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and meteorological radars data acquired from the Institute of Meteorology and Water Management (IMGW), Warsaw, Poland. The satellite images acquisition system and the COAMPS model are run operationally in the Faculty of Civil Engineering and Geodesy. The mesoscale model is run on an IA64 Feniks multiprocessor 64-bit computer cluster. The basic task of the module is to enable a complex analysis of data sets of miscellaneous information structure and to verify COAMPS results using satellite and radar data. The research is conducted using uniform cartographic projection of all elements of the database. Satellite and radar images are transformed into the Lambert Conformal projection of COAMPS. This facilitates simultaneous interpretation and supports decision making process for safe execution of flights. Forecasts are based on horizontal distributions and vertical profiles of meteorological parameters produced by the module. Verification of forecasts includes research of spatial and temporal correlations of structures generated by the model, e.g.: cloudiness, meteorological phenomena (fogs, precipitation, turbulence) and structures identified on current satellite images. The developed module determines meteorological parameters fields for vertical profiles of the atmosphere. Interpolation procedures run at user selected standard (pressure) or height levels of the model enable to determine weather conditions along any route of aircraft. Basic parameters of the procedures determining e.g. flight safety include: cloud base, visibility, cloud cover, turbulence coefficient, icing and precipitation intensity. Determining icing and turbulence characteristics is based on standard and new methods (from other mesoscale models). The research includes also investigating new generation mesoscale models, especially remote sensing data assimilation. This is required by necessity to develop and introduce objective methods of forecasting weather conditions. Current research in the Faculty of Civil Engineering and Geodesy concerns validation of the mesoscale module performance.

Long-range non-contact imaging photoplethysmography: cardiac pulse wave sensing at a distance

NASA Astrophysics Data System (ADS)

Blackford, Ethan B.; Estepp, Justin R.; Piasecki, Alyssa M.; Bowers, Margaret A.; Klosterman, Samantha L.

2016-03-01

Non-contact, imaging photoplethysmography uses photo-optical sensors to measure variations in light absorption, caused by blood volume pulsations, to assess cardiopulmonary parameters including pulse rate, pulse rate variability, and respiration rate. Recently, researchers have studied the applications and methodology of imaging photoplethysmography. Basic research has examined some of the variables affecting data quality and accuracy of imaging photoplethysmography including signal processing, imager parameters (e.g. frame rate and resolution), lighting conditions, subject motion, and subject skin tone. This technology may be beneficial for long term or continuous monitoring where contact measurements may be harmful (e.g. skin sensitivities) or where imperceptible or unobtrusive measurements are desirable. Using previously validated signal processing methods, we examined the effects of imager-to-subject distance on one-minute, windowed estimates of pulse rate. High-resolution video of 22, stationary participants was collected using an enthusiast-grade, mirrorless, digital camera equipped with a fully-manual, super-telephoto lens at distances of 25, 50, and 100 meters with simultaneous contact measurements of electrocardiography, and fingertip photoplethysmography. By comparison, previous studies have usually been conducted with imager-to-subject distances of up to only a few meters. Mean absolute error for one-minute, windowed, pulse rate estimates (compared to those derived from gold-standard electrocardiography) were 2.0, 4.1, and 10.9 beats per minute at distances of 25, 50, and 100 meters, respectively. Long-range imaging presents several unique challenges among which include decreased, observed light reflectance and smaller regions of interest. Nevertheless, these results demonstrate that accurate pulse rate measurements can be obtained from over long imager-to-participant distances given these constraints.

High-speed image processing system and its micro-optics application

NASA Astrophysics Data System (ADS)

Ohba, Kohtaro; Ortega, Jesus C. P.; Tanikawa, Tamio; Tanie, Kazuo; Tajima, Kenji; Nagai, Hiroshi; Tsuji, Masataka; Yamada, Shigeru

2003-07-01

In this paper, a new application system with high speed photography, i.e. an observational system for the tele-micro-operation, has been proposed with a dynamic focusing system and a high-speed image processing system using the "Depth From Focus (DFF)" criteria. In micro operation, such as for the microsurgery, DNA operation and etc., the small depth of a focus on the microscope makes bad observation. For example, if the focus is on the object, the actuator cannot be seen with the microscope. On the other hand, if the focus is on the actuator, the object cannot be observed. In this sense, the "all-in-focus image," which holds the in-focused texture all over the image, is useful to observe the microenvironments on the microscope. It is also important to obtain the "depth map" which could show the 3D micro virtual environments in real-time to actuate the micro objects, intuitively. To realize the real-time micro operation with DFF criteria, which has to integrate several images to obtain "all-in-focus image" and "depth map," at least, the 240 frames par second based image capture and processing system should be required. At first, this paper briefly reviews the criteria of "depth from focus" to achieve the all-in-focus image and the 3D microenvironments' reconstruction, simultaneously. After discussing the problem in our past system, a new frame-rate system is constructed with the high-speed video camera and FPGA hardware with 240 frames par second. To apply this system in the real microscope, a new criterion "ghost filtering" technique to reconstruct the all-in-focus image is proposed. Finally, the micro observation shows the validity of this system.

Purification of Training Samples Based on Spectral Feature and Superpixel Segmentation

NASA Astrophysics Data System (ADS)

Guan, X.; Qi, W.; He, J.; Wen, Q.; Chen, T.; Wang, Z.

2018-04-01

Remote sensing image classification is an effective way to extract information from large volumes of high-spatial resolution remote sensing images. Generally, supervised image classification relies on abundant and high-precision training data, which is often manually interpreted by human experts to provide ground truth for training and evaluating the performance of the classifier. Remote sensing enterprises accumulated lots of manually interpreted products from early lower-spatial resolution remote sensing images by executing their routine research and business programs. However, these manually interpreted products may not match the very high resolution (VHR) image properly because of different dates or spatial resolution of both data, thus, hindering suitability of manually interpreted products in training classification models, or small coverage area of these manually interpreted products. We also face similar problems in our laboratory in 21st Century Aerospace Technology Co. Ltd (short for 21AT). In this work, we propose a method to purify the interpreted product to match newly available VHRI data and provide the best training data for supervised image classifiers in VHR image classification. And results indicate that our proposed method can efficiently purify the input data for future machine learning use.

Thermal remote sensing as a part of Exupéry volcano fast response system

NASA Astrophysics Data System (ADS)

Zakšek, Klemen; Hort, Matthias

2010-05-01

In order to understand the eruptive potential of a volcanic system one has to characterize the actual state of stress of a volcanic system that involves proper monitoring strategies. As several volcanoes in highly populated areas especially in south east Asia are still nearly unmonitored a mobile volcano monitoring system is currently being developed in Germany. One of the major novelties of this mobile volcano fast response system called Exupéry is the direct inclusion of satellite based observations. Remote sensing data are introduced together with ground based field measurements into the GIS database, where the statistical properties of all recorded data are estimated. Using physical modelling and statistical methods we hope to constrain the probability of future eruptions. The emphasis of this contribution is on using thermal remote sensing as tool for monitoring active volcanoes. One can detect thermal anomalies originating from a volcano by comparing signals in mid and thermal infrared spectra. A reliable and effective thermal anomalies detection algorithm was developed by Wright (2002) for MODIS sensor; it is based on the threshold of the so called normalized thermal index (NTI). This is the method we use in Exupéry, where we characterize each detected thermal anomaly by temperature, area, heat flux and effusion rate. The recent work has shown that radiant flux is the most robust parameter for this characterization. Its derivation depends on atmosphere, satellite viewing angle and sensor characteristics. Some of these influences are easy to correct using standard remote sensing pre-processing techniques, however, some noise still remains in data. In addition, satellites in polar orbits have long revisit times and thus they might fail to follow a fast evolving volcanic crisis due to long revisit times. Thus we are currently testing Kalman filter on simultaneous use of MODIS and AVHRR data to improve the thermal anomaly characterization. The advantage of this technique is that it increases the temporal resolution through using images from different satellites having different resolution and sensitivity. This algorithm has been tested for an eruption at Mt. Etna (2002) and successfully captures more details of the eruption evolution than would be seen by using only one satellite source. At the moment for Exupéry, merely MODIS (a sensor aboard NASA's Terra and Aqua satellite) data are used for the operational use. As MODIS is a meteorological sensor, it is suitable also for producing general overview images of the crisis area. Therefore, for each processed MODIS image we also produce RGB image where some basic meteorological features are classified: e.g. clouds, volcanic ash plumes, ocean, etc. In the case of detected hotspot an additional image is created; it contains the original measured radiances of the selected channels for the crisis area. All anomaly and processing parameters are additionally written into an XML file. The results are available in web GIS in the worst case two hours after NASA provides level 1b data online.

SenseCam reminiscence and action recall in memory-unimpaired people.

PubMed

Seamon, John G; Moskowitz, Tacie N; Swan, Ashley E; Zhong, Boyuan; Golembeski, Amy; Liong, Christopher; Narzikul, Alexa C; Sosan, Olumide A

2014-01-01

Case studies of memory-impaired individuals consistently show that reminiscing with SenseCam images enhances event recall. This exploratory study examined whether a similar benefit would occur for the consolidation of memories in memory-unimpaired people. We tested delayed recall for atypical actions observed on a lengthy walk. Participants used SenseCam, a diary, or no external memory aid while walking, followed by reminiscence with SenseCam images, diary entries, or no aid, either alone (self-reminiscence) or with the experimenter (social reminiscence). One week later, when tested without SenseCam images or diary entries, prior social reminiscence produced greater recall than self-reminiscence, but there were no differences between memory aid conditions for action free recall or action order recall. When methodological variables were controlled, there was no recall advantage for SenseCam reminiscence with memory-unimpaired participants. The case studies and present study differ in multiple ways, making direct comparisons problematic. SenseCam is a valuable aid to the memory impaired, but its mnemonic value for non-clinical populations remains to be determined.

A Remote Sensing Image Fusion Method based on adaptive dictionary learning

NASA Astrophysics Data System (ADS)

He, Tongdi; Che, Zongxi

2018-01-01

This paper discusses using a remote sensing fusion method, based on' adaptive sparse representation (ASP)', to provide improved spectral information, reduce data redundancy and decrease system complexity. First, the training sample set is formed by taking random blocks from the images to be fused, the dictionary is then constructed using the training samples, and the remaining terms are clustered to obtain the complete dictionary by iterated processing at each step. Second, the self-adaptive weighted coefficient rule of regional energy is used to select the feature fusion coefficients and complete the reconstruction of the image blocks. Finally, the reconstructed image blocks are rearranged and an average is taken to obtain the final fused images. Experimental results show that the proposed method is superior to other traditional remote sensing image fusion methods in both spectral information preservation and spatial resolution.

Possibility of Cloudless Optical Remote Sensing Images Acquisition Study by Using Meteorological Satellite Observations

NASA Astrophysics Data System (ADS)

Zhang, T.; Lei, B.; Hu, Y.; Liu, K.; Gan, Y.

2018-04-01

Optical remote sensing images have been widely used in feature interpretation and geo-information extraction. All the fundamental applications of optical remote sensing, are greatly influenced by cloud coverage. Generally, the availability of cloudless images depends on the meteorological conditions for a given area. In this study, the cloud total amount (CTA) products of the Fengyun (FY) satellite were introduced to explore the meteorological changes in a year over China. The cloud information of CTA products were tested by using ZY-3 satellite images firstly. CTA products from 2006 to 2017 were used to get relatively reliable results. The window period of cloudless images acquisition for different areas in China was then determined. This research provides a feasible way to get the cloudless images acquisition window by using meteorological observations.

Three-dimensional fluorescent microscopy via simultaneous illumination and detection at multiple planes.

PubMed

Ma, Qian; Khademhosseinieh, Bahar; Huang, Eric; Qian, Haoliang; Bakowski, Malina A; Troemel, Emily R; Liu, Zhaowei

2016-08-16

The conventional optical microscope is an inherently two-dimensional (2D) imaging tool. The objective lens, eyepiece and image sensor are all designed to capture light emitted from a 2D 'object plane'. Existing technologies, such as confocal or light sheet fluorescence microscopy have to utilize mechanical scanning, a time-multiplexing process, to capture a 3D image. In this paper, we present a 3D optical microscopy method based upon simultaneously illuminating and detecting multiple focal planes. This is implemented by adding two diffractive optical elements to modify the illumination and detection optics. We demonstrate that the image quality of this technique is comparable to conventional light sheet fluorescent microscopy with the advantage of the simultaneous imaging of multiple axial planes and reduced number of scans required to image the whole sample volume.

Scaling dimensions in spectroscopy of soil and vegetation

NASA Astrophysics Data System (ADS)

Malenovský, Zbyněk; Bartholomeus, Harm M.; Acerbi-Junior, Fausto W.; Schopfer, Jürg T.; Painter, Thomas H.; Epema, Gerrit F.; Bregt, Arnold K.

2007-05-01

The paper revises and clarifies definitions of the term scale and scaling conversions for imaging spectroscopy of soil and vegetation. We demonstrate a new four-dimensional scale concept that includes not only spatial but also the spectral, directional and temporal components. Three scaling remote sensing techniques are reviewed: (1) radiative transfer, (2) spectral (un)mixing, and (3) data fusion. Relevant case studies are given in the context of their up- and/or down-scaling abilities over the soil/vegetation surfaces and a multi-source approach is proposed for their integration. Radiative transfer (RT) models are described to show their capacity for spatial, spectral up-scaling, and directional down-scaling within a heterogeneous environment. Spectral information and spectral derivatives, like vegetation indices (e.g. TCARI/OSAVI), can be scaled and even tested by their means. Radiative transfer of an experimental Norway spruce ( Picea abies (L.) Karst.) research plot in the Czech Republic was simulated by the Discrete Anisotropic Radiative Transfer (DART) model to prove relevance of the correct object optical properties scaled up to image data at two different spatial resolutions. Interconnection of the successive modelling levels in vegetation is shown. A future development in measurement and simulation of the leaf directional spectral properties is discussed. We describe linear and/or non-linear spectral mixing techniques and unmixing methods that demonstrate spatial down-scaling. Relevance of proper selection or acquisition of the spectral endmembers using spectral libraries, field measurements, and pure pixels of the hyperspectral image is highlighted. An extensive list of advanced unmixing techniques, a particular example of unmixing a reflective optics system imaging spectrometer (ROSIS) image from Spain, and examples of other mixture applications give insight into the present status of scaling capabilities. Simultaneous spatial and temporal down-scaling by means of a data fusion technique is described. A demonstrative example is given for the moderate resolution imaging spectroradiometer (MODIS) and LANDSAT Thematic Mapper (TM) data from Brazil. Corresponding spectral bands of both sensors were fused via a pyramidal wavelet transform in Fourier space. New spectral and temporal information of the resultant image can be used for thematic classification or qualitative mapping. All three described scaling techniques can be integrated as the relevant methodological steps within a complex multi-source approach. We present this concept of combining numerous optical remote sensing data and methods to generate inputs for ecosystem process models.

Hurricane Katrina as Observed by NASA's Spaceborne Atmospheric Infrared Sounder (AIRS)

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site] Figure 1: click on image for larger AIRS microwave image

At 1:30 a.m. local time this morning, the remnants of (now Tropical Depression) Katrina were centered on the Mississippi-Tennessee border. This microwave image from the Atmospheric Infrared Sounder instrument on NASA's Aqua spacecrat shows that the area of most intense precipitation was concentrated to the north of the center of activity.

The infrared image shows how the storms look through an AIRS Infrared window channel. Window channels measure the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures are associated with high, cold cloud tops that make up the top of the hurricane. The infrared signal does not penetrate through clouds, so the purple color indicates the cool cloud tops of the storm. In cloud-free areas, the infrared signal is retrieved at the Earth's surface, revealing warmer temperatures. Cooler areas are pushing to purple and warmer areas are pushing to red.

The microwave image (figure 1) reveals where the heaviest precipitation in the hurricane is taking place. The blue areas within the storm show the location of this heavy precipitation. Blue areas outside of the storm where there are moderate or no clouds are where the cold (in the microwave sense) sea surface shines through.

The Atmospheric Infrared Sounder Experiment, with its visible, infrared, and microwave detectors, provides a three-dimensional look at Earth's weather. Working in tandem, the three instruments can make simultaneous observations all the way down to the Earth's surface, even in the presence of heavy clouds. With more than 2,000 channels sensing different regions of the atmosphere, the system creates a global, 3-D map of atmospheric temperature and humidity and provides information on clouds, greenhouse gases, and many other atmospheric phenomena. The AIRS Infrared Sounder Experiment flies onboard NASA's Aqua spacecraft and is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., under contract to NASA. JPL is a division of the California Institute of Technology in Pasadena.

High-power THz to IR emission by femtosecond laser irradiation of random 2D metallic nanostructures.

PubMed

Zhang, Liangliang; Mu, Kaijun; Zhou, Yunsong; Wang, Hai; Zhang, Cunlin; Zhang, X-C

2015-07-24

Terahertz (THz) spectroscopic sensing and imaging has identified its potentials in a number of areas such as standoff security screening at portals, explosive detection at battle fields, bio-medical research, and so on. With these needs, the development of an intense and broadband THz source has been a focus of THz research. In this work, we report an intense (~10 mW) and ultra-broadband (~150 THz) THz to infrared (IR) source with a Gaussian wavefront, emitted from nano-pore-structured metallic thin films with femtosecond laser pulse excitation. The underlying mechanism has been proposed as thermal radiation. In addition, an intense coherent THz signal was generated through the optical rectification process simultaneously with the strong thermal signal. This unique feature opens up new avenues in biomedical research.

The research of road and vehicle information extraction algorithm based on high resolution remote sensing image

NASA Astrophysics Data System (ADS)

Zhou, Tingting; Gu, Lingjia; Ren, Ruizhi; Cao, Qiong

2016-09-01

With the rapid development of remote sensing technology, the spatial resolution and temporal resolution of satellite imagery also have a huge increase. Meanwhile, High-spatial-resolution images are becoming increasingly popular for commercial applications. The remote sensing image technology has broad application prospects in intelligent traffic. Compared with traditional traffic information collection methods, vehicle information extraction using high-resolution remote sensing image has the advantages of high resolution and wide coverage. This has great guiding significance to urban planning, transportation management, travel route choice and so on. Firstly, this paper preprocessed the acquired high-resolution multi-spectral and panchromatic remote sensing images. After that, on the one hand, in order to get the optimal thresholding for image segmentation, histogram equalization and linear enhancement technologies were applied into the preprocessing results. On the other hand, considering distribution characteristics of road, the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to suppress water and vegetation information of preprocessing results. Then, the above two processing result were combined. Finally, the geometric characteristics were used to completed road information extraction. The road vector extracted was used to limit the target vehicle area. Target vehicle extraction was divided into bright vehicles extraction and dark vehicles extraction. Eventually, the extraction results of the two kinds of vehicles were combined to get the final results. The experiment results demonstrated that the proposed algorithm has a high precision for the vehicle information extraction for different high resolution remote sensing images. Among these results, the average fault detection rate was about 5.36%, the average residual rate was about 13.60% and the average accuracy was approximately 91.26%.

Few-mode optical fiber based simultaneously distributed curvature and temperature sensing.

PubMed

Wu, Hao; Tang, Ming; Wang, Meng; Zhao, Can; Zhao, Zhiyong; Wang, Ruoxu; Liao, Ruolin; Fu, Songnian; Yang, Chen; Tong, Weijun; Shum, Perry Ping; Liu, Deming

2017-05-29

The few-mode fiber (FMF) based Brillouin sensing operated in quasi-single mode (QSM) has been reported to achieve the distributed curvature measurement by monitoring the bend-induced strain variation. However, its practicality is limited by the inherent temperature-strain cross-sensitivity of Brillouin sensors. Here we proposed and experimentally demonstrated an approach for simultaneously distributed curvature and temperature sensing, which exploits a hybrid QSM operated Raman-Brillouin system in FMFs. Thanks to the larger spot size of the fundamental mode in the FMF, the Brillouin frequency shift change of the FMF is used for curvature estimation while the temperature variation is alleviated through Raman signals with the enhanced signal-to-noise ratio (SNR). Within 2 minutes measuring time, a 1.5 m spatial resolution is achieved along a 2 km FMF. The worst resolution of the square of fiber curvature is 0.333 cm -2 while the temperature resolution is 1.301 °C at the end of fiber.

Factors Regarding a Sense of Belonging on a University Campus: Affects on the Success of African American Male Students

ERIC Educational Resources Information Center

Addo-Yobo, Festus

2013-01-01

This dissertation examines the relationship of African American male undergraduate students from the context of one academic institution in the southwest border region of the United States. It explores the aspect of a sense of belonging on this particular university campus. The multiple mixed simultaneous study was conducted through the…