Science.gov

Sample records for pixel space convolution

  1. Fast convolution with free-space Green's functions

    NASA Astrophysics Data System (ADS)

    Vico, Felipe; Greengard, Leslie; Ferrando, Miguel

    2016-10-01

    We introduce a fast algorithm for computing volume potentials - that is, the convolution of a translation invariant, free-space Green's function with a compactly supported source distribution defined on a uniform grid. The algorithm relies on regularizing the Fourier transform of the Green's function by cutting off the interaction in physical space beyond the domain of interest. This permits the straightforward application of trapezoidal quadrature and the standard FFT, with superalgebraic convergence for smooth data. Moreover, the method can be interpreted as employing a Nystrom discretization of the corresponding integral operator, with matrix entries which can be obtained explicitly and rapidly. This is of use in the design of preconditioners or fast direct solvers for a variety of volume integral equations. The method proposed permits the computation of any derivative of the potential, at the cost of an additional FFT.

  2. Classification of Urban Aerial Data Based on Pixel Labelling with Deep Convolutional Neural Networks and Logistic Regression

    NASA Astrophysics Data System (ADS)

    Yao, W.; Poleswki, P.; Krzystek, P.

    2016-06-01

    The recent success of deep convolutional neural networks (CNN) on a large number of applications can be attributed to large amounts of available training data and increasing computing power. In this paper, a semantic pixel labelling scheme for urban areas using multi-resolution CNN and hand-crafted spatial-spectral features of airborne remotely sensed data is presented. Both CNN and hand-crafted features are applied to image/DSM patches to produce per-pixel class probabilities with a L1-norm regularized logistical regression classifier. The evidence theory infers a degree of belief for pixel labelling from different sources to smooth regions by handling the conflicts present in the both classifiers while reducing the uncertainty. The aerial data used in this study were provided by ISPRS as benchmark datasets for 2D semantic labelling tasks in urban areas, which consists of two data sources from LiDAR and color infrared camera. The test sites are parts of a city in Germany which is assumed to consist of typical object classes including impervious surfaces, trees, buildings, low vegetation, vehicles and clutter. The evaluation is based on the computation of pixel-based confusion matrices by random sampling. The performance of the strategy with respect to scene characteristics and method combination strategies is analyzed and discussed. The competitive classification accuracy could be not only explained by the nature of input data sources: e.g. the above-ground height of nDSM highlight the vertical dimension of houses, trees even cars and the nearinfrared spectrum indicates vegetation, but also attributed to decision-level fusion of CNN's texture-based approach with multichannel spatial-spectral hand-crafted features based on the evidence combination theory.

  3. convolve_image.pro: Common-Resolution Convolution Kernels for Space- and Ground-Based Telescopes

    NASA Astrophysics Data System (ADS)

    Aniano, Gonzalo J.

    2014-01-01

    The IDL package convolve_image.pro transforms images between different instrumental point spread functions (PSFs). It can load an image file and corresponding kernel and return the convolved image, thus preserving the colors of the astronomical sources. Convolution kernels are available for images from Spitzer (IRAC MIPS), Herschel (PACS SPIRE), GALEX (FUV NUV), WISE (W1 - W4), Optical PSFs (multi- Gaussian and Moffat functions), and Gaussian PSFs; they allow the study of the Spectral Energy Distribution (SED) of extended objects and preserve the characteristic SED in each pixel.

  4. A semiconductor radiation imaging pixel detector for space radiation dosimetry.

    PubMed

    Kroupa, Martin; Bahadori, Amir; Campbell-Ricketts, Thomas; Empl, Anton; Hoang, Son Minh; Idarraga-Munoz, John; Rios, Ryan; Semones, Edward; Stoffle, Nicholas; Tlustos, Lukas; Turecek, Daniel; Pinsky, Lawrence

    2015-07-01

    Progress in the development of high-performance semiconductor radiation imaging pixel detectors based on technologies developed for use in high-energy physics applications has enabled the development of a completely new generation of compact low-power active dosimeters and area monitors for use in space radiation environments. Such detectors can provide real-time information concerning radiation exposure, along with detailed analysis of the individual particles incident on the active medium. Recent results from the deployment of detectors based on the Timepix from the CERN-based Medipix2 Collaboration on the International Space Station (ISS) are reviewed, along with a glimpse of developments to come. Preliminary results from Orion MPCV Exploration Flight Test 1 are also presented.

  5. Compressed convolution

    NASA Astrophysics Data System (ADS)

    Elsner, Franz; Wandelt, Benjamin D.

    2014-01-01

    We introduce the concept of compressed convolution, a technique to convolve a given data set with a large number of non-orthogonal kernels. In typical applications our technique drastically reduces the effective number of computations. The new method is applicable to convolutions with symmetric and asymmetric kernels and can be easily controlled for an optimal trade-off between speed and accuracy. It is based on linear compression of the collection of kernels into a small number of coefficients in an optimal eigenbasis. The final result can then be decompressed in constant time for each desired convolved output. The method is fully general and suitable for a wide variety of problems. We give explicit examples in the context of simulation challenges for upcoming multi-kilo-detector cosmic microwave background (CMB) missions. For a CMB experiment with detectors with similar beam properties, we demonstrate that the algorithm can decrease the costs of beam convolution by two to three orders of magnitude with negligible loss of accuracy. Likewise, it has the potential to allow the reduction of disk space required to store signal simulations by a similar amount. Applications in other areas of astrophysics and beyond are optimal searches for a large number of templates in noisy data, e.g. from a parametrized family of gravitational wave templates; or calculating convolutions with highly overcomplete wavelet dictionaries, e.g. in methods designed to uncover sparse signal representations.

  6. Pixel detectors for x-ray imaging spectroscopy in space

    NASA Astrophysics Data System (ADS)

    Treis, J.; Andritschke, R.; Hartmann, R.; Herrmann, S.; Holl, P.; Lauf, T.; Lechner, P.; Lutz, G.; Meidinger, N.; Porro, M.; Richter, R. H.; Schopper, F.; Soltau, H.; Strüder, L.

    2009-03-01

    Pixelated semiconductor detectors for X-ray imaging spectroscopy are foreseen as key components of the payload of various future space missions exploring the x-ray sky. Located on the platform of the new Spectrum-Roentgen-Gamma satellite, the eROSITA (extended Roentgen Survey with an Imaging Telescope Array) instrument will perform an imaging all-sky survey up to an X-ray energy of 10 keV with unprecedented spectral and angular resolution. The instrument will consist of seven parallel oriented mirror modules each having its own pnCCD camera in the focus. The satellite born X-ray observatory SIMBOL-X will be the first mission to use formation-flying techniques to implement an X-ray telescope with an unprecedented focal length of around 20 m. The detector instrumentation consists of separate high- and low energy detectors, a monolithic 128 × 128 DEPFET macropixel array and a pixellated CdZTe detector respectively, making energy band between 0.5 to 80 keV accessible. A similar concept is proposed for the next generation X-ray observatory IXO. Finally, the MIXS (Mercury Imaging X-ray Spectrometer) instrument on the European Mercury exploration mission BepiColombo will use DEPFET macropixel arrays together with a small X-ray telescope to perform a spatially resolved planetary XRF analysis of Mercury's crust. Here, the mission concepts and their scientific targets are briefly discussed, and the resulting requirements on the detector devices together with the implementation strategies are shown.

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

    NASA Technical Reports Server (NTRS)

    Baxter, Lisa C.; Coggins, James M.

    1991-01-01

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

  8. Smart-Pixel Array Processors Based on Optimal Cellular Neural Networks for Space Sensor Applications

    NASA Technical Reports Server (NTRS)

    Fang, Wai-Chi; Sheu, Bing J.; Venus, Holger; Sandau, Rainer

    1997-01-01

    A smart-pixel cellular neural network (CNN) with hardware annealing capability, digitally programmable synaptic weights, and multisensor parallel interface has been under development for advanced space sensor applications. The smart-pixel CNN architecture is a programmable multi-dimensional array of optoelectronic neurons which are locally connected with their local neurons and associated active-pixel sensors. Integration of the neuroprocessor in each processor node of a scalable multiprocessor system offers orders-of-magnitude computing performance enhancements for on-board real-time intelligent multisensor processing and control tasks of advanced small satellites. The smart-pixel CNN operation theory, architecture, design and implementation, and system applications are investigated in detail. The VLSI (Very Large Scale Integration) implementation feasibility was illustrated by a prototype smart-pixel 5x5 neuroprocessor array chip of active dimensions 1380 micron x 746 micron in a 2-micron CMOS technology.

  9. HUBBLE SPACE TELESCOPE PIXEL ANALYSIS OF THE INTERACTING S0 GALAXY NGC 5195 (M51B)

    SciTech Connect

    Lee, Joon Hyeop; Kim, Sang Chul; Ree, Chang Hee; Kim, Minjin; Jeong, Hyunjin; Lee, Jong Chul; Kyeong, Jaemann E-mail: sckim@kasi.re.kr E-mail: mkim@kasi.re.kr E-mail: jclee@kasi.re.kr

    2012-08-01

    We report the properties of the interacting S0 galaxy NGC 5195 (M51B), revealed in a pixel analysis using the Hubble Space Telescope/Advanced Camera for Surveys images in the F435W, F555W, and F814W (BVI) bands. We analyze the pixel color-magnitude diagram (pCMD) of NGC 5195, focusing on the properties of its red and blue pixel sequences and the difference from the pCMD of NGC 5194 (M51A; the spiral galaxy interacting with NGC 5195). The red pixel sequence of NGC 5195 is redder than that of NGC 5194, which corresponds to the difference in the dust optical depth of 2 < {Delta}{tau}{sub V} < 4 at fixed age and metallicity. The blue pixel sequence of NGC 5195 is very weak and spatially corresponds to the tidal bridge between the two interacting galaxies. This implies that the blue pixel sequence is not an ordinary feature in the pCMD of an early-type galaxy, but that it is a transient feature of star formation caused by the galaxy-galaxy interaction. We also find a difference in the shapes of the red pixel sequences on the pixel color-color diagrams (pCCDs) of NGC 5194 and NGC 5195. We investigate the spatial distributions of the pCCD-based pixel stellar populations. The young population fraction in the tidal bridge area is larger than that in other areas by a factor >15. Along the tidal bridge, young populations seem to be clumped particularly at the middle point of the bridge. On the other hand, the dusty population shows a relatively wide distribution between the tidal bridge and the center of NGC 5195.

  10. Autonomous Sub-Pixel Satellite Track Endpoint Determination for Space Based Images

    SciTech Connect

    Simms, L M

    2011-03-07

    An algorithm for determining satellite track endpoints with sub-pixel resolution in spaced-based images is presented. The algorithm allows for significant curvature in the imaged track due to rotation of the spacecraft capturing the image. The motivation behind the subpixel endpoint determination is first presented, followed by a description of the methodology used. Results from running the algorithm on real ground-based and simulated spaced-based images are shown to highlight its effectiveness.

  11. H4RG Near-IR Detectors with 10 micron pixels for WFIRST and Space Astrophysics

    NASA Astrophysics Data System (ADS)

    Kruk, Jeffrey W.; Rauscher, B. J.

    2014-01-01

    Hybrid sensor chip assemblies (SCAs) employing HgCdTe photo-diode arrays integrated with CMOS read-out integrated circuits (ROICs) have become the detector of choice for many cutting-edge ground-based and space-based astronomical instruments operating at near infrared wavelengths. 2Kx2K arrays of 18-micron pixels are in use at many ground-based observatories and will fly on JWST and Euclid later this decade. The Wide-Field Infra-Red Survey Telescope (WFIRST) mission, which will survey large areas of the sky with reasonably-fine sampling, is extending these prior designs by developing 4Kx4K HgCdTe NIR hybrid detectors with 10 micron pixels. These will provide four times as many pixels as the current 2Kx2K detectors in a package that is only slightly larger. Four prototype 4Kx4K devices with conservative pixel designs were produced in 2011; these devices met many though not all WFIRST performance requirements. A Strategic Astrophysics Technology proposal was submitted to further the development of these detectors. This poster describes the technology development plan, progress made in the first year of the program, and plans for the future.

  12. Soccer player recognition by pixel classification in a hybrid color space

    NASA Astrophysics Data System (ADS)

    Vandenbroucke, Nicolas; Macaire, Ludovic; Postaire, Jack-Gerard

    1997-08-01

    Soccer is a very popular sport all over the world, Coaches and sport commentators need accurate information about soccer games, especially about the players behavior. These information can be gathered by inspectors who watch the soccer match and report manually the actions of the players involved in the principal phases of the game. Generally, these inspectors focus their attention on the few players standing near the ball and don't report about the motion of all the other players. So it seems desirable to design a system which automatically tracks all the players in real- time. That's why we propose to automatically track each player through the successive color images of the sequences acquired by a fixed color camera. Each player which is present in the image, is modelized by an active contour model or snake. When, during the soccer match, a player is hidden by another, the snakes which track these two players merge. So, it becomes impossible to track the players, except if the snakes are interactively re-initialized. Fortunately, in most cases, the two players don't belong to the same team. That is why we present an algorithm which recognizes the teams of the players by pixels representing the soccer ground which must be withdrawn before considering the players themselves. To eliminate these pixels, the color characteristics of the ground are determined interactively. In a second step, dealing with windows containing only one player of one team, the color features which yield the best discrimination between the two teams are selected. Thanks to these color features, the pixels associated to the players of the two teams form two separated clusters into a color space. In fact, there are many color representation systems and it's interesting to evaluate the features which provide the best separation between the two classes of pixels according to the players soccer suit. Finally, the classification process for image segmentation is based on the three most

  13. Verification of Dosimetry Measurements with Timepix Pixel Detectors for Space Applications

    NASA Technical Reports Server (NTRS)

    Kroupa, M.; Pinsky, L. S.; Idarraga-Munoz, J.; Hoang, S. M.; Semones, E.; Bahadori, A.; Stoffle, N.; Rios, R.; Vykydal, Z.; Jakubek, J.; Pospisil, S.; Turecek, D.; Kitamura, H.

    2014-01-01

    The current capabilities of modern pixel-detector technology has provided the possibility to design a new generation of radiation monitors. Timepix detectors are semiconductor pixel detectors based on a hybrid configuration. As such, the read-out chip can be used with different types and thicknesses of sensors. For space radiation dosimetry applications, Timepix devices with 300 and 500 microns thick silicon sensors have been used by a collaboration between NASA and University of Houston to explore their performance. For that purpose, an extensive evaluation of the response of Timepix for such applications has been performed. Timepix-based devices were tested in many different environments both at ground-based accelerator facilities such as HIMAC (Heavy Ion Medical Accelerator in Chiba, Japan), and at NSRL (NASA Space Radiation Laboratory at Brookhaven National Laboratory in Upton, NY), as well as in space on board of the International Space Station (ISS). These tests have included a wide range of the particle types and energies, from protons through iron nuclei. The results have been compared both with other devices and theoretical values. This effort has demonstrated that Timepix-based detectors are exceptionally capable at providing accurate dosimetry measurements in this application as verified by the confirming correspondence with the other accepted techniques.

  14. Carotenoid pixels characterization under color space tests and RGB formulas for mesocarp of mango's fruits cultivars

    NASA Astrophysics Data System (ADS)

    Hammad, Ahmed Yahya; Kassim, Farid Saad Eid Saad

    2010-01-01

    This study experimented the pulp (mesocarp) of fourteen cultivars were healthy ripe of Mango fruits (Mangifera indica L.) selected after picking from Mango Spp. namely Taimour [Ta], Dabsha [Da], Aromanis [Ar], Zebda [Ze], Fagri Kelan [Fa], Alphonse [Al], Bulbek heart [Bu], Hindi- Sinnara [Hi], Compania [Co], Langra [La], Mestikawi [Me], Ewais [Ew], Montakhab El Kanater [Mo] and Mabroka [Ma] . Under seven color space tests included (RGB: Red, Green and Blue), (CMY: Cyan, Magenta and Yellow), (CMY: Cyan, Magenta and Yellow), (HSL: Hue, Saturation and Lightness), (CMYK%: Cyan%, Magenta%, Yellow% and Black%), (HSV: Hue, Saturation and Value), (HºSB%: Hueº, Saturation% and Brightness%) and (Lab). (CMY: Cyan, Magenta and Yellow), (HSL: Hue, Saturation and Lightness), (CMYK%: Cyan%, Magenta%, Yellow% and Black%), (HSV: Hue, Saturation and Value), (HºSB%: Hueº, Saturation% and Brightness%) and (Lab). Addition, nine formula of color space tests included (sRGB 0÷1, CMY, CMYK, XYZ, CIE-L*ab, CIE-L*CH, CIE-L*uv, Yxy and Hunter-Lab) and (RGB 0÷FF/hex triplet) and Carotenoid Pixels Scale. Utilizing digital color photographs as tool for obtainment the natural color information for each cultivar then the result expounded with chemical pigment estimations. Our location study in the visual yellow to orange color degrees from the visible color of electromagnetic spectrum in wavelength between (~570 to 620) nm and frequency between (~480 to 530) THz. The results found carotene very strong influence in band Red while chlorophyll (a & b) was very lower subsequently, the values in band Green was depressed. Meanwhile, the general ratios percentage for carotenoid pixels in bands Red, Green and Blue were 50%, 39% and 11% as orderliness opposite the ratios percentage for carotene, chlorophyll a and chlorophyll b which were 63%, 22% and 16% approximately. According to that the pigments influence in all color space tests and RGB formulas. Band Yellow% in color test (CMYK%) as signature

  15. HUBBLE SPACE TELESCOPE PIXEL ANALYSIS OF THE INTERACTING FACE-ON SPIRAL GALAXY NGC 5194 (M51A)

    SciTech Connect

    Lee, Joon Hyeop; Kim, Sang Chul; Park, Hong Soo; Ree, Chang Hee; Kyeong, Jaemann; Chung, Jiwon E-mail: sckim@kasi.re.kr E-mail: chr@kasi.re.kr E-mail: jiwon@kasi.re.kr

    2011-10-10

    A pixel analysis is carried out on the interacting face-on spiral galaxy NGC 5194 (M51A), using the Hubble Space Telescope (HST)/Advanced Camera for Surveys (ACS) images in the F435W, F555W, and F814W (BVI) bands. After 4 x 4 binning of the HST/ACS images to secure a sufficient signal-to-noise ratio for each pixel, we derive several quantities describing the pixel color-magnitude diagram (pCMD) of NGC 5194: blue/red color cut, red pixel sequence parameters, blue pixel sequence parameters, and blue-to-red pixel ratio. The red sequence pixels are mostly older than 1 Gyr, while the blue sequence pixels are mostly younger than 1 Gyr, in their luminosity-weighted mean stellar ages. The color variation in the red pixel sequence from V = 20 mag arcsec{sup -2} to V = 17 mag arcsec{sup -2} corresponds to a metallicity variation of {Delta}[Fe/H] {approx}2 or an optical depth variation of {Delta}{tau}{sub V} {approx} 4 by dust, but the actual sequence is thought to originate from the combination of those two effects. At V < 20 mag arcsec{sup -2}, the color variation in the blue pixel sequence corresponds to an age variation from 5 Myr to 300 Myr under the assumption of solar metallicity and {tau}{sub V} = 1. To investigate the spatial distributions of stellar populations, we divide pixel stellar populations using the pixel color-color diagram and population synthesis models. As a result, we find that the pixel population distributions across the spiral arms agree with a compressing process by spiral density waves: dense dust {yields} newly formed stars. The tidal interaction between NGC 5194 and NGC 5195 appears to enhance the star formation at the tidal bridge connecting the two galaxies. We find that the pixels corresponding to the central active galactic nucleus (AGN) area of NGC 5194 show a tight sequence at the bright-end of the pCMD, which are in the region of R {approx} 100 pc and may be a photometric indicator of AGN properties.

  16. From Single Pixels to Many Megapixels: Progress in Astronomical Infrared Imaging from Space-borne Telescopes

    NASA Astrophysics Data System (ADS)

    Pipher, Judith

    2017-01-01

    In the 1960s, rocket infrared astronomy was in its infancy. The Cornell group planned a succession of rocket launches of a small cryogenically cooled telescope above much of the atmosphere. Cornell graduate students were tasked with hand-making single pixel detectors for the focal plane at wavelengths ranging from ~5 microns to just short of 1 mm. “Images” could only be constructed from scans of objects such as HII regions/giant molecular clouds, the galactic center, and of diffuse radiation from the various IR backgrounds. IRAS and COBE, followed by the KAO utilized ever more sensitive single IR detectors, and revolutionized our understanding of the Universe. The first IR arrays came onto the scene in the early 1970s - and in 1983 several experiments for the space mission SIRTF (later named Spitzer Space Telescope following launch 20 years later) were selected, all boasting (relatively small) arrays. Europe’s ISO and Herschel also employed arrays to good advantage, as has SOFIA, and now, many-megapixel IR arrays are sufficiently well-developed for upcoming space missions.

  17. Analysis and Optimization of the Performance of a Convolutionally Encoded Deep-Space Link in the Presence of Spacecraft Oscillator Phase Noise

    NASA Astrophysics Data System (ADS)

    Shambayati, S.

    1999-10-01

    In order to reduce the cost of deep-space missions, NASA is exploring the possibility of using new, cheaper technologies. Among these is the possibility of replacing ultra-stable oscillators (USOs) onboard the spacecraft with oscillators with measurable phase noise. In addition, it is proposed that these spacecraft use higher 32-GHz (Ka-band) radio frequencies in order to save mass. In this article, the performance of a convolutionally encoded deep-space link using non-USO-type oscillators onboard the spacecraft at Ka-band is analyzed. It is shown that the ground-receiver tracking-loop bandwidth settings need to be optimized and that, by selecting an oscillator with good phase-noise characteristics, the minimum required power onboard the spacecraft could be reduced by as much as 10 dB.

  18. Comparison of rate one-half, equivalent constraint length 24, binary convolutional codes for use with sequential decoding on the deep-space channel

    NASA Technical Reports Server (NTRS)

    Massey, J. L.

    1976-01-01

    Virtually all previously-suggested rate 1/2 binary convolutional codes with KE = 24 are compared. Their distance properties are given; and their performance, both in computation and in error probability, with sequential decoding on the deep-space channel is determined by simulation. Recommendations are made both for the choice of a specific KE = 24 code as well as for codes to be included in future coding standards for the deep-space channel. A new result given in this report is a method for determining the statistical significance of error probability data when the error probability is so small that it is not feasible to perform enough decoding simulations to obtain more than a very small number of decoding errors.

  19. Signal dependence of inter-pixel capacitance in hybridized HgCdTe H2RG arrays for use in James Webb space telescope's NIRcam

    NASA Astrophysics Data System (ADS)

    Donlon, Kevan; Ninkov, Zoran; Baum, Stefi

    2016-08-01

    Interpixel capacitance (IPC) is a deterministic electronic coupling by which signal generated in one pixel is measured in neighboring pixels. Examination of dark frames from test NIRcam arrays corroborates earlier results and simulations illustrating a signal dependent coupling. When the signal on an individual pixel is larger, the fractional coupling to nearest neighbors is lesser than when the signal is lower. Frames from test arrays indicate a drop in average coupling from approximately 1.0% at low signals down to approximately 0.65% at high signals depending on the particular array in question. The photometric ramifications for this non-uniformity are not fully understood. This non-uniformity intro-duces a non-linearity in the current mathematical model for IPC coupling. IPC coupling has been mathematically formalized as convolution by a blur kernel. Signal dependence requires that the blur kernel be locally defined as a function of signal intensity. Through application of a signal dependent coupling kernel, the IPC coupling can be modeled computationally. This method allows for simultaneous knowledge of the intrinsic parameters of the image scene, the result of applying a constant IPC, and the result of a signal dependent IPC. In the age of sub-pixel precision in astronomy these effects must be properly understood and accounted for in order for the data to accurately represent the object of observation. Implementation of this method is done through python scripted processing of images. The introduction of IPC into simulated frames is accomplished through convolution of the image with a blur kernel whose parameters are themselves locally defined functions of the image. These techniques can be used to enhance the data processing pipeline for NIRcam.

  20. Early breast tumor and late SARS detections using space-variant multispectral infrared imaging at a single pixel

    NASA Astrophysics Data System (ADS)

    Szu, Harold H.; Buss, James R.; Kopriva, Ivica

    2004-04-01

    We proposed the physics approach to solve a physical inverse problem, namely to choose the unique equilibrium solution (at the minimum free energy: H= E - ToS, including the Wiener, l.m.s E, and ICA, Max S, as special cases). The "unsupervised classification" presumes that required information must be learned and derived directly and solely from the data alone, in consistence with the classical Duda-Hart ATR definition of the "unlabelled data". Such truly unsupervised methodology is presented for space-variant imaging processing for a single pixel in the real world case of remote sensing, early tumor detections and SARS. The indeterminacy of the multiple solutions of the inverse problem is regulated or selected by means of the absolute minimum of isothermal free energy as the ground truth of local equilibrium condition at the single-pixel foot print.

  1. Human Parsing with Contextualized Convolutional Neural Network.

    PubMed

    Liang, Xiaodan; Xu, Chunyan; Shen, Xiaohui; Yang, Jianchao; Tang, Jinhui; Lin, Liang; Yan, Shuicheng

    2016-03-02

    In this work, we address the human parsing task with a novel Contextualized Convolutional Neural Network (Co-CNN) architecture, which well integrates the cross-layer context, global image-level context, semantic edge context, within-super-pixel context and cross-super-pixel neighborhood context into a unified network. Given an input human image, Co-CNN produces the pixel-wise categorization in an end-to-end way. First, the cross-layer context is captured by our basic local-to-global-to-local structure, which hierarchically combines the global semantic information and the local fine details across different convolutional layers. Second, the global image-level label prediction is used as an auxiliary objective in the intermediate layer of the Co-CNN, and its outputs are further used for guiding the feature learning in subsequent convolutional layers to leverage the global imagelevel context. Third, semantic edge context is further incorporated into Co-CNN, where the high-level semantic boundaries are leveraged to guide pixel-wise labeling. Finally, to further utilize the local super-pixel contexts, the within-super-pixel smoothing and cross-super-pixel neighbourhood voting are formulated as natural sub-components of the Co-CNN to achieve the local label consistency in both training and testing process. Comprehensive evaluations on two public datasets well demonstrate the significant superiority of our Co-CNN over other state-of-the-arts for human parsing. In particular, the F-1 score on the large dataset [1] reaches 81:72% by Co-CNN, significantly higher than 62:81% and 64:38% by the state-of-the-art algorithms, MCNN [2] and ATR [1], respectively. By utilizing our newly collected large dataset for training, our Co-CNN can achieve 85:36% in F-1 score.

  2. High-End CMOS Active Pixel Sensors For Space-Borne Imaging Instruments

    DTIC Science & Technology

    2005-07-13

    sur la technologie CCD, alors que les capteurs CMOS à pixel actifs (APS) ont des nombreux avantages pour des applications embarquées. Cette...Les capteurs optiques intégrés sont utilisés dans le domaine spatial dans un large éventail d’applications. Beaucoup d’entres elles reposent toujours...publication présente des capteurs CMOS hautes performances d’aujourd’hui et met en lumière leurs avantages par rapport à leur équivalent CCD. Ces capteurs

  3. Using hybrid GPU/CPU kernel splitting to accelerate spherical convolutions

    NASA Astrophysics Data System (ADS)

    Sutter, P. M.; Wandelt, B. D.; Elsner, F.

    2015-06-01

    We present a general method for accelerating by more than an order of magnitude the convolution of pixelated functions on the sphere with a radially-symmetric kernel. Our method splits the kernel into a compact real-space component and a compact spherical harmonic space component. These components can then be convolved in parallel using an inexpensive commodity GPU and a CPU. We provide models for the computational cost of both real-space and Fourier space convolutions and an estimate for the approximation error. Using these models we can determine the optimum split that minimizes the wall clock time for the convolution while satisfying the desired error bounds. We apply this technique to the problem of simulating a cosmic microwave background (CMB) anisotropy sky map at the resolution typical of the high resolution maps produced by the Planck mission. For the main Planck CMB science channels we achieve a speedup of over a factor of ten, assuming an acceptable fractional rms error of order 10-5 in the power spectrum of the output map.

  4. ENGage: The use of space and pixel art for increasing primary school children's interest in science, technology, engineering and mathematics

    NASA Astrophysics Data System (ADS)

    Roberts, Simon J.

    2014-01-01

    The Faculty of Engineering at The University of Nottingham, UK, has developed interdisciplinary, hands-on workshops for primary schools that introduce space technology, its relevance to everyday life and the importance of science, technology, engineering and maths. The workshop activities for 7-11 year olds highlight the roles that space and satellite technology play in observing and monitoring the Earth's biosphere as well as being vital to communications in the modern digital world. The programme also provides links to 'how science works', the environment and citizenship and uses pixel art through the medium of digital photography to demonstrate the importance of maths in a novel and unconventional manner. The interactive programme of activities provides learners with an opportunity to meet 'real' scientists and engineers, with one of the key messages from the day being that anyone can become involved in science and engineering whatever their ability or subject of interest. The methodology introduces the role of scientists and engineers using space technology themes, but it could easily be adapted for use with any inspirational topic. Analysis of learners' perceptions of science, technology, engineering and maths before and after participating in ENGage showed very positive and significant changes in their attitudes to these subjects and an increase in the number of children thinking they would be interested and capable in pursuing a career in science and engineering. This paper provides an overview of the activities, the methodology, the evaluation process and results.

  5. The analysis of convolutional codes via the extended Smith algorithm

    NASA Technical Reports Server (NTRS)

    Mceliece, R. J.; Onyszchuk, I.

    1993-01-01

    Convolutional codes have been the central part of most error-control systems in deep-space communication for many years. Almost all such applications, however, have used the restricted class of (n,1), also known as 'rate 1/n,' convolutional codes. The more general class of (n,k) convolutional codes contains many potentially useful codes, but their algebraic theory is difficult and has proved to be a stumbling block in the evolution of convolutional coding systems. In this article, the situation is improved by describing a set of practical algorithms for computing certain basic things about a convolutional code (among them the degree, the Forney indices, a minimal generator matrix, and a parity-check matrix), which are usually needed before a system using the code can be built. The approach is based on the classic Forney theory for convolutional codes, together with the extended Smith algorithm for polynomial matrices, which is introduced in this article.

  6. Correction of defective pixels for medical and space imagers based on Ising Theory

    NASA Astrophysics Data System (ADS)

    Cohen, Eliahu; Shnitser, Moriel; Avraham, Tsvika; Hadar, Ofer

    2014-09-01

    We propose novel models for image restoration based on statistical physics. We investigate the affinity between these fields and describe a framework from which interesting denoising algorithms can be derived: Ising-like models and simulated annealing techniques. When combined with known predictors such as Median and LOCO-I, these models become even more effective. In order to further examine the proposed models we apply them to two important problems: (i) Digital Cameras in space damaged from cosmic radiation. (ii) Ultrasonic medical devices damaged from speckle noise. The results, as well as benchmark and comparisons, suggest in most of the cases a significant gain in PSNR and SSIM in comparison to other filters.

  7. Development of a pixel sensor with fine space-time resolution based on SOI technology for the ILC vertex detector

    NASA Astrophysics Data System (ADS)

    Ono, Shun; Togawa, Manabu; Tsuji, Ryoji; Mori, Teppei; Yamada, Miho; Arai, Yasuo; Tsuboyama, Toru; Hanagaki, Kazunori

    2017-02-01

    We have been developing a new monolithic pixel sensor with silicon-on-insulator (SOI) technology for the International Linear Collider (ILC) vertex detector system. The SOI monolithic pixel detector is realized using standard CMOS circuits fabricated on a fully depleted sensor layer. The new SOI sensor SOFIST can store both the position and timing information of charged particles in each 20×20 μm2 pixel. The position resolution is further improved by the position weighted with the charges spread to multiple pixels. The pixel also records the hit timing with an embedded time-stamp circuit. The sensor chip has column-parallel analog-to-digital conversion (ADC) circuits and zero-suppression logic for high-speed data readout. We are designing and evaluating some prototype sensor chips for optimizing and minimizing the pixel circuit.

  8. 4K×4K format 10μm pixel pitch H4RG-10 hybrid CMOS silicon visible focal plane array for space astronomy

    NASA Astrophysics Data System (ADS)

    Bai, Yibin; Tennant, William; Anglin, Selmer; Wong, Andre; Farris, Mark; Xu, Min; Holland, Eric; Cooper, Donald; Hosack, Joseph; Ho, Kenneth; Sprafke, Thomas; Kopp, Robert; Starr, Brian; Blank, Richard; Beletic, James W.; Luppino, Gerard A.

    2012-07-01

    Teledyne’s silicon hybrid CMOS focal plane array technology has matured into a viable, high performance and high- TRL alternative to scientific CCD sensors for space-based applications in the UV-visible-NIR wavelengths. This paper presents the latest results from Teledyne’s low noise silicon hybrid CMOS visible focal place array produced in 4K×4K format with 10 μm pixel pitch. The H4RG-10 readout circuit retains all of the CMOS functionality (windowing, guide mode, reference pixels) and heritage of its highly successful predecessor (H2RG) developed for JWST, with additional features for improved performance. Combined with a silicon PIN detector layer, this technology is termed HyViSI™ (Hybrid Visible Silicon Imager). H4RG-10 HyViSI™ arrays achieve high pixel interconnectivity (<99.99%), low readout noise (<10 e- rms single CDS), low dark current (<0.5 e-/pixel/s at 193K), high quantum efficiency (<90% broadband), and large dynamic range (<13 bits). Pixel crosstalk and interpixel capacitance (IPC) have been predicted using detailed models of the hybrid structure and these predictions have been confirmed by measurements with Fe-55 Xray events and the single pixel reset technique. For a 100-micron thick detector, IPC of less than 3% and total pixel crosstalk of less than 7% have been achieved for the HyViSI™ H4RG-10. The H4RG-10 array is mounted on a lightweight silicon carbide (SiC) package and has been qualified to Technology Readiness Level 6 (TRL-6). As part of space qualification, the HyViSI™ H4RG-10 array passed radiation testing for low earth orbit (LEO) environment.

  9. Spatial-Spectral Classification Based on the Unsupervised Convolutional Sparse Auto-Encoder for Hyperspectral Remote Sensing Imagery

    NASA Astrophysics Data System (ADS)

    Han, Xiaobing; Zhong, Yanfei; Zhang, Liangpei

    2016-06-01

    Current hyperspectral remote sensing imagery spatial-spectral classification methods mainly consider concatenating the spectral information vectors and spatial information vectors together. However, the combined spatial-spectral information vectors may cause information loss and concatenation deficiency for the classification task. To efficiently represent the spatial-spectral feature information around the central pixel within a neighbourhood window, the unsupervised convolutional sparse auto-encoder (UCSAE) with window-in-window selection strategy is proposed in this paper. Window-in-window selection strategy selects the sub-window spatial-spectral information for the spatial-spectral feature learning and extraction with the sparse auto-encoder (SAE). Convolution mechanism is applied after the SAE feature extraction stage with the SAE features upon the larger outer window. The UCSAE algorithm was validated by two common hyperspectral imagery (HSI) datasets - Pavia University dataset and the Kennedy Space Centre (KSC) dataset, which shows an improvement over the traditional hyperspectral spatial-spectral classification methods.

  10. Astronomical Image Subtraction by Cross-Convolution

    NASA Astrophysics Data System (ADS)

    Yuan, Fang; Akerlof, Carl W.

    2008-04-01

    In recent years, there has been a proliferation of wide-field sky surveys to search for a variety of transient objects. Using relatively short focal lengths, the optics of these systems produce undersampled stellar images often marred by a variety of aberrations. As participants in such activities, we have developed a new algorithm for image subtraction that no longer requires high-quality reference images for comparison. The computational efficiency is comparable with similar procedures currently in use. The general technique is cross-convolution: two convolution kernels are generated to make a test image and a reference image separately transform to match as closely as possible. In analogy to the optimization technique for generating smoothing splines, the inclusion of an rms width penalty term constrains the diffusion of stellar images. In addition, by evaluating the convolution kernels on uniformly spaced subimages across the total area, these routines can accommodate point-spread functions that vary considerably across the focal plane.

  11. Non-Uniform Object-Space Pixelation (NUOP) for Penalized Maximum-Likelihood Image Reconstruction for a Single Photon Emission Microscope System

    PubMed Central

    Meng, L. J.; Li, Nan

    2016-01-01

    This paper presents a non-uniform object-space pixelation (NUOP) approach for image reconstruction using the penalized maximum likelihood methods. This method was developed for use with a single photon emission microscope (SPEM) system that offers an ultrahigh spatial resolution for a targeted local region inside mouse brain. In this approach, the object-space is divided with non-uniform pixel sizes, which are chosen adaptively based on object-dependent criteria. These include (a) some known characteristics of a target-region, (b) the associated Fisher Information that measures the weighted correlation between the responses of the system to gamma ray emissions occurred at different spatial locations, and (c) the linear distance from a given location to the target-region. In order to quantify the impact of this non-uniform pixelation approach on image quality, we used the Modified Uniform Cramer-Rao bound (MUCRB) to evaluate the local resolution-variance and bias-variance tradeoffs achievable with different pixelation strategies. As demonstrated in this paper, an efficient object-space pixelation could improve the speed of computation by 1–2 orders of magnitude, whilst maintaining an excellent reconstruction for the target-region. This improvement is crucial for making the SPEM system a practical imaging tool for mouse brain studies. The proposed method also allows rapid computation of the first and second order statistics of reconstructed images using analytical approximations, which is the key for the evaluation of several analytical system performance indices for system design and optimization.

  12. NUCLEI SEGMENTATION VIA SPARSITY CONSTRAINED CONVOLUTIONAL REGRESSION

    PubMed Central

    Zhou, Yin; Chang, Hang; Barner, Kenneth E.; Parvin, Bahram

    2017-01-01

    Automated profiling of nuclear architecture, in histology sections, can potentially help predict the clinical outcomes. However, the task is challenging as a result of nuclear pleomorphism and cellular states (e.g., cell fate, cell cycle), which are compounded by the batch effect (e.g., variations in fixation and staining). Present methods, for nuclear segmentation, are based on human-designed features that may not effectively capture intrinsic nuclear architecture. In this paper, we propose a novel approach, called sparsity constrained convolutional regression (SCCR), for nuclei segmentation. Specifically, given raw image patches and the corresponding annotated binary masks, our algorithm jointly learns a bank of convolutional filters and a sparse linear regressor, where the former is used for feature extraction, and the latter aims to produce a likelihood for each pixel being nuclear region or background. During classification, the pixel label is simply determined by a thresholding operation applied on the likelihood map. The method has been evaluated using the benchmark dataset collected from The Cancer Genome Atlas (TCGA). Experimental results demonstrate that our method outperforms traditional nuclei segmentation algorithms and is able to achieve competitive performance compared to the state-of-the-art algorithm built upon human-designed features with biological prior knowledge. PMID:28101301

  13. The time-space relationship of the data point (Pixels) of the thematic mapper and multispectral scanner or the myth of simultaneity

    NASA Technical Reports Server (NTRS)

    Gordon, F., Jr.

    1980-01-01

    A simplified explanation of the time space relationships among scanner pixels is presented. The examples of the multispectral scanner (MSS) on Landsats 1, 2, and 3 and the thematic mapper (TM) of Landsat D are used to describe the concept and degree of nonsimultaneity of scanning system data. The time aspects of scanner data acquisition and those parts of the MSS and TM systems related to that phenomena are addressed.

  14. PIXEL PUSHER

    NASA Technical Reports Server (NTRS)

    Stanfill, D. F.

    1994-01-01

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

  15. Two dimensional convolute integers for machine vision and image recognition

    NASA Technical Reports Server (NTRS)

    Edwards, Thomas R.

    1988-01-01

    Machine vision and image recognition require sophisticated image processing prior to the application of Artificial Intelligence. Two Dimensional Convolute Integer Technology is an innovative mathematical approach for addressing machine vision and image recognition. This new technology generates a family of digital operators for addressing optical images and related two dimensional data sets. The operators are regression generated, integer valued, zero phase shifting, convoluting, frequency sensitive, two dimensional low pass, high pass and band pass filters that are mathematically equivalent to surface fitted partial derivatives. These operators are applied non-recursively either as classical convolutions (replacement point values), interstitial point generators (bandwidth broadening or resolution enhancement), or as missing value calculators (compensation for dead array element values). These operators show frequency sensitive feature selection scale invariant properties. Such tasks as boundary/edge enhancement and noise or small size pixel disturbance removal can readily be accomplished. For feature selection tight band pass operators are essential. Results from test cases are given.

  16. Exploring the Hidden Structure of Astronomical Images: A "Pixelated" View of Solar System and Deep Space Features!

    ERIC Educational Resources Information Center

    Ward, R. Bruce; Sienkiewicz, Frank; Sadler, Philip; Antonucci, Paul; Miller, Jaimie

    2013-01-01

    We describe activities created to help student participants in Project ITEAMS (Innovative Technology-Enabled Astronomy for Middle Schools) develop a deeper understanding of picture elements (pixels), image creation, and analysis of the recorded data. ITEAMS is an out-of-school time (OST) program funded by the National Science Foundation (NSF) with…

  17. Convolutional coding techniques for data protection

    NASA Technical Reports Server (NTRS)

    Massey, J. L.

    1975-01-01

    Results of research on the use of convolutional codes in data communications are presented. Convolutional coding fundamentals are discussed along with modulation and coding interaction. Concatenated coding systems and data compression with convolutional codes are described.

  18. The effect of whitening transformation on pooling operations in convolutional autoencoders

    NASA Astrophysics Data System (ADS)

    Li, Zuhe; Fan, Yangyu; Liu, Weihua

    2015-12-01

    Convolutional autoencoders (CAEs) are unsupervised feature extractors for high-resolution images. In the pre-processing step, whitening transformation has widely been adopted to remove redundancy by making adjacent pixels less correlated. Pooling is a biologically inspired operation to reduce the resolution of feature maps and achieve spatial invariance in convolutional neural networks. Conventionally, pooling methods are mainly determined empirically in most previous work. Therefore, our main purpose is to study the relationship between whitening processing and pooling operations in convolutional autoencoders for image classification. We propose an adaptive pooling approach based on the concepts of information entropy to test the effect of whitening on pooling in different conditions. Experimental results on benchmark datasets indicate that the performance of pooling strategies is associated with the distribution of feature activations, which can be affected by whitening processing. This provides guidance for the selection of pooling methods in convolutional autoencoders and other convolutional neural networks.

  19. Fiber pixelated image database

    NASA Astrophysics Data System (ADS)

    Shinde, Anant; Perinchery, Sandeep Menon; Matham, Murukeshan Vadakke

    2016-08-01

    Imaging of physically inaccessible parts of the body such as the colon at micron-level resolution is highly important in diagnostic medical imaging. Though flexible endoscopes based on the imaging fiber bundle are used for such diagnostic procedures, their inherent honeycomb-like structure creates fiber pixelation effects. This impedes the observer from perceiving the information from an image captured and hinders the direct use of image processing and machine intelligence techniques on the recorded signal. Significant efforts have been made by researchers in the recent past in the development and implementation of pixelation removal techniques. However, researchers have often used their own set of images without making source data available which subdued their usage and adaptability universally. A database of pixelated images is the current requirement to meet the growing diagnostic needs in the healthcare arena. An innovative fiber pixelated image database is presented, which consists of pixelated images that are synthetically generated and experimentally acquired. Sample space encompasses test patterns of different scales, sizes, and shapes. It is envisaged that this proposed database will alleviate the current limitations associated with relevant research and development and would be of great help for researchers working on comb structure removal algorithms.

  20. Determinate-state convolutional codes

    NASA Technical Reports Server (NTRS)

    Collins, O.; Hizlan, M.

    1991-01-01

    A determinate state convolutional code is formed from a conventional convolutional code by pruning away some of the possible state transitions in the decoding trellis. The type of staged power transfer used in determinate state convolutional codes proves to be an extremely efficient way of enhancing the performance of a concatenated coding system. The decoder complexity is analyzed along with free distances of these new codes and extensive simulation results is provided of their performance at the low signal to noise ratios where a real communication system would operate. Concise, practical examples are provided.

  1. Pixelation Effects in Weak Lensing

    NASA Technical Reports Server (NTRS)

    High, F. William; Rhodes, Jason; Massey, Richard; Ellis, Richard

    2007-01-01

    Weak gravitational lensing can be used to investigate both dark matter and dark energy but requires accurate measurements of the shapes of faint, distant galaxies. Such measurements are hindered by the finite resolution and pixel scale of digital cameras. We investigate the optimum choice of pixel scale for a space-based mission, using the engineering model and survey strategy of the proposed Supernova Acceleration Probe as a baseline. We do this by simulating realistic astronomical images containing a known input shear signal and then attempting to recover the signal using the Rhodes, Refregier, and Groth algorithm. We find that the quality of shear measurement is always improved by smaller pixels. However, in practice, telescopes are usually limited to a finite number of pixels and operational life span, so the total area of a survey increases with pixel size. We therefore fix the survey lifetime and the number of pixels in the focal plane while varying the pixel scale, thereby effectively varying the survey size. In a pure trade-off for image resolution versus survey area, we find that measurements of the matter power spectrum would have minimum statistical error with a pixel scale of 0.09' for a 0.14' FWHM point-spread function (PSF). The pixel scale could be increased to 0.16' if images dithered by exactly half-pixel offsets were always available. Some of our results do depend on our adopted shape measurement method and should be regarded as an upper limit: future pipelines may require smaller pixels to overcome systematic floors not yet accessible, and, in certain circumstances, measuring the shape of the PSF might be more difficult than those of galaxies. However, the relative trends in our analysis are robust, especially those of the surface density of resolved galaxies. Our approach thus provides a snapshot of potential in available technology, and a practical counterpart to analytic studies of pixelation, which necessarily assume an idealized shape

  2. Pixel Perfect

    SciTech Connect

    Perrine, Kenneth A.; Hopkins, Derek F.; Lamarche, Brian L.; Sowa, Marianne B.

    2005-09-01

    cubic warp. During image acquisitions, the cubic warp is evaluated by way of forward differencing. Unwanted pixelation artifacts are minimized by bilinear sampling. The resulting system is state-of-the-art for biological imaging. Precisely registered images enable the reliable use of FRET techniques. In addition, real-time image processing performance allows computed images to be fed back and displayed to scientists immediately, and the pipelined nature of the FPGA allows additional image processing algorithms to be incorporated into the system without slowing throughput.

  3. Inhibitor Discovery by Convolution ABPP.

    PubMed

    Chandrasekar, Balakumaran; Hong, Tram Ngoc; van der Hoorn, Renier A L

    2017-01-01

    Activity-based protein profiling (ABPP) has emerged as a powerful proteomic approach to study the active proteins in their native environment by using chemical probes that label active site residues in proteins. Traditionally, ABPP is classified as either comparative or competitive ABPP. In this protocol, we describe a simple method called convolution ABPP, which takes benefit from both the competitive and comparative ABPP. Convolution ABPP allows one to detect if a reduced signal observed during comparative ABPP could be due to the presence of inhibitors. In convolution ABPP, the proteomes are analyzed by comparing labeling intensities in two mixed proteomes that were labeled either before or after mixing. A reduction of labeling in the mix-and-label sample when compared to the label-and-mix sample indicates the presence of an inhibitor excess in one of the proteomes. This method is broadly applicable to detect inhibitors in proteomes against any proteome containing protein activities of interest. As a proof of concept, we applied convolution ABPP to analyze secreted proteomes from Pseudomonas syringae-infected Nicotiana benthamiana leaves to display the presence of a beta-galactosidase inhibitor.

  4. Pixelated gamma detector

    SciTech Connect

    Dolinsky, Sergei Ivanovich; Yanoff, Brian David; Guida, Renato; Ivan, Adrian

    2016-12-27

    A pixelated gamma detector includes a scintillator column assembly having scintillator crystals and optical transparent elements alternating along a longitudinal axis, a collimator assembly having longitudinal walls separated by collimator septum, the collimator septum spaced apart to form collimator channels, the scintillator column assembly positioned adjacent to the collimator assembly so that the respective ones of the scintillator crystal are positioned adjacent to respective ones of the collimator channels, the respective ones of the optical transparent element are positioned adjacent to respective ones of the collimator septum, and a first photosensor and a second photosensor, the first and the second photosensor each connected to an opposing end of the scintillator column assembly. A system and a method for inspecting and/or detecting defects in an interior of an object are also disclosed.

  5. Simplified Decoding of Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Truong, T. K.; Reed, I. S.

    1986-01-01

    Some complicated intermediate steps shortened or eliminated. Decoding of convolutional error-correcting digital codes simplified by new errortrellis syndrome technique. In new technique, syndrome vector not computed. Instead, advantage taken of newly-derived mathematical identities simplify decision tree, folding it back on itself into form called "error trellis." This trellis graph of all path solutions of syndrome equations. Each path through trellis corresponds to specific set of decisions as to received digits. Existing decoding algorithms combined with new mathematical identities reduce number of combinations of errors considered and enable computation of correction vector directly from data and check bits as received.

  6. ATLAS IBL Pixel Upgrade

    NASA Astrophysics Data System (ADS)

    La Rosa, A.; Atlas Ibl Collaboration

    2011-06-01

    The upgrade for ATLAS detector will undergo different phases towards super-LHC. The first upgrade for the Pixel detector will consist of the construction of a new pixel layer which will be installed during the first shutdown of the LHC machine (LHC phase-I upgrade). The new detector, called Insertable B-Layer (IBL), will be inserted between the existing pixel detector and a new (smaller radius) beam-pipe at a radius of 3.3 cm. The IBL will require the development of several new technologies to cope with increase of radiation or pixel occupancy and also to improve the physics performance which will be achieved by reducing the pixel size and of the material budget. Three different promising sensor technologies (planar-Si, 3D-Si and diamond) are currently under investigation for the pixel detector. An overview of the project with particular emphasis on the pixel module is presented in this paper.

  7. The trellis complexity of convolutional codes

    NASA Technical Reports Server (NTRS)

    Mceliece, R. J.; Lin, W.

    1995-01-01

    It has long been known that convolutional codes have a natural, regular trellis structure that facilitates the implementation of Viterbi's algorithm. It has gradually become apparent that linear block codes also have a natural, though not in general a regular, 'minimal' trellis structure, which allows them to be decoded with a Viterbi-like algorithm. In both cases, the complexity of the Viterbi decoding algorithm can be accurately estimated by the number of trellis edges per encoded bit. It would, therefore, appear that we are in a good position to make a fair comparison of the Viterbi decoding complexity of block and convolutional codes. Unfortunately, however, this comparison is somewhat muddled by the fact that some convolutional codes, the punctured convolutional codes, are known to have trellis representations that are significantly less complex than the conventional trellis. In other words, the conventional trellis representation for a convolutional code may not be the minimal trellis representation. Thus, ironically, at present we seem to know more about the minimal trellis representation for block than for convolutional codes. In this article, we provide a remedy, by developing a theory of minimal trellises for convolutional codes. (A similar theory has recently been given by Sidorenko and Zyablov). This allows us to make a direct performance-complexity comparison for block and convolutional codes. A by-product of our work is an algorithm for choosing, from among all generator matrices for a given convolutional code, what we call a trellis-minimal generator matrix, from which the minimal trellis for the code can be directly constructed. Another by-product is that, in the new theory, punctured convolutional codes no longer appear as a special class, but simply as high-rate convolutional codes whose trellis complexity is unexpectedly small.

  8. Convolution-deconvolution in DIGES

    SciTech Connect

    Philippacopoulos, A.J.; Simos, N.

    1995-05-01

    Convolution and deconvolution operations is by all means a very important aspect of SSI analysis since it influences the input to the seismic analysis. This paper documents some of the convolution/deconvolution procedures which have been implemented into the DIGES code. The 1-D propagation of shear and dilatational waves in typical layered configurations involving a stack of layers overlying a rock is treated by DIGES in a similar fashion to that of available codes, e.g. CARES, SHAKE. For certain configurations, however, there is no need to perform such analyses since the corresponding solutions can be obtained in analytic form. Typical cases involve deposits which can be modeled by a uniform halfspace or simple layered halfspaces. For such cases DIGES uses closed-form solutions. These solutions are given for one as well as two dimensional deconvolution. The type of waves considered include P, SV and SH waves. The non-vertical incidence is given special attention since deconvolution can be defined differently depending on the problem of interest. For all wave cases considered, corresponding transfer functions are presented in closed-form. Transient solutions are obtained in the frequency domain. Finally, a variety of forms are considered for representing the free field motion both in terms of deterministic as well as probabilistic representations. These include (a) acceleration time histories, (b) response spectra (c) Fourier spectra and (d) cross-spectral densities.

  9. Bad pixel mapping

    NASA Astrophysics Data System (ADS)

    Smith, Roger M.; Hale, David; Wizinowich, Peter

    2014-07-01

    Bad pixels are generally treated as a loss of useable area and then excluded from averaged performance metrics. The definition and detection of "bad pixels" or "cosmetic defects" are seldom discussed, perhaps because they are considered self-evident or of minor consequence for any scientific grade detector, however the ramifications can be more serious than generally appreciated. While the definition of pixel performance is generally understood, the classification of pixels as useable is highly application-specific, as are the consequences of ignoring or interpolating over such pixels. CMOS sensors (including NIR detectors) exhibit less compact distributions of pixel properties than CCDs. The extended tails in these distributions result in a steeper increase in bad pixel counts as performance thresholds are tightened which comes as a surprise to many users. To illustrate how some applications are much more sensitive to bad pixels than others, we present a bad pixel mapping exercise for the Teledyne H2RG used as the NIR tip-tilt sensor in the Keck-1 Adaptive Optics system. We use this example to illustrate the wide range of metrics by which a pixel might be judged inadequate. These include pixel bump bond connectivity, vignetting, addressing faults in the mux, severe sensitivity deficiency of some pixels, non linearity, poor signal linearity, low full well, poor mean-variance linearity, excessive noise and high dark current. Some pixels appear bad by multiple metrics. We also discuss the importance of distinguishing true performance outliers from measurement errors. We note how the complexity of these issues has ramifications for sensor procurement and acceptance testing strategies.

  10. The general theory of convolutional codes

    NASA Technical Reports Server (NTRS)

    Mceliece, R. J.; Stanley, R. P.

    1993-01-01

    This article presents a self-contained introduction to the algebraic theory of convolutional codes. This introduction is partly a tutorial, but at the same time contains a number of new results which will prove useful for designers of advanced telecommunication systems. Among the new concepts introduced here are the Hilbert series for a convolutional code and the class of compact codes.

  11. Achieving unequal error protection with convolutional codes

    NASA Technical Reports Server (NTRS)

    Mills, D. G.; Costello, D. J., Jr.; Palazzo, R., Jr.

    1994-01-01

    This paper examines the unequal error protection capabilities of convolutional codes. Both time-invariant and periodically time-varying convolutional encoders are examined. The effective free distance vector is defined and is shown to be useful in determining the unequal error protection (UEP) capabilities of convolutional codes. A modified transfer function is used to determine an upper bound on the bit error probabilities for individual input bit positions in a convolutional encoder. The bound is heavily dependent on the individual effective free distance of the input bit position. A bound relating two individual effective free distances is presented. The bound is a useful tool in determining the maximum possible disparity in individual effective free distances of encoders of specified rate and memory distribution. The unequal error protection capabilities of convolutional encoders of several rates and memory distributions are determined and discussed.

  12. PixelLearn

    NASA Technical Reports Server (NTRS)

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

    2006-01-01

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

  13. High stroke pixel for a deformable mirror

    DOEpatents

    Miles, Robin R.; Papavasiliou, Alexandros P.

    2005-09-20

    A mirror pixel that can be fabricated using standard MEMS methods for a deformable mirror. The pixel is electrostatically actuated and is capable of the high deflections needed for spaced-based mirror applications. In one embodiment, the mirror comprises three layers, a top or mirror layer, a middle layer which consists of flexures, and a comb drive layer, with the flexures of the middle layer attached to the mirror layer and to the comb drive layer. The comb drives are attached to a frame via spring flexures. A number of these mirror pixels can be used to construct a large mirror assembly. The actuator for the mirror pixel may be configured as a crenellated beam with one end fixedly secured, or configured as a scissor jack. The mirror pixels may be used in various applications requiring high stroke adaptive optics.

  14. Star-galaxy classification using deep convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Kim, Edward J.; Brunner, Robert J.

    2017-02-01

    Most existing star-galaxy classifiers use the reduced summary information from catalogues, requiring careful feature extraction and selection. The latest advances in machine learning that use deep convolutional neural networks (ConvNets) allow a machine to automatically learn the features directly from the data, minimizing the need for input from human experts. We present a star-galaxy classification framework that uses deep ConvNets directly on the reduced, calibrated pixel values. Using data from the Sloan Digital Sky Survey and the Canada-France-Hawaii Telescope Lensing Survey, we demonstrate that ConvNets are able to produce accurate and well-calibrated probabilistic classifications that are competitive with conventional machine learning techniques. Future advances in deep learning may bring more success with current and forthcoming photometric surveys, such as the Dark Energy Survey and the Large Synoptic Survey Telescope, because deep neural networks require very little, manual feature engineering.

  15. Convolutional neural network features based change detection in satellite images

    NASA Astrophysics Data System (ADS)

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

    2016-07-01

    With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

  16. Parallel architectures for computing cyclic convolutions

    NASA Technical Reports Server (NTRS)

    Yeh, C.-S.; Reed, I. S.; Truong, T. K.

    1983-01-01

    In the paper two parallel architectural structures are developed to compute one-dimensional cyclic convolutions. The first structure is based on the Chinese remainder theorem and Kung's pipelined array. The second structure is a direct mapping from the mathematical definition of a cyclic convolution to a computational architecture. To compute a d-point cyclic convolution the first structure needs d/2 inner product cells, while the second structure and Kung's linear array require d cells. However, to compute a cyclic convolution, the second structure requires less time than both the first structure and Kung's linear array. Another application of the second structure is to multiply a Toeplitz matrix by a vector. A table is listed to compare these two structures and Kung's linear array. Both structures are simple and regular and are therefore suitable for VLSI implementation.

  17. Fast vision through frameless event-based sensing and convolutional processing: application to texture recognition.

    PubMed

    Perez-Carrasco, Jose Antonio; Acha, Begona; Serrano, Carmen; Camunas-Mesa, Luis; Serrano-Gotarredona, Teresa; Linares-Barranco, Bernabe

    2010-04-01

    Address-event representation (AER) is an emergent hardware technology which shows a high potential for providing in the near future a solid technological substrate for emulating brain-like processing structures. When used for vision, AER sensors and processors are not restricted to capturing and processing still image frames, as in commercial frame-based video technology, but sense and process visual information in a pixel-level event-based frameless manner. As a result, vision processing is practically simultaneous to vision sensing, since there is no need to wait for sensing full frames. Also, only meaningful information is sensed, communicated, and processed. Of special interest for brain-like vision processing are some already reported AER convolutional chips, which have revealed a very high computational throughput as well as the possibility of assembling large convolutional neural networks in a modular fashion. It is expected that in a near future we may witness the appearance of large scale convolutional neural networks with hundreds or thousands of individual modules. In the meantime, some research is needed to investigate how to assemble and configure such large scale convolutional networks for specific applications. In this paper, we analyze AER spiking convolutional neural networks for texture recognition hardware applications. Based on the performance figures of already available individual AER convolution chips, we emulate large scale networks using a custom made event-based behavioral simulator. We have developed a new event-based processing architecture that emulates with AER hardware Manjunath's frame-based feature recognition software algorithm, and have analyzed its performance using our behavioral simulator. Recognition rate performance is not degraded. However, regarding speed, we show that recognition can be achieved before an equivalent frame is fully sensed and transmitted.

  18. Coset Codes Viewed as Terminated Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Fossorier, Marc P. C.; Lin, Shu

    1996-01-01

    In this paper, coset codes are considered as terminated convolutional codes. Based on this approach, three new general results are presented. First, it is shown that the iterative squaring construction can equivalently be defined from a convolutional code whose trellis terminates. This convolutional code determines a simple encoder for the coset code considered, and the state and branch labelings of the associated trellis diagram become straightforward. Also, from the generator matrix of the code in its convolutional code form, much information about the trade-off between the state connectivity and complexity at each section, and the parallel structure of the trellis, is directly available. Based on this generator matrix, it is shown that the parallel branches in the trellis diagram of the convolutional code represent the same coset code C(sub 1), of smaller dimension and shorter length. Utilizing this fact, a two-stage optimum trellis decoding method is devised. The first stage decodes C(sub 1), while the second stage decodes the associated convolutional code, using the branch metrics delivered by stage 1. Finally, a bidirectional decoding of each received block starting at both ends is presented. If about the same number of computations is required, this approach remains very attractive from a practical point of view as it roughly doubles the decoding speed. This fact is particularly interesting whenever the second half of the trellis is the mirror image of the first half, since the same decoder can be implemented for both parts.

  19. High density pixel array

    NASA Technical Reports Server (NTRS)

    Wiener-Avnear, Eliezer (Inventor); McFall, James Earl (Inventor)

    2004-01-01

    A pixel array device is fabricated by a laser micro-milling method under strict process control conditions. The device has an array of pixels bonded together with an adhesive filling the grooves between adjacent pixels. The array is fabricated by moving a substrate relative to a laser beam of predetermined intensity at a controlled, constant velocity along a predetermined path defining a set of grooves between adjacent pixels so that a predetermined laser flux per unit area is applied to the material, and repeating the movement for a plurality of passes of the laser beam until the grooves are ablated to a desired depth. The substrate is of an ultrasonic transducer material in one example for fabrication of a 2D ultrasonic phase array transducer. A substrate of phosphor material is used to fabricate an X-ray focal plane array detector.

  20. Classification of breast cancer cytological specimen using convolutional neural network

    NASA Astrophysics Data System (ADS)

    Żejmo, Michał; Kowal, Marek; Korbicz, Józef; Monczak, Roman

    2017-01-01

    The paper presents a deep learning approach for automatic classification of breast tumors based on fine needle cytology. The main aim of the system is to distinguish benign from malignant cases based on microscopic images. Experiment was carried out on cytological samples derived from 50 patients (25 benign cases + 25 malignant cases) diagnosed in Regional Hospital in Zielona Góra. To classify microscopic images, we used convolutional neural networks (CNN) of two types: GoogLeNet and AlexNet. Due to the very large size of images of cytological specimen (on average 200000 × 100000 pixels), they were divided into smaller patches of size 256 × 256 pixels. Breast cancer classification usually is based on morphometric features of nuclei. Therefore, training and validation patches were selected using Support Vector Machine (SVM) so that suitable amount of cell material was depicted. Neural classifiers were tuned using GPU accelerated implementation of gradient descent algorithm. Training error was defined as a cross-entropy classification loss. Classification accuracy was defined as the percentage ratio of successfully classified validation patches to the total number of validation patches. The best accuracy rate of 83% was obtained by GoogLeNet model. We observed that more misclassified patches belong to malignant cases.

  1. Simplified Syndrome Decoding of (n, 1) Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1983-01-01

    A new syndrome decoding algorithm for the (n, 1) convolutional codes (CC) that is different and simpler than the previous syndrome decoding algorithm of Schalkwijk and Vinck is presented. The new algorithm uses the general solution of the polynomial linear Diophantine equation for the error polynomial vector E(D). This set of Diophantine solutions is a coset of the CC space. A recursive or Viterbi-like algorithm is developed to find the minimum weight error vector cirumflex E(D) in this error coset. An example illustrating the new decoding algorithm is given for the binary nonsymmetric (2,1)CC.

  2. Selecting Pixels for Kepler Downlink

    NASA Technical Reports Server (NTRS)

    Bryson, Stephen T.; Jenkins, Jon M.; Klaus, Todd C.; Cote, Miles T.; Quintana, Elisa V.; Hall, Jennifer R.; Ibrahim, Khadeejah; Chandrasekaran, Hema; Caldwell, Douglas A.; Van Cleve, Jeffrey E.; Haas, Michael R.

    2010-01-01

    The Kepler mission monitors > 100,000 stellar targets using 42 2200 1024 pixel CCDs. Bandwidth constraints prevent the downlink of all 96 million pixels per 30-minute cadence, so the Kepler spacecraft downlinks a specified collection of pixels for each target. These pixels are selected by considering the object brightness, background and the signal-to-noise of each pixel, and are optimized to maximize the signal-to-noise ratio of the target. This paper describes pixel selection, creation of spacecraft apertures that efficiently capture selected pixels, and aperture assignment to a target. Diagnostic apertures, short-cadence targets and custom specified shapes are discussed.

  3. Molecular graph convolutions: moving beyond fingerprints.

    PubMed

    Kearnes, Steven; McCloskey, Kevin; Berndl, Marc; Pande, Vijay; Riley, Patrick

    2016-08-01

    Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structure while ignoring others, rather than allowing the model to make data-driven decisions. We describe molecular graph convolutions, a machine learning architecture for learning from undirected graphs, specifically small molecules. Graph convolutions use a simple encoding of the molecular graph-atoms, bonds, distances, etc.-which allows the model to take greater advantage of information in the graph structure. Although graph convolutions do not outperform all fingerprint-based methods, they (along with other graph-based methods) represent a new paradigm in ligand-based virtual screening with exciting opportunities for future improvement.

  4. Cyclic Cocycles on Twisted Convolution Algebras

    NASA Astrophysics Data System (ADS)

    Angel, Eitan

    2013-01-01

    We give a construction of cyclic cocycles on convolution algebras twisted by gerbes over discrete translation groupoids. For proper étale groupoids, Tu and Xu (Adv Math 207(2):455-483, 2006) provide a map between the periodic cyclic cohomology of a gerbe-twisted convolution algebra and twisted cohomology groups which is similar to the construction of Mathai and Stevenson (Adv Math 200(2):303-335, 2006). When the groupoid is not proper, we cannot construct an invariant connection on the gerbe; therefore to study this algebra, we instead develop simplicial techniques to construct a simplicial curvature 3-form representing the class of the gerbe. Then by using a JLO formula we define a morphism from a simplicial complex twisted by this simplicial curvature 3-form to the mixed bicomplex computing the periodic cyclic cohomology of the twisted convolution algebras.

  5. Molecular graph convolutions: moving beyond fingerprints

    NASA Astrophysics Data System (ADS)

    Kearnes, Steven; McCloskey, Kevin; Berndl, Marc; Pande, Vijay; Riley, Patrick

    2016-08-01

    Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structure while ignoring others, rather than allowing the model to make data-driven decisions. We describe molecular graph convolutions, a machine learning architecture for learning from undirected graphs, specifically small molecules. Graph convolutions use a simple encoding of the molecular graph—atoms, bonds, distances, etc.—which allows the model to take greater advantage of information in the graph structure. Although graph convolutions do not outperform all fingerprint-based methods, they (along with other graph-based methods) represent a new paradigm in ligand-based virtual screening with exciting opportunities for future improvement.

  6. Illuminant spectrum estimation at a pixel.

    PubMed

    Ratnasingam, Sivalogeswaran; Hernández-Andrés, Javier

    2011-04-01

    In this paper, an algorithm is proposed to estimate the spectral power distribution of a light source at a pixel. The first step of the algorithm is forming a two-dimensional illuminant invariant chromaticity space. In estimating the illuminant spectrum, generalized inverse estimation and Wiener estimation methods were applied. The chromaticity space was divided into small grids and a weight matrix was used to estimate the illuminant spectrum illuminating the pixels that fall within a grid. The algorithm was tested using a different number of sensor responses to determine the optimum number of sensors for accurate colorimetric and spectral reproduction. To investigate the performance of the algorithm realistically, the responses were multiplied with Gaussian noise and then quantized to 10 bits. The algorithm was tested with standard and measured data. Based on the results presented, the algorithm can be used with six sensors to obtain a colorimetrically good estimate of the illuminant spectrum at a pixel.

  7. On the twisted convolution product and the Weyl transformation of tempered distributions

    NASA Astrophysics Data System (ADS)

    Maillard, J. M.

    It is well known that the Weyl transformation in a phase space R21, transforms the elements of L( R21) in trace class operators and the elements of L 2( R21) in the Hilbert-Schmidt operators of the Hilbert space L 2( R1); this fact leads to a general method of quantization suggested by E. Wigner and J.E. Moyal and developed by M. Flato, A. Lichnerowicz, C. Fronsdal, D. Sternheimer and F. Bayen for an arbitrary symplectic manifold, known under the name of star-product method. In this context, it is important to study the Weyl transforms of the tempered distributions on the phase space and that of the star-exponentials which gave the spectrum in this process of quantization. We analyze here the relations between the star-product, the twisted convolution product and the Weyl transformation of tempered distributions. We introduce symplectic differential operators which permit us to study the structure of the space O1λ λ ≠ 0, (similar to the space O1C) of the left (twisted) convolution operators of L( R21) which permit to define the twisted convolution product in the space L( R21), and the structures of the admissible symbols for the Weyl transformation (i.e. the domain of the Weyl transformation). We prove that the bounded operators of L 2( R1) are exactly the Weyl transforms of the bounded (twisted) convolution operators of L 2( R21). We give an expression of the integral formula of the star product in terms of twisted convolution products which is valid in the most general case. The unitary representations of the Heisenberg group play an important role here.

  8. Architectural style classification of Mexican historical buildings using deep convolutional neural networks and sparse features

    NASA Astrophysics Data System (ADS)

    Obeso, Abraham Montoya; Benois-Pineau, Jenny; Acosta, Alejandro Álvaro Ramirez; Vázquez, Mireya Saraí García

    2017-01-01

    We propose a convolutional neural network to classify images of buildings using sparse features at the network's input in conjunction with primary color pixel values. As a result, a trained neuronal model is obtained to classify Mexican buildings in three classes according to the architectural styles: prehispanic, colonial, and modern with an accuracy of 88.01%. The problem of poor information in a training dataset is faced due to the unequal availability of cultural material. We propose a data augmentation and oversampling method to solve this problem. The results are encouraging and allow for prefiltering of the content in the search tasks.

  9. Sequential Syndrome Decoding of Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1984-01-01

    The algebraic structure of convolutional codes are reviewed and sequential syndrome decoding is applied to those codes. These concepts are then used to realize by example actual sequential decoding, using the stack algorithm. The Fano metric for use in sequential decoding is modified so that it can be utilized to sequentially find the minimum weight error sequence.

  10. Effectiveness of Convolutional Code in Multipath Underwater Acoustic Channel

    NASA Astrophysics Data System (ADS)

    Park, Jihyun; Seo, Chulwon; Park, Kyu-Chil; Yoon, Jong Rak

    2013-07-01

    The forward error correction (FEC) is achieved by increasing redundancy of information. Convolutional coding with Viterbi decoding is a typical FEC technique in channel corrupted by additive white gaussian noise. But the FEC effectiveness of convolutional code is questioned in multipath frequency selective fading channel. In this paper, how convolutional code works in multipath channel in underwater, is examined. Bit error rates (BER) with and without 1/2 convolutional code are analyzed based on channel bandwidth which is frequency selectivity parameter. It is found that convolution code performance is well matched in non selective channel and also effective in selective channel.

  11. An optimal nonorthogonal separation of the anisotropic Gaussian convolution filter.

    PubMed

    Lampert, Christoph H; Wirjadi, Oliver

    2006-11-01

    We give an analytical and geometrical treatment of what it means to separate a Gaussian kernel along arbitrary axes in R(n), and we present a separation scheme that allows us to efficiently implement anisotropic Gaussian convolution filters for data of arbitrary dimensionality. Based on our previous analysis we show that this scheme is optimal with regard to the number of memory accesses and interpolation operations needed. The proposed method relies on nonorthogonal convolution axes and works completely in image space. Thus, it avoids the need for a fast Fourier transform (FFT)-subroutine. Depending on the accuracy and speed requirements, different interpolation schemes and methods to implement the one-dimensional Gaussian (finite impulse response and infinite impulse response) can be integrated. Special emphasis is put on analyzing the performance and accuracy of the new method. In particular, we show that without any special optimization of the source code, it can perform anisotropic Gaussian filtering faster than methods relying on the FFT.

  12. Infrared astronomy - Pixels to spare

    SciTech Connect

    Mccaughrean, M. )

    1991-07-01

    An infrared CCD camera containing an array with 311,040 pixels arranged in 486 rows of 640 each is tested. The array is a chip of platinum silicide (PtSi), sensitive to photons with wavelengths between 1 and 6 microns. Observations of the Hubble Space Telescope, Mars, Pluto and moon are reported. It is noted that the satellite's twin solar-cell arrays, at an apparent separation of about 1 1/4 arc second, are well resolved. Some two dozen video frames were stacked to make each presented image of Mars at 1.6 microns; at this wavelength Mars appears much as it does in visible light. A stack of 11 images at a wavelength of 1.6 microns is used for an image of Jupiter with its Great Red Spot and moons Io and Europa.

  13. Fast space-variant elliptical filtering using box splines.

    PubMed

    Chaudhury, Kunal Narayan; Munoz-Barrutia, Arrate; Unser, Michael

    2010-09-01

    The efficient realization of linear space-variant (non-convolution) filters is a challenging computational problem in image processing. In this paper, we demonstrate that it is possible to filter an image with a Gaussian-like elliptic window of varying size, elongation and orientation using a fixed number of computations per pixel. The associated algorithm, which is based upon a family of smooth compactly supported piecewise polynomials, the radially-uniform box splines, is realized using preintegration and local finite-differences. The radially-uniform box splines are constructed through the repeated convolution of a fixed number of box distributions, which have been suitably scaled and distributed radially in an uniform fashion. The attractive features of these box splines are their asymptotic behavior, their simple covariance structure, and their quasi-separability. They converge to Gaussians with the increase of their order, and are used to approximate anisotropic Gaussians of varying covariance simply by controlling the scales of the constituent box distributions. Based upon the second feature, we develop a technique for continuously controlling the size, elongation and orientation of these Gaussian-like functions. Finally, the quasi-separable structure, along with a certain scaling property of box distributions, is used to efficiently realize the associated space-variant elliptical filtering, which requires O(1) computations per pixel irrespective of the shape and size of the filter.

  14. Digital Correlation By Optical Convolution/Correlation

    NASA Astrophysics Data System (ADS)

    Trimble, Joel; Casasent, David; Psaltis, Demetri; Caimi, Frank; Carlotto, Mark; Neft, Deborah

    1980-12-01

    Attention is given to various methods by which the accuracy achieveable and the dynamic range requirements of an optical computer can be enhanced. A new time position coding acousto-optic technique for optical residue arithmetic processing is presented and experimental demonstration is included. Major attention is given to the implementation of a correlator operating on digital or decimal encoded signals. Using a convolution description of multiplication, we realize such a correlator by optical convolution in one dimension and optical correlation in the other dimension of a optical system. A coherent matched spatial filter system operating on digital encoded signals, a noncoherent processor operating on complex-valued digital-encoded data, and a real-time multi-channel acousto-optic system for such operations are described and experimental verifications are included.

  15. Performance of convolutionally coded unbalanced QPSK systems

    NASA Technical Reports Server (NTRS)

    Divsalar, D.; Yuen, J. H.

    1980-01-01

    An evaluation is presented of the performance of three representative convolutionally coded unbalanced quadri-phase-shift-keying (UQPSK) systems in the presence of noisy carrier reference and crosstalk. The use of a coded UQPSK system for transmitting two telemetry data streams with different rates and different powers has been proposed for the Venus Orbiting Imaging Radar mission. Analytical expressions for bit error rates in the presence of a noisy carrier phase reference are derived for three representative cases: (1) I and Q channels are coded independently; (2) I channel is coded, Q channel is uncoded; and (3) I and Q channels are coded by a common 1/2 code. For rate 1/2 convolutional codes, QPSK modulation can be used to reduce the bandwidth requirement.

  16. Convoluted accommodation structures in folded rocks

    NASA Astrophysics Data System (ADS)

    Dodwell, T. J.; Hunt, G. W.

    2012-10-01

    A simplified variational model for the formation of convoluted accommodation structures, as seen in the hinge zones of larger-scale geological folds, is presented. The model encapsulates some important and intriguing nonlinear features, notably: infinite critical loads, formation of plastic hinges, and buckling on different length-scales. An inextensible elastic beam is forced by uniform overburden pressure and axial load into a V-shaped geometry dictated by formation of a plastic hinge. Using variational methods developed by Dodwell et al., upon which this paper leans heavily, energy minimisation leads to representation as a fourth-order nonlinear differential equation with free boundary conditions. Equilibrium solutions are found using numerical shooting techniques. Under the Maxwell stability criterion, it is recognised that global energy minimisers can exist with convoluted physical shapes. For such solutions, parallels can be drawn with some of the accommodation structures seen in exposed escarpments of real geological folds.

  17. A convolutional neural network neutrino event classifier

    DOE PAGES

    Aurisano, A.; Radovic, A.; Rocco, D.; ...

    2016-09-01

    Here, convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology withoutmore » the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.« less

  18. A convolutional neural network neutrino event classifier

    SciTech Connect

    Aurisano, A.; Radovic, A.; Rocco, D.; Himmel, A.; Messier, M. D.; Niner, E.; Pawloski, G.; Psihas, F.; Sousa, A.; Vahle, P.

    2016-09-01

    Here, convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology without the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.

  19. A Construction of MDS Quantum Convolutional Codes

    NASA Astrophysics Data System (ADS)

    Zhang, Guanghui; Chen, Bocong; Li, Liangchen

    2015-09-01

    In this paper, two new families of MDS quantum convolutional codes are constructed. The first one can be regarded as a generalization of [36, Theorem 6.5], in the sense that we do not assume that q≡1 (mod 4). More specifically, we obtain two classes of MDS quantum convolutional codes with parameters: (i) [( q 2+1, q 2-4 i+3,1;2,2 i+2)] q , where q≥5 is an odd prime power and 2≤ i≤( q-1)/2; (ii) , where q is an odd prime power with the form q=10 m+3 or 10 m+7 ( m≥2), and 2≤ i≤2 m-1.

  20. A convolutional neural network neutrino event classifier

    NASA Astrophysics Data System (ADS)

    Aurisano, A.; Radovic, A.; Rocco, D.; Himmel, A.; Messier, M. D.; Niner, E.; Pawloski, G.; Psihas, F.; Sousa, A.; Vahle, P.

    2016-09-01

    Convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology without the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.

  1. Deep Learning with Hierarchical Convolutional Factor Analysis

    PubMed Central

    Chen, Bo; Polatkan, Gungor; Sapiro, Guillermo; Blei, David; Dunson, David; Carin, Lawrence

    2013-01-01

    Unsupervised multi-layered (“deep”) models are considered for general data, with a particular focus on imagery. The model is represented using a hierarchical convolutional factor-analysis construction, with sparse factor loadings and scores. The computation of layer-dependent model parameters is implemented within a Bayesian setting, employing a Gibbs sampler and variational Bayesian (VB) analysis, that explicitly exploit the convolutional nature of the expansion. In order to address large-scale and streaming data, an online version of VB is also developed. The number of basis functions or dictionary elements at each layer is inferred from the data, based on a beta-Bernoulli implementation of the Indian buffet process. Example results are presented for several image-processing applications, with comparisons to related models in the literature. PMID:23787342

  2. Pixelated neutron image plates

    NASA Astrophysics Data System (ADS)

    Schlapp, M.; Conrad, H.; von Seggern, H.

    2004-09-01

    Neutron image plates (NIPs) have found widespread application as neutron detectors for single-crystal and powder diffraction, small-angle scattering and tomography. After neutron exposure, the image plate can be read out by scanning with a laser. Commercially available NIPs consist of a powder mixture of BaFBr : Eu2+ and Gd2O3 dispersed in a polymer matrix and supported by a flexible polymer sheet. Since BaFBr : Eu2+ is an excellent x-ray storage phosphor, these NIPs are particularly sensitive to ggr-radiation, which is always present as a background radiation in neutron experiments. In this work we present results on NIPs consisting of KCl : Eu2+ and LiF that were fabricated into ceramic image plates in which the alkali halides act as a self-supporting matrix without the necessity for using a polymeric binder. An advantage of this type of NIP is the significantly reduced ggr-sensitivity. However, the much lower neutron absorption cross section of LiF compared with Gd2O3 demands a thicker image plate for obtaining comparable neutron absorption. The greater thickness of the NIP inevitably leads to a loss in spatial resolution of the image plate. However, this reduction in resolution can be restricted by a novel image plate concept in which a ceramic structure with square cells (referred to as a 'honeycomb') is embedded in the NIP, resulting in a pixelated image plate. In such a NIP the read-out light is confined to the particular illuminated pixel, decoupling the spatial resolution from the optical properties of the image plate material and morphology. In this work, a comparison of experimentally determined and simulated spatial resolutions of pixelated and unstructured image plates for a fixed read-out laser intensity is presented, as well as simulations of the properties of these NIPs at higher laser powers.

  3. The ALICE Pixel Detector

    NASA Astrophysics Data System (ADS)

    Mercado-Perez, Jorge

    2002-07-01

    The present document is a brief summary of the performed activities during the 2001 Summer Student Programme at CERN under the Scientific Summer at Foreign Laboratories Program organized by the Particles and Fields Division of the Mexican Physical Society (Sociedad Mexicana de Fisica). In this case, the activities were related with the ALICE Pixel Group of the EP-AIT Division, under the supervision of Jeroen van Hunen, research fellow in this group. First, I give an introduction and overview to the ALICE experiment; followed by a description of wafer probing. A brief summary of the test beam that we had from July 13th to July 25th is given as well.

  4. Dense Semantic Labeling of Subdecimeter Resolution Images With Convolutional Neural Networks

    NASA Astrophysics Data System (ADS)

    Volpi, Michele; Tuia, Devis

    2017-02-01

    Semantic labeling (or pixel-level land-cover classification) in ultra-high resolution imagery (< 10cm) requires statistical models able to learn high level concepts from spatial data, with large appearance variations. Convolutional Neural Networks (CNNs) achieve this goal by learning discriminatively a hierarchy of representations of increasing abstraction. In this paper we present a CNN-based system relying on an downsample-then-upsample architecture. Specifically, it first learns a rough spatial map of high-level representations by means of convolutions and then learns to upsample them back to the original resolution by deconvolutions. By doing so, the CNN learns to densely label every pixel at the original resolution of the image. This results in many advantages, including i) state-of-the-art numerical accuracy, ii) improved geometric accuracy of predictions and iii) high efficiency at inference time. We test the proposed system on the Vaihingen and Potsdam sub-decimeter resolution datasets, involving semantic labeling of aerial images of 9cm and 5cm resolution, respectively. These datasets are composed by many large and fully annotated tiles allowing an unbiased evaluation of models making use of spatial information. We do so by comparing two standard CNN architectures to the proposed one: standard patch classification, prediction of local label patches by employing only convolutions and full patch labeling by employing deconvolutions. All the systems compare favorably or outperform a state-of-the-art baseline relying on superpixels and powerful appearance descriptors. The proposed full patch labeling CNN outperforms these models by a large margin, also showing a very appealing inference time.

  5. $\\mathtt {Deepr}$: A Convolutional Net for Medical Records.

    PubMed

    Nguyen, Phuoc; Tran, Truyen; Wickramasinghe, Nilmini; Venkatesh, Svetha

    2017-01-01

    Feature engineering remains a major bottleneck when creating predictive systems from electronic medical records. At present, an important missing element is detecting predictive regular clinical motifs from irregular episodic records. We present Deepr (short for Deep record), a new end-to-end deep learning system that learns to extract features from medical records and predicts future risk automatically. Deepr transforms a record into a sequence of discrete elements separated by coded time gaps and hospital transfers. On top of the sequence is a convolutional neural net that detects and combines predictive local clinical motifs to stratify the risk. Deepr permits transparent inspection and visualization of its inner working. We validate Deepr on hospital data to predict unplanned readmission after discharge. Deepr achieves superior accuracy compared to traditional techniques, detects meaningful clinical motifs, and uncovers the underlying structure of the disease and intervention space.

  6. Imaging properties of pixellated scintillators with deep pixels

    PubMed Central

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

    2015-01-01

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

  7. Imaging properties of pixellated scintillators with deep pixels

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

  8. Imaging properties of pixellated scintillators with deep pixels.

    PubMed

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

    2014-08-17

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

  9. A multilevel local discrete convolution method for the numerical solution for Maxwell's Equations

    NASA Astrophysics Data System (ADS)

    Lo, Boris; Colella, Phillip

    2016-10-01

    We present a new discrete multilevel local discrete convolution method for solving Maxwell's equations in three dimensions. We obtain an explicit real-space representation for the propagator of an auxiliary system of differential equations with initial value constraints that is equivalent to Maxwell's equations. The propagator preserves finite speed of propagation and source locality. Because the propagator involves convolution against a singular distribution, we regularize via convolution with smoothing kernels (B-splines) prior to sampling. We have shown that the ultimate discrete convolutional propagator can be constructed to attain an arbitrarily high order of accuracy by using higher-order regularizing kernels and finite difference stencils. The discretized propagator is compactly supported and can be applied using Hockney's method (1970) and parallelized using domain decomposition, leading to a method that is computationally efficient. The algorithm is extended to work for locally refined fixed hierarchy of rectangular grids. This research is supported by the Office of Advanced Scientific Computing Research of the US Department of Energy under Contract Number DE-AC02-05CH11231.

  10. A fast complex integer convolution using a hybrid transform

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; K Truong, T.

    1978-01-01

    It is shown that the Winograd transform can be combined with a complex integer transform over the Galois field GF(q-squared) to yield a new algorithm for computing the discrete cyclic convolution of complex number points. By this means a fast method for accurately computing the cyclic convolution of a sequence of complex numbers for long convolution lengths can be obtained. This new hybrid algorithm requires fewer multiplications than previous algorithms.

  11. Applications of convolution voltammetry in electroanalytical chemistry.

    PubMed

    Bentley, Cameron L; Bond, Alan M; Hollenkamp, Anthony F; Mahon, Peter J; Zhang, Jie

    2014-02-18

    The robustness of convolution voltammetry for determining accurate values of the diffusivity (D), bulk concentration (C(b)), and stoichiometric number of electrons (n) has been demonstrated by applying the technique to a series of electrode reactions in molecular solvents and room temperature ionic liquids (RTILs). In acetonitrile, the relatively minor contribution of nonfaradaic current facilitates analysis with macrodisk electrodes, thus moderate scan rates can be used without the need to perform background subtraction to quantify the diffusivity of iodide [D = 1.75 (±0.02) × 10(-5) cm(2) s(-1)] in this solvent. In the RTIL 1-ethyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide, background subtraction is necessary at a macrodisk electrode but can be avoided at a microdisk electrode, thereby simplifying the analytical procedure and allowing the diffusivity of iodide [D = 2.70 (±0.03) × 10(-7) cm(2) s(-1)] to be quantified. Use of a convolutive procedure which simultaneously allows D and nC(b) values to be determined is also demonstrated. Three conditions under which a technique of this kind may be applied are explored and are related to electroactive species which display slow dissolution kinetics, undergo a single multielectron transfer step, or contain multiple noninteracting redox centers using ferrocene in an RTIL, 1,4-dinitro-2,3,5,6-tetramethylbenzene, and an alkynylruthenium trimer, respectively, as examples. The results highlight the advantages of convolution voltammetry over steady-state techniques such as rotating disk electrode voltammetry and microdisk electrode voltammetry, as it is not restricted by the mode of diffusion (planar or radial), hence removing limitations on solvent viscosity, electrode geometry, and voltammetric scan rate.

  12. Bacterial colony counting by Convolutional Neural Networks.

    PubMed

    Ferrari, Alessandro; Lombardi, Stefano; Signoroni, Alberto

    2015-01-01

    Counting bacterial colonies on microbiological culture plates is a time-consuming, error-prone, nevertheless fundamental task in microbiology. Computer vision based approaches can increase the efficiency and the reliability of the process, but accurate counting is challenging, due to the high degree of variability of agglomerated colonies. In this paper, we propose a solution which adopts Convolutional Neural Networks (CNN) for counting the number of colonies contained in confluent agglomerates, that scored an overall accuracy of the 92.8% on a large challenging dataset. The proposed CNN-based technique for estimating the cardinality of colony aggregates outperforms traditional image processing approaches, becoming a promising approach to many related applications.

  13. Zebrafish tracking using convolutional neural networks

    PubMed Central

    XU, Zhiping; Cheng, Xi En

    2017-01-01

    Keeping identity for a long term after occlusion is still an open problem in the video tracking of zebrafish-like model animals, and accurate animal trajectories are the foundation of behaviour analysis. We utilize the highly accurate object recognition capability of a convolutional neural network (CNN) to distinguish fish of the same congener, even though these animals are indistinguishable to the human eye. We used data augmentation and an iterative CNN training method to optimize the accuracy for our classification task, achieving surprisingly accurate trajectories of zebrafish of different size and age zebrafish groups over different time spans. This work will make further behaviour analysis more reliable. PMID:28211462

  14. Convolutional coding combined with continuous phase modulation

    NASA Technical Reports Server (NTRS)

    Pizzi, S. V.; Wilson, S. G.

    1985-01-01

    Background theory and specific coding designs for combined coding/modulation schemes utilizing convolutional codes and continuous-phase modulation (CPM) are presented. In this paper the case of r = 1/2 coding onto a 4-ary CPM is emphasized, with short-constraint length codes presented for continuous-phase FSK, double-raised-cosine, and triple-raised-cosine modulation. Coding buys several decibels of coding gain over the Gaussian channel, with an attendant increase of bandwidth. Performance comparisons in the power-bandwidth tradeoff with other approaches are made.

  15. Zebrafish tracking using convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Xu, Zhiping; Cheng, Xi En

    2017-02-01

    Keeping identity for a long term after occlusion is still an open problem in the video tracking of zebrafish-like model animals, and accurate animal trajectories are the foundation of behaviour analysis. We utilize the highly accurate object recognition capability of a convolutional neural network (CNN) to distinguish fish of the same congener, even though these animals are indistinguishable to the human eye. We used data augmentation and an iterative CNN training method to optimize the accuracy for our classification task, achieving surprisingly accurate trajectories of zebrafish of different size and age zebrafish groups over different time spans. This work will make further behaviour analysis more reliable.

  16. QCDNUM: Fast QCD evolution and convolution

    NASA Astrophysics Data System (ADS)

    Botje, M.

    2011-02-01

    The QCDNUM program numerically solves the evolution equations for parton densities and fragmentation functions in perturbative QCD. Un-polarised parton densities can be evolved up to next-to-next-to-leading order in powers of the strong coupling constant, while polarised densities or fragmentation functions can be evolved up to next-to-leading order. Other types of evolution can be accessed by feeding alternative sets of evolution kernels into the program. A versatile convolution engine provides tools to compute parton luminosities, cross-sections in hadron-hadron scattering, and deep inelastic structure functions in the zero-mass scheme or in generalised mass schemes. Input to these calculations are either the QCDNUM evolved densities, or those read in from an external parton density repository. Included in the software distribution are packages to calculate zero-mass structure functions in un-polarised deep inelastic scattering, and heavy flavour contributions to these structure functions in the fixed flavour number scheme. Program summaryProgram title: QCDNUM version: 17.00 Catalogue identifier: AEHV_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHV_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU Public Licence No. of lines in distributed program, including test data, etc.: 45 736 No. of bytes in distributed program, including test data, etc.: 911 569 Distribution format: tar.gz Programming language: Fortran-77 Computer: All Operating system: All RAM: Typically 3 Mbytes Classification: 11.5 Nature of problem: Evolution of the strong coupling constant and parton densities, up to next-to-next-to-leading order in perturbative QCD. Computation of observable quantities by Mellin convolution of the evolved densities with partonic cross-sections. Solution method: Parametrisation of the parton densities as linear or quadratic splines on a discrete grid, and evolution of the spline

  17. PIXELS: Using field-based learning to investigate students' concepts of pixels and sense of scale

    NASA Astrophysics Data System (ADS)

    Pope, A.; Tinigin, L.; Petcovic, H. L.; Ormand, C. J.; LaDue, N.

    2015-12-01

    Empirical work over the past decade supports the notion that a high level of spatial thinking skill is critical to success in the geosciences. Spatial thinking incorporates a host of sub-skills such as mentally rotating an object, imagining the inside of a 3D object based on outside patterns, unfolding a landscape, and disembedding critical patterns from background noise. In this study, we focus on sense of scale, which refers to how an individual quantified space, and is thought to develop through kinesthetic experiences. Remote sensing data are increasingly being used for wide-reaching and high impact research. A sense of scale is critical to many areas of the geosciences, including understanding and interpreting remotely sensed imagery. In this exploratory study, students (N=17) attending the Juneau Icefield Research Program participated in a 3-hour exercise designed to study how a field-based activity might impact their sense of scale and their conceptions of pixels in remotely sensed imagery. Prior to the activity, students had an introductory remote sensing lecture and completed the Sense of Scale inventory. Students walked and/or skied the perimeter of several pixel types, including a 1 m square (representing a WorldView sensor's pixel), a 30 m square (a Landsat pixel) and a 500 m square (a MODIS pixel). The group took reflectance measurements using a field radiometer as they physically traced out the pixel. The exercise was repeated in two different areas, one with homogenous reflectance, and another with heterogeneous reflectance. After the exercise, students again completed the Sense of Scale instrument and a demographic survey. This presentation will share the effects and efficacy of the field-based intervention to teach remote sensing concepts and to investigate potential relationships between students' concepts of pixels and sense of scale.

  18. Convolutional Neural Network on Embedded Linux System-on-Chip: A Methodology and Performance Benchmark

    DTIC Science & Technology

    2016-05-01

    heat sink. Note that a final system could be made much smaller than this development board, which has “wasted” space compared to a board used in a...TECHNICAL REPORT 3010 May 2016 Convolutional Neural Network on Embedded Linux® System -on-Chip A Methodology and Performance Benchmark Daniel...in this report was performed by the IO Support to National Security Branch (Code 56120), the Mission Systems Engineering Branch (Code 56170), and the

  19. Sub pixel location identification using super resolved multilooking CHRIS data

    NASA Astrophysics Data System (ADS)

    Sahithi, V. S.; Agrawal, S.

    2014-11-01

    CHRIS /Proba is a multiviewing hyperspectral sensor that monitors the earth in five different zenith angles +55°, +36°, nadir, -36° and -55° with a spatial resolution of 17 m and within a spectral range of 400-1050 nm in mode 3. These multiviewing images are suitable for constructing a super resolved high resolution image that can reveal the mixed pixel of the hyperspectral image. In the present work, an attempt is made to find the location of various features constituted within the 17m mixed pixel of the CHRIS image using various super resolution reconstruction techniques. Four different super resolution reconstruction techniques namely interpolation, iterative back projection, projection on to convex sets (POCS) and robust super resolution were tried on the -36, nadir and +36 images to construct a super resolved high resolution 5.6 m image. The results of super resolution reconstruction were compared with the scaled nadir image and bicubic convoluted image for comparision of the spatial and spectral property preservance. A support vector machine classification of the best super resolved high resolution image was performed to analyse the location of the sub pixel features. Validation of the obtained results was performed using the spectral unmixing fraction images and the 5.6 m classified LISS IV image.

  20. THE KEPLER PIXEL RESPONSE FUNCTION

    SciTech Connect

    Bryson, Stephen T.; Haas, Michael R.; Dotson, Jessie L.; Koch, David G.; Borucki, William J.; Tenenbaum, Peter; Jenkins, Jon M.; Chandrasekaran, Hema; Caldwell, Douglas A.; Klaus, Todd; Gilliland, Ronald L.

    2010-04-20

    Kepler seeks to detect sequences of transits of Earth-size exoplanets orbiting solar-like stars. Such transit signals are on the order of 100 ppm. The high photometric precision demanded by Kepler requires detailed knowledge of how the Kepler pixels respond to starlight during a nominal observation. This information is provided by the Kepler pixel response function (PRF), defined as the composite of Kepler's optical point-spread function, integrated spacecraft pointing jitter during a nominal cadence and other systematic effects. To provide sub-pixel resolution, the PRF is represented as a piecewise-continuous polynomial on a sub-pixel mesh. This continuous representation allows the prediction of a star's flux value on any pixel given the star's pixel position. The advantages and difficulties of this polynomial representation are discussed, including characterization of spatial variation in the PRF and the smoothing of discontinuities between sub-pixel polynomial patches. On-orbit super-resolution measurements of the PRF across the Kepler field of view are described. Two uses of the PRF are presented: the selection of pixels for each star that maximizes the photometric signal-to-noise ratio for that star, and PRF-fitted centroids which provide robust and accurate stellar positions on the CCD, primarily used for attitude and plate scale tracking. Good knowledge of the PRF has been a critical component for the successful collection of high-precision photometry by Kepler.

  1. Pixel size adjustment in coherent diffractive imaging within the Rayleigh-Sommerfeld regime.

    PubMed

    Claus, Daniel; Rodenburg, John Marius

    2015-03-10

    The reconstruction of the smallest resolvable object detail in digital holography and coherent diffractive imaging when the detector is mounted close to the object of interest is restricted by the sensor's pixel size. Very high resolution information is intrinsically encoded in the data because the effective numerical aperture (NA) of the detector (its solid angular size as subtended at the object plane) is very high. The correct physical propagation model to use in the reconstruction process for this setup should be based on the Rayleigh-Sommerfeld diffraction integral, which is commonly implemented via a convolution operation. However, the convolution operation has the drawback that the pixel size of the propagation calculation is preserved between the object and the detector, and so the maximum resolution of the reconstruction is limited by the detector pixel size, not its effective NA. Here we show that this problem can be overcome via the introduction of a numerical spherical lens with adjustable magnification. This approach enables the reconstruction of object details smaller than the detector pixel size or of objects that extend beyond the size of the detector. It will have applications in all forms of near-field lensless microscopy.

  2. Convolutional fountain distribution over fading wireless channels

    NASA Astrophysics Data System (ADS)

    Usman, Mohammed

    2012-08-01

    Mobile broadband has opened the possibility of a rich variety of services to end users. Broadcast/multicast of multimedia data is one such service which can be used to deliver multimedia to multiple users economically. However, the radio channel poses serious challenges due to its time-varying properties, resulting in each user experiencing different channel characteristics, independent of other users. Conventional methods of achieving reliability in communication, such as automatic repeat request and forward error correction do not scale well in a broadcast/multicast scenario over radio channels. Fountain codes, being rateless and information additive, overcome these problems. Although the design of fountain codes makes it possible to generate an infinite sequence of encoded symbols, the erroneous nature of radio channels mandates the need for protecting the fountain-encoded symbols, so that the transmission is feasible. In this article, the performance of fountain codes in combination with convolutional codes, when used over radio channels, is presented. An investigation of various parameters, such as goodput, delay and buffer size requirements, pertaining to the performance of fountain codes in a multimedia broadcast/multicast environment is presented. Finally, a strategy for the use of 'convolutional fountain' over radio channels is also presented.

  3. Convolution Inequalities for the Boltzmann Collision Operator

    NASA Astrophysics Data System (ADS)

    Alonso, Ricardo J.; Carneiro, Emanuel; Gamba, Irene M.

    2010-09-01

    We study integrability properties of a general version of the Boltzmann collision operator for hard and soft potentials in n-dimensions. A reformulation of the collisional integrals allows us to write the weak form of the collision operator as a weighted convolution, where the weight is given by an operator invariant under rotations. Using a symmetrization technique in L p we prove a Young’s inequality for hard potentials, which is sharp for Maxwell molecules in the L 2 case. Further, we find a new Hardy-Littlewood-Sobolev type of inequality for Boltzmann collision integrals with soft potentials. The same method extends to radially symmetric, non-increasing potentials that lie in some {Ls_{weak}} or L s . The method we use resembles a Brascamp, Lieb and Luttinger approach for multilinear weighted convolution inequalities and follows a weak formulation setting. Consequently, it is closely connected to the classical analysis of Young and Hardy-Littlewood-Sobolev inequalities. In all cases, the inequality constants are explicitly given by formulas depending on integrability conditions of the angular cross section (in the spirit of Grad cut-off). As an additional application of the technique we also obtain estimates with exponential weights for hard potentials in both conservative and dissipative interactions.

  4. Experimental Investigation of Convoluted Contouring for Aircraft Afterbody Drag Reduction

    NASA Technical Reports Server (NTRS)

    Deere, Karen A.; Hunter, Craig A.

    1999-01-01

    An experimental investigation was performed in the NASA Langley 16-Foot Transonic Tunnel to determine the aerodynamic effects of external convolutions, placed on the boattail of a nonaxisymmetric nozzle for drag reduction. Boattail angles of 15 and 22 were tested with convolutions placed at a forward location upstream of the boattail curvature, at a mid location along the curvature and at a full location that spanned the entire boattail flap. Each of the baseline nozzle afterbodies (no convolutions) had a parabolic, converging contour with a parabolically decreasing corner radius. Data were obtained at several Mach numbers from static conditions to 1.2 for a range of nozzle pressure ratios and angles of attack. An oil paint flow visualization technique was used to qualitatively assess the effect of the convolutions. Results indicate that afterbody drag reduction by convoluted contouring is convolution location, Mach number, boattail angle, and NPR dependent. The forward convolution location was the most effective contouring geometry for drag reduction on the 22 afterbody, but was only effective for M < 0.95. At M = 0.8, drag was reduced 20 and 36 percent at NPRs of 5.4 and 7, respectively, but drag was increased 10 percent for M = 0.95 at NPR = 7. Convoluted contouring along the 15 boattail angle afterbody was not effective at reducing drag because the flow was minimally separated from the baseline afterbody, unlike the massive separation along the 22 boattail angle baseline afterbody.

  5. New quantum MDS-convolutional codes derived from constacyclic codes

    NASA Astrophysics Data System (ADS)

    Li, Fengwei; Yue, Qin

    2015-12-01

    In this paper, we utilize a family of Hermitian dual-containing constacyclic codes to construct classical and quantum MDS convolutional codes. Our classical and quantum convolutional codes are optimal in the sense that they attain the classical (quantum) generalized Singleton bound.

  6. From Pixels to Planets

    NASA Technical Reports Server (NTRS)

    Brownston, Lee; Jenkins, Jon M.

    2015-01-01

    The Kepler Mission was launched in 2009 as NASAs first mission capable of finding Earth-size planets in the habitable zone of Sun-like stars. Its telescope consists of a 1.5-m primary mirror and a 0.95-m aperture. The 42 charge-coupled devices in its focal plane are read out every half hour, compressed, and then downlinked monthly. After four years, the second of four reaction wheels failed, ending the original mission. Back on earth, the Science Operations Center developed the Science Pipeline to analyze about 200,000 target stars in Keplers field of view, looking for evidence of periodic dimming suggesting that one or more planets had crossed the face of its host star. The Pipeline comprises several steps, from pixel-level calibration, through noise and artifact removal, to detection of transit-like signals and the construction of a suite of diagnostic tests to guard against false positives. The Kepler Science Pipeline consists of a pipeline infrastructure written in the Java programming language, which marshals data input to and output from MATLAB applications that are executed as external processes. The pipeline modules, which underwent continuous development and refinement even after data started arriving, employ several analytic techniques, many developed for the Kepler Project. Because of the large number of targets, the large amount of data per target and the complexity of the pipeline algorithms, the processing demands are daunting. Some pipeline modules require days to weeks to process all of their targets, even when run on NASA's 128-node Pleiades supercomputer. The software developers are still seeking ways to increase the throughput. To date, the Kepler project has discovered more than 4000 planetary candidates, of which more than 1000 have been independently confirmed or validated to be exoplanets. Funding for this mission is provided by NASAs Science Mission Directorate.

  7. Pixel-based reconstruction (PBR) promising simultaneous techniques for CT reconstructions.

    PubMed

    Fager, R S; Peddanarappagari, K V; Kumar, G N

    1993-01-01

    Algorithms belonging to the class of pixel-based reconstruction (PBR) algorithms, which are similar to simultaneous iterative reconstruction techniques (SIRTs) for reconstruction of objects from their fan beam projections in X-ray transmission tomography, are discussed. The general logic of these algorithms is discussed. Simulation studies indicate that, contrary to previous results with parallel beam projections, the iterative algebraic algorithms do not diverge when a more logical technique of obtaining the pseudoprojections is used. These simulations were carried out under conditions in which the number of object pixels exceeded (double) the number of detector pixel readings, i.e., the equations were highly underdetermined. The effect of the number of projections on the reconstruction and the convergence (empirical) to the exact solution is shown. For comparison, the reconstructions obtained by convolution backprojection are also given.

  8. Convolutional neural network for pottery retrieval

    NASA Astrophysics Data System (ADS)

    Benhabiles, Halim; Tabia, Hedi

    2017-01-01

    The effectiveness of the convolutional neural network (CNN) has already been demonstrated in many challenging tasks of computer vision, such as image retrieval, action recognition, and object classification. This paper specifically exploits CNN to design local descriptors for content-based retrieval of complete or nearly complete three-dimensional (3-D) vessel replicas. Based on vector quantization, the designed descriptors are clustered to form a shape vocabulary. Then, each 3-D object is associated to a set of clusters (words) in that vocabulary. Finally, a weighted vector counting the occurrences of every word is computed. The reported experimental results on the 3-D pottery benchmark show the superior performance of the proposed method.

  9. Robust smile detection using convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Bianco, Simone; Celona, Luigi; Schettini, Raimondo

    2016-11-01

    We present a fully automated approach for smile detection. Faces are detected using a multiview face detector and aligned and scaled using automatically detected eye locations. Then, we use a convolutional neural network (CNN) to determine whether it is a smiling face or not. To this end, we investigate different shallow CNN architectures that can be trained even when the amount of learning data is limited. We evaluate our complete processing pipeline on the largest publicly available image database for smile detection in an uncontrolled scenario. We investigate the robustness of the method to different kinds of geometric transformations (rotation, translation, and scaling) due to imprecise face localization, and to several kinds of distortions (compression, noise, and blur). To the best of our knowledge, this is the first time that this type of investigation has been performed for smile detection. Experimental results show that our proposal outperforms state-of-the-art methods on both high- and low-quality images.

  10. Object class segmentation of RGB-D video using recurrent convolutional neural networks.

    PubMed

    Pavel, Mircea Serban; Schulz, Hannes; Behnke, Sven

    2017-04-01

    Object class segmentation is a computer vision task which requires labeling each pixel of an image with the class of the object it belongs to. Deep convolutional neural networks (DNN) are able to learn and take advantage of local spatial correlations required for this task. They are, however, restricted by their small, fixed-sized filters, which limits their ability to learn long-range dependencies. Recurrent Neural Networks (RNN), on the other hand, do not suffer from this restriction. Their iterative interpretation allows them to model long-range dependencies by propagating activity. This property is especially useful when labeling video sequences, where both spatial and temporal long-range dependencies occur. In this work, a novel RNN architecture for object class segmentation is presented. We investigate several ways to train such a network. We evaluate our models on the challenging NYU Depth v2 dataset for object class segmentation and obtain competitive results.

  11. Crosstalk characterization of PMD pixels using the spatial response function at subpixel level

    NASA Astrophysics Data System (ADS)

    Heredia Conde, Miguel; Hartmann, Klaus; Loffeld, Otmar

    2015-03-01

    Time-of-Flight cameras have become one of the most widely-spread low-cost 3D-sensing devices. Most of them do not actually measure the time the light needs to hit an object and come back to the camera, but the difference of phase with respect to a reference signal. This requires special pixels with complex spatial structure, such as PMD pixels, able to sample the cross-correlation function between the incoming signal, reflected by the scene, and the reference signal. The complex structure, together with the presence of in-pixel electronics and the need for a compact readout circuitry for both pixel channels, suggests that systematic crosstalk effects will come up in this kind of devices. For the first time, we take profit of recent results on subpixel spatial responses of PMD pixels to detect and characterize crosstalk occurrences. Well-defined crosstalk patterns have been identified and quantitatively characterized through integration of the inter-pixel spatial response over each sensitive area. We cast the crosstalk problem into an image convolution and provide deconvolution kernels for cleaning PMD raw images from crosstalk. Experiments on real PMD raw images show that our results can be used to undo the lowpass filtering caused by crosstalk in high contrast image areas. The application of our kernels to undo crosstalk effects leads to reductions of the depth RMSE up to 50% in critical areas.

  12. Local Pixel Bundles: Bringing the Pixels to the People

    NASA Astrophysics Data System (ADS)

    Anderson, Jay

    2014-12-01

    The automated galaxy-based alignment software package developed for the Frontier Fields program (hst2galign, see Anderson & Ogaz 2014 and http://www.stsci.edu/hst/campaigns/frontier-fields/) produces a direct mapping from the pixels of the flt frame of each science exposure into a common master frame. We can use these mappings to extract the flt-pixels in the vicinity of a source of interest and package them into a convenient "bundle". In addition to the pixels, this data bundle can also contain "meta" information that will allow users to transform positions from the flt pixels to the reference frame and vice-versa. Since the un-resampled pixels in the flt frames are the only true constraints we have on the astronomical scene, the ability to inter-relate these pixels will enable many high-precision studies, such as: point-source-fitting and deconvolution with accurate PSFs, easy exploration of different image-combining algorithms, and accurate faint-source finding and photometry. The data products introduced in this ISR are a very early attempt to provide the flt-level pixel constraints in a package that is accessible to more than the handful of experts in HST astrometry. The hope is that users in the community might begin using them and will provide feedback as to what information they might want to see in the bundles and what general analysis packages they might find useful. For that reason, this document is somewhat informally written, since I know that it will be modified and updated as the products and tools are optimized.

  13. Intra-pixel response of infrared detector arrays for JWST

    NASA Astrophysics Data System (ADS)

    Hardy, Tim; Baril, M. R.; Pazder, J.; Stilburn, J. S.

    2008-07-01

    The near-infrared instruments on the James Webb Space Telescope will use 5 micron cutoff HAWAII-2RG detector arrays. We have investigated the response of this type of detector at sub-pixel resolution to determine whether variations at this scale would affect the performance of the instruments. Using a simple experimental setup we were able to get measurements with a resolution of approximately 4 microns. We have measured an un-hybridized HAWAII-1RG multiplexer, a hybridized HAWAII-1RG device with a 5 micron cutoff HgCdTe detector layer, and a hybridized HAWAII-2RG device with a 5 micron cutoff substrate-removed HgCdTe detector layer. We found that the intra-pixel response functions of the hybrid devices are basically smooth and well behaved, and vary little from pixel to pixel. However, we did find numerous sub-pixel sized defects, notably some long straight thin features like scratches. We were not able to detect any significant variations with wavelength between 0.65 and 2.2 microns, but in the -1RG device there was a variation with temperature. When cooled from 80K to 40K, the pixel response became narrower, and some signal began to be lost at the edges of the pixel. We believe this reflects a reduction in charge diffusion at the lower temperature.

  14. Image quality of mixed convolution kernel in thoracic computed tomography.

    PubMed

    Neubauer, Jakob; Spira, Eva Maria; Strube, Juliane; Langer, Mathias; Voss, Christian; Kotter, Elmar

    2016-11-01

    The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images.Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likert scale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test.Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P < 0.03). Compared to the hard convolution kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilar lymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P < 0.004) but a lower image quality for trachea, segmental bronchi, lung parenchyma, and skeleton (P < 0.001).The mixed convolution kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT.

  15. Painting with pixels.

    PubMed

    Kyte, S

    1989-04-01

    Two decades ago the subject of computer graphics was regarded as pure science fiction, more within the realms of Star Trek fantasy than of everyday use, but today it is difficult to avoid its influence. Television programmes abound with slick moving, twisting, distorting images, the printing media throws colourful shapes and forms off the page at you, and computer games explode noisily into our living rooms. In a very short space of time computer graphics have risen from being a toy of the affluent minority to a working tool of the cost-conscious majority. Even the most purist of artists have realized that in order to survive in an increasingly competitive world they must inevitably take the plunge into the world of electronic imagery.

  16. Output-sensitive 3D line integral convolution.

    PubMed

    Falk, Martin; Weiskopf, Daniel

    2008-01-01

    We propose an output-sensitive visualization method for 3D line integral convolution (LIC) whose rendering speed is largely independent of the data set size and mostly governed by the complexity of the output on the image plane. Our approach of view-dependent visualization tightly links the LIC generation with the volume rendering of the LIC result in order to avoid the computation of unnecessary LIC points: early-ray termination and empty-space leaping techniques are used to skip the computation of the LIC integral in a lazy-evaluation approach; both ray casting and texture slicing can be used as volume-rendering techniques. The input noise is modeled in object space to allow for temporal coherence under object and camera motion. Different noise models are discussed, covering dense representations based on filtered white noise all the way to sparse representations similar to oriented LIC. Aliasing artifacts are avoided by frequency control over the 3D noise and by employing a 3D variant of MIPmapping. A range of illumination models is applied to the LIC streamlines: different codimension-2 lighting models and a novel gradient-based illumination model that relies on precomputed gradients and does not require any direct calculation of gradients after the LIC integral is evaluated. We discuss the issue of proper sampling of the LIC and volume-rendering integrals by employing a frequency-space analysis of the noise model and the precomputed gradients. Finally, we demonstrate that our visualization approach lends itself to a fast graphics processing unit (GPU) implementation that supports both steady and unsteady flow. Therefore, this 3D LIC method allows users to interactively explore 3D flow by means of high-quality, view-dependent, and adaptive LIC volume visualization. Applications to flow visualization in combination with feature extraction and focus-and-context visualization are described, a comparison to previous methods is provided, and a detailed performance

  17. Convolution modeling of two-domain, nonlinear water-level responses in karst aquifers (Invited)

    NASA Astrophysics Data System (ADS)

    Long, A. J.

    2009-12-01

    Convolution modeling is a useful method for simulating the hydraulic response of water levels to sinking streamflow or precipitation infiltration at the macro scale. This approach is particularly useful in karst aquifers, where the complex geometry of the conduit and pore network is not well characterized but can be represented approximately by a parametric impulse-response function (IRF) with very few parameters. For many applications, one-dimensional convolution models can be equally effective as complex two- or three-dimensional models for analyzing water-level responses to recharge. Moreover, convolution models are well suited for identifying and characterizing the distinct domains of quick flow and slow flow (e.g., conduit flow and diffuse flow). Two superposed lognormal functions were used in the IRF to approximate the impulses of the two flow domains. Nonlinear response characteristics of the flow domains were assessed by observing temporal changes in the IRFs. Precipitation infiltration was simulated by filtering the daily rainfall record with a backward-in-time exponential function that weights each day’s rainfall with the rainfall of previous days and thus accounts for the effects of soil moisture on aquifer infiltration. The model was applied to the Edwards aquifer in Texas and the Madison aquifer in South Dakota. Simulations of both aquifers showed similar characteristics, including a separation on the order of years between the quick-flow and slow-flow IRF peaks and temporal changes in the IRF shapes when water levels increased and empty pore spaces became saturated.

  18. Programmable convolution via the chirp Z-transform with CCD's

    NASA Technical Reports Server (NTRS)

    Buss, D. D.

    1977-01-01

    Technique filtering by convolution in frequency domain rather than in time domain presents possible solution to problem of programmable transversal filters. Process is accomplished through utilization of chip z-transform (CZT) with charge-coupled devices

  19. Metaheuristic Algorithms for Convolution Neural Network

    PubMed Central

    Fanany, Mohamad Ivan; Arymurthy, Aniati Murni

    2016-01-01

    A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry. However, implementation strategy of metaheuristic for accuracy improvement on convolution neural networks (CNN), a famous deep learning method, is still rarely investigated. Deep learning relates to a type of machine learning technique, where its aim is to move closer to the goal of artificial intelligence of creating a machine that could successfully perform any intellectual tasks that can be carried out by a human. In this paper, we propose the implementation strategy of three popular metaheuristic approaches, that is, simulated annealing, differential evolution, and harmony search, to optimize CNN. The performances of these metaheuristic methods in optimizing CNN on classifying MNIST and CIFAR dataset were evaluated and compared. Furthermore, the proposed methods are also compared with the original CNN. Although the proposed methods show an increase in the computation time, their accuracy has also been improved (up to 7.14 percent). PMID:27375738

  20. Accelerated unsteady flow line integral convolution.

    PubMed

    Liu, Zhanping; Moorhead, Robert J

    2005-01-01

    Unsteady flow line integral convolution (UFLIC) is a texture synthesis technique for visualizing unsteady flows with high temporal-spatial coherence. Unfortunately, UFLIC requires considerable time to generate each frame due to the huge amount of pathline integration that is computed for particle value scattering. This paper presents Accelerated UFLIC (AUFLIC) for near interactive (1 frame/second) visualization with 160,000 particles per frame. AUFLIC reuses pathlines in the value scattering process to reduce computationally expensive pathline integration. A flow-driven seeding strategy is employed to distribute seeds such that only a few of them need pathline integration while most seeds are placed along the pathlines advected at earlier times by other seeds upstream and, therefore, the known pathlines can be reused for fast value scattering. To maintain a dense scattering coverage to convey high temporal-spatial coherence while keeping the expense of pathline integration low, a dynamic seeding controller is designed to decide whether to advect, copy, or reuse a pathline. At a negligible memory cost, AUFLIC is 9 times faster than UFLIC with comparable image quality.

  1. Convolution kernels for multi-wavelength imaging

    NASA Astrophysics Data System (ADS)

    Boucaud, A.; Bocchio, M.; Abergel, A.; Orieux, F.; Dole, H.; Hadj-Youcef, M. A.

    2016-12-01

    Astrophysical images issued from different instruments and/or spectral bands often require to be processed together, either for fitting or comparison purposes. However each image is affected by an instrumental response, also known as point-spread function (PSF), that depends on the characteristics of the instrument as well as the wavelength and the observing strategy. Given the knowledge of the PSF in each band, a straightforward way of processing images is to homogenise them all to a target PSF using convolution kernels, so that they appear as if they had been acquired by the same instrument. We propose an algorithm that generates such PSF-matching kernels, based on Wiener filtering with a tunable regularisation parameter. This method ensures all anisotropic features in the PSFs to be taken into account. We compare our method to existing procedures using measured Herschel/PACS and SPIRE PSFs and simulated JWST/MIRI PSFs. Significant gains up to two orders of magnitude are obtained with respect to the use of kernels computed assuming Gaussian or circularised PSFs. A software to compute these kernels is available at https://github.com/aboucaud/pypher

  2. Event Discrimination using Convolutional Neural Networks

    NASA Astrophysics Data System (ADS)

    Menon, Hareesh; Hughes, Richard; Daling, Alec; Winer, Brian

    2017-01-01

    Convolutional Neural Networks (CNNs) are computational models that have been shown to be effective at classifying different types of images. We present a method to use CNNs to distinguish events involving the production of a top quark pair and a Higgs boson from events involving the production of a top quark pair and several quark and gluon jets. To do this, we generate and simulate data using MADGRAPH and DELPHES for a general purpose LHC detector at 13 TeV. We produce images using a particle flow algorithm by binning the particles geometrically based on their position in the detector and weighting the bins by the energy of each particle within each bin, and by defining channels based on particle types (charged track, neutral hadronic, neutral EM, lepton, heavy flavor). Our classification results are competitive with standard machine learning techniques. We have also looked into the classification of the substructure of the events, in a process known as scene labeling. In this context, we look for the presence of boosted objects (such as top quarks) with substructure encompassed within single jets. Preliminary results on substructure classification will be presented.

  3. Edge pixel response studies of edgeless silicon sensor technology for pixellated imaging detectors

    NASA Astrophysics Data System (ADS)

    Maneuski, D.; Bates, R.; Blue, A.; Buttar, C.; Doonan, K.; Eklund, L.; Gimenez, E. N.; Hynds, D.; Kachkanov, S.; Kalliopuska, J.; McMullen, T.; O'Shea, V.; Tartoni, N.; Plackett, R.; Vahanen, S.; Wraight, K.

    2015-03-01

    Silicon sensor technologies with reduced dead area at the sensor's perimeter are under development at a number of institutes. Several fabrication methods for sensors which are sensitive close to the physical edge of the device are under investigation utilising techniques such as active-edges, passivated edges and current-terminating rings. Such technologies offer the goal of a seamlessly tiled detection surface with minimum dead space between the individual modules. In order to quantify the performance of different geometries and different bulk and implant types, characterisation of several sensors fabricated using active-edge technology were performed at the B16 beam line of the Diamond Light Source. The sensors were fabricated by VTT and bump-bonded to Timepix ROICs. They were 100 and 200 μ m thick sensors, with the last pixel-to-edge distance of either 50 or 100 μ m. The sensors were fabricated as either n-on-n or n-on-p type devices. Using 15 keV monochromatic X-rays with a beam spot of 2.5 μ m, the performance at the outer edge and corners pixels of the sensors was evaluated at three bias voltages. The results indicate a significant change in the charge collection properties between the edge and 5th (up to 275 μ m) from edge pixel for the 200 μ m thick n-on-n sensor. The edge pixel performance of the 100 μ m thick n-on-p sensors is affected only for the last two pixels (up to 110 μ m) subject to biasing conditions. Imaging characteristics of all sensor types investigated are stable over time and the non-uniformities can be minimised by flat-field corrections. The results from the synchrotron tests combined with lab measurements are presented along with an explanation of the observed effects.

  4. Pixel response function experimental techniques and analysis of active pixel sensor star cameras

    NASA Astrophysics Data System (ADS)

    Fumo, Patrick; Waldron, Erik; Laine, Juha-Pekka; Evans, Gary

    2015-04-01

    The pixel response function (PRF) of a pixel within a focal plane is defined as the pixel intensity with respect to the position of a point source within the pixel. One of its main applications is in the field of astrometry, which is a branch of astronomy that deals with positioning data of a celestial body for tracking movement or adjusting the attitude of a spacecraft. Complementary metal oxide semiconductor (CMOS) image sensors generally offer better radiation tolerance to protons and heavy ions than CCDs making them ideal candidates for space applications aboard satellites, but like all image sensors they are limited by their spatial frequency response, better known as the modulation transfer function. Having a well-calibrated PRF allows us to eliminate some of the uncertainty in the spatial response of the system providing better resolution and a more accurate centroid estimation. This paper describes the experimental setup for determining the PRF of a CMOS image sensor and analyzes the effect on the oversampled point spread function (PSF) of an image intensifier, as well as the effects due to the wavelength of light used as a point source. It was found that using electron bombarded active pixel sensor (EBAPS) intensification technology had a significant impact on the PRF of the camera being tested as a result of an increase in the amount of carrier diffusion between collection sites generated by the intensification process. Taking the full width at half maximum (FWHM) of the resulting data, it was found that the intensified version of a CMOS camera exhibited a PSF roughly 16.42% larger than its nonintensified counterpart.

  5. Single image depth estimation based on convolutional neural network and sparse connected conditional random field

    NASA Astrophysics Data System (ADS)

    Zhu, Leqing; Wang, Xun; Wang, Dadong; Wang, Huiyan

    2016-10-01

    Deep convolutional neural networks (DCNNs) have attracted significant interest in the computer vision community in the recent years and have exhibited high performance in resolving many computer vision problems, such as image classification. We address the pixel-level depth prediction from a single image by combining DCNN and sparse connected conditional random field (CRF). Owing to the invariance properties of DCNNs that make them suitable for high-level tasks, their outputs are generally not localized enough for detailed pixel-level regression. A multiscale DCNN and sparse connected CRF are combined to overcome this localization weakness. We have evaluated our framework using the well-known NYU V2 depth dataset, and the results show that the proposed method can improve the depth prediction accuracy both qualitatively and quantitatively, as compared to previous works. This finding shows the potential use of the proposed method in three-dimensional (3-D) modeling or 3-D video production from the given two-dimensional (2-D) images or 2-D videos.

  6. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Scene Segmentation.

    PubMed

    Badrinarayanan, Vijay; Kendall, Alex; Cipolla, Roberto

    2017-01-02

    We present a novel and practical deep fully convolutional neural network architecture for semantic pixel-wise segmentation termed SegNet. This core trainable segmentation engine consists of an encoder network, a corresponding decoder network followed by a pixel-wise classification layer. The architecture of the encoder network is topologically identical to the 13 convolutional layers in the VGG16 network [1]. The role of the decoder network is to map the low resolution encoder feature maps to full input resolution feature maps for pixel-wise classification. The novelty of SegNet lies is in the manner in which the decoder upsamples its lower resolution input feature map(s). Specifically, the decoder uses pooling indices computed in the max-pooling step of the corresponding encoder to perform non-linear upsampling. This eliminates the need for learning to upsample. The upsampled maps are sparse and are then convolved with trainable filters to produce dense feature maps. We compare our proposed architecture with the widely adopted FCN [2] and also with the well known DeepLab-LargeFOV [3], DeconvNet [4] architectures. This comparison reveals the memory versus accuracy trade-off involved in achieving good segmentation performance. SegNet was primarily motivated by scene understanding applications. Hence, it is designed to be efficient both in terms of memory and computational time during inference. It is also significantly smaller in the number of trainable parameters than other competing architectures and can be trained end-to-end using stochastic gradient descent. We also performed a controlled benchmark of SegNet and other architectures on both road scenes and SUN RGB-D indoor scene segmentation tasks. These quantitative assessments show that SegNet provides good performance with competitive inference time and most efficient inference memory-wise as compared to other architectures. We also provide a Caffe implementation of SegNet and a web demo at http://mi.eng.cam.ac.uk/projects/segnet/.

  7. WFC3 Pixel Area Maps

    NASA Astrophysics Data System (ADS)

    Kalirai, J. S.; Cox, C.; Dressel, L.; Fruchter, A.; Hack, W.; Kozhurina-Platais, V.; Mack, J.

    2010-04-01

    We present the pixel area maps (PAMs) for the WFC3/UVIS and WFC3/IR detectors, and discuss the normalization of these images. HST processed flt images suffer from geometric distortion and therefore have pixel areas that vary on the sky. The counts (electrons) measured for a source on these images depends on the position of the source on the detector, an effect that is implicitly corrected when these images are multidrizzled into drz files. The flt images can be multiplied by the PAMs to yield correct and uniform counts for a given source irrespective of its location on the image. To ensure consistency between the count rate measured for sources in drz images and near the center of flt images, we set the normalization of the PAMs to unity at a reference pixel near the center of the UVIS mosaic and IR detector, and set the SCALE in the IDCTAB equal to the square root of the area of this reference pixel. The implications of this choice for photometric measurements are discussed.

  8. Colonoscopic polyp detection using convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Park, Sun Young; Sargent, Dusty

    2016-03-01

    Computer aided diagnosis (CAD) systems for medical image analysis rely on accurate and efficient feature extraction methods. Regardless of which type of classifier is used, the results will be limited if the input features are not diagnostically relevant and do not properly discriminate between the different classes of images. Thus, a large amount of research has been dedicated to creating feature sets that capture the salient features that physicians are able to observe in the images. Successful feature extraction reduces the semantic gap between the physician's interpretation and the computer representation of images, and helps to reduce the variability in diagnosis between physicians. Due to the complexity of many medical image classification tasks, feature extraction for each problem often requires domainspecific knowledge and a carefully constructed feature set for the specific type of images being classified. In this paper, we describe a method for automatic diagnostic feature extraction from colonoscopy images that may have general application and require a lower level of domain-specific knowledge. The work in this paper expands on our previous CAD algorithm for detecting polyps in colonoscopy video. In that work, we applied an eigenimage model to extract features representing polyps, normal tissue, diverticula, etc. from colonoscopy videos taken from various viewing angles and imaging conditions. Classification was performed using a conditional random field (CRF) model that accounted for the spatial and temporal adjacency relationships present in colonoscopy video. In this paper, we replace the eigenimage feature descriptor with features extracted from a convolutional neural network (CNN) trained to recognize the same image types in colonoscopy video. The CNN-derived features show greater invariance to viewing angles and image quality factors when compared to the eigenimage model. The CNN features are used as input to the CRF classifier as before. We report

  9. Space suit

    NASA Technical Reports Server (NTRS)

    Shepard, L. F.; Durney, G. P.; Case, M. C.; Kenneway, A. J., III; Wise, R. C.; Rinehart, D.; Bessette, R. J.; Pulling, R. C. (Inventor)

    1973-01-01

    A pressure suit for high altitude flights, particularly space missions is reported. The suit is designed for astronauts in the Apollo space program and may be worn both inside and outside a space vehicle, as well as on the lunar surface. It comprises an integrated assembly of inner comfort liner, intermediate pressure garment, and outer thermal protective garment with removable helmet, and gloves. The pressure garment comprises an inner convoluted sealing bladder and outer fabric restraint to which are attached a plurality of cable restraint assemblies. It provides versitility in combination with improved sealing and increased mobility for internal pressures suitable for life support in the near vacuum of outer space.

  10. Inequalities and consequences of new convolutions for the fractional Fourier transform with Hermite weights

    NASA Astrophysics Data System (ADS)

    Anh, P. K.; Castro, L. P.; Thao, P. T.; Tuan, N. M.

    2017-01-01

    This paper presents new convolutions for the fractional Fourier transform which are somehow associated with the Hermite functions. Consequent inequalities and properties are derived for these convolutions, among which we emphasize two new types of Young's convolution inequalities. The results guarantee a general framework where the present convolutions are well-defined, allowing larger possibilities than the known ones for other convolutions. Furthermore, we exemplify the use of our convolutions by providing explicit solutions of some classes of integral equations which appear in engineering problems.

  11. SAR Image Complex Pixel Representations

    SciTech Connect

    Doerry, Armin W.

    2015-03-01

    Complex pixel values for Synthetic Aperture Radar (SAR) images of uniform distributed clutter can be represented as either real/imaginary (also known as I/Q) values, or as Magnitude/Phase values. Generally, these component values are integers with limited number of bits. For clutter energy well below full-scale, Magnitude/Phase offers lower quantization noise than I/Q representation. Further improvement can be had with companding of the Magnitude value.

  12. Single-pixel hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Suo, Jinli; Wang, Yuwang; Bian, Liheng; Dai, Qionghai

    2016-10-01

    Conventional multispectral imaging methods detect photons of a 3D hyperspectral data cube separately either in the spatial or spectral dimension using array detectors, and are thus photon inefficient and spectrum range limited. Besides, they are usually bulky and highly expensive. To address these issues, this paper presents single-pixel multispectral imaging techniques, which are of high sensitivity, wide spectrum range, low cost and light weight. Two mechanisms are proposed, and experimental validation are also reported.

  13. A robust sub-pixel edge detection method of infrared image based on tremor-based retinal receptive field model

    NASA Astrophysics Data System (ADS)

    Gao, Kun; Yang, Hu; Chen, Xiaomei; Ni, Guoqiang

    2008-03-01

    Because of complex thermal objects in an infrared image, the prevalent image edge detection operators are often suitable for a certain scene and extract too wide edges sometimes. From a biological point of view, the image edge detection operators work reliably when assuming a convolution-based receptive field architecture. A DoG (Difference-of- Gaussians) model filter based on ON-center retinal ganglion cell receptive field architecture with artificial eye tremors introduced is proposed for the image contour detection. Aiming at the blurred edges of an infrared image, the subsequent orthogonal polynomial interpolation and sub-pixel level edge detection in rough edge pixel neighborhood is adopted to locate the foregoing rough edges in sub-pixel level. Numerical simulations show that this method can locate the target edge accurately and robustly.

  14. CMOS digital pixel sensors: technology and applications

    NASA Astrophysics Data System (ADS)

    Skorka, Orit; Joseph, Dileepan

    2014-04-01

    CMOS active pixel sensor technology, which is widely used these days for digital imaging, is based on analog pixels. Transition to digital pixel sensors can boost signal-to-noise ratios and enhance image quality, but can increase pixel area to dimensions that are impractical for the high-volume market of consumer electronic devices. There are two main approaches to digital pixel design. The first uses digitization methods that largely rely on photodetector properties and so are unique to imaging. The second is based on adaptation of a classical analog-to-digital converter (ADC) for in-pixel data conversion. Imaging systems for medical, industrial, and security applications are emerging lower-volume markets that can benefit from these in-pixel ADCs. With these applications, larger pixels are typically acceptable, and imaging may be done in invisible spectral bands.

  15. Error-trellis syndrome decoding techniques for convolutional codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1985-01-01

    An error-trellis syndrome decoding technique for convolutional codes is developed. This algorithm is then applied to the entire class of systematic convolutional codes and to the high-rate, Wyner-Ash convolutional codes. A special example of the one-error-correcting Wyner-Ash code, a rate 3/4 code, is treated. The error-trellis syndrome decoding method applied to this example shows in detail how much more efficient syndrome decordig is than Viterbi decoding if applied to the same problem. For standard Viterbi decoding, 64 states are required, whereas in the example only 7 states are needed. Also, within the 7 states required for decoding, many fewer transitions are needed between the states.

  16. Error-trellis Syndrome Decoding Techniques for Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1984-01-01

    An error-trellis syndrome decoding technique for convolutional codes is developed. This algorithm is then applied to the entire class of systematic convolutional codes and to the high-rate, Wyner-Ash convolutional codes. A special example of the one-error-correcting Wyner-Ash code, a rate 3/4 code, is treated. The error-trellis syndrome decoding method applied to this example shows in detail how much more efficient syndrome decoding is than Viterbi decoding if applied to the same problem. For standard Viterbi decoding, 64 states are required, whereas in the example only 7 states are needed. Also, within the 7 states required for decoding, many fewer transitions are needed between the states.

  17. Improving the full spectrum fitting method: accurate convolution with Gauss-Hermite functions

    NASA Astrophysics Data System (ADS)

    Cappellari, Michele

    2017-04-01

    I start by providing an updated summary of the penalized pixel-fitting (PPXF) method that is used to extract the stellar and gas kinematics, as well as the stellar population of galaxies, via full spectrum fitting. I then focus on the problem of extracting the kinematics when the velocity dispersion σ is smaller than the velocity sampling ΔV that is generally, by design, close to the instrumental dispersion σinst. The standard approach consists of convolving templates with a discretized kernel, while fitting for its parameters. This is obviously very inaccurate when σ ≲ ΔV/2, due to undersampling. Oversampling can prevent this, but it has drawbacks. Here I present a more accurate and efficient alternative. It avoids the evaluation of the undersampled kernel and instead directly computes its well-sampled analytic Fourier transform, for use with the convolution theorem. A simple analytic transform exists when the kernel is described by the popular Gauss-Hermite parametrization (which includes the Gaussian as special case) for the line-of-sight velocity distribution. I describe how this idea was implemented in a significant upgrade to the publicly available PPXF software. The key advantage of the new approach is that it provides accurate velocities regardless of σ. This is important e.g. for spectroscopic surveys targeting galaxies with σ ≪ σinst, for galaxy redshift determinations or for measuring line-of-sight velocities of individual stars. The proposed method could also be used to fix Gaussian convolution algorithms used in today's popular software packages.

  18. Mapping Electrical Crosstalk in Pixelated Sensor Arrays

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  19. Mapping Electrical Crosstalk in Pixelated Sensor Arrays

    NASA Technical Reports Server (NTRS)

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

    2017-01-01

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

  20. X-ray micro-beam characterization of a small pixel spectroscopic CdTe detector

    NASA Astrophysics Data System (ADS)

    Veale, M. C.; Bell, S. J.; Seller, P.; Wilson, M. D.; Kachkanov, V.

    2012-07-01

    A small pixel, spectroscopic, CdTe detector has been developed at the Rutherford Appleton Laboratory (RAL) for X-ray imaging applications. The detector consists of 80 × 80 pixels on a 250 μm pitch with 50 μm inter-pixel spacing. Measurements with an 241Am γ-source demonstrated that 96% of all pixels have a FWHM of better than 1 keV while the majority of the remaining pixels have FWHM of less than 4 keV. Using the Diamond Light Source synchrotron, a 10 μm collimated beam of monochromatic 20 keV X-rays has been used to map the spatial variation in the detector response and the effects of charge sharing corrections on detector efficiency and resolution. The mapping measurements revealed the presence of inclusions in the detector and quantified their effect on the spectroscopic resolution of pixels.

  1. Missing pixels restoration for remote sensing images using adaptive search window and linear regression

    NASA Astrophysics Data System (ADS)

    Tai, Shen-Chuan; Chen, Peng-Yu; Chao, Chian-Yen

    2016-07-01

    The Consultative Committee for Space Data Systems proposed an efficient image compression standard that can do lossless compression (CCSDS-ICS). CCSDS-ICS is the most widely utilized standard for satellite communications. However, the original CCSDS-ICS is weak in terms of error resilience with even a single incorrect bit possibly causing numerous missing pixels. A restoration algorithm based on the neighborhood similar pixel interpolator is proposed to fill in missing pixels. The linear regression model is used to generate the reference image from other panchromatic or multispectral images. Furthermore, an adaptive search window is utilized to sieve out similar pixels from the pixels in the search region defined in the neighborhood similar pixel interpolator. The experimental results show that the proposed methods are capable of reconstructing missing regions with good visual quality.

  2. Image Labeling for LIDAR Intensity Image Using K-Nn of Feature Obtained by Convolutional Neural Network

    NASA Astrophysics Data System (ADS)

    Umemura, Masaki; Hotta, Kazuhiro; Nonaka, Hideki; Oda, Kazuo

    2016-06-01

    We propose an image labeling method for LIDAR intensity image obtained by Mobile Mapping System (MMS) using K-Nearest Neighbor (KNN) of feature obtained by Convolutional Neural Network (CNN). Image labeling assigns labels (e.g., road, cross-walk and road shoulder) to semantic regions in an image. Since CNN is effective for various image recognition tasks, we try to use the feature of CNN (Caffenet) pre-trained by ImageNet. We use 4,096-dimensional feature at fc7 layer in the Caffenet as the descriptor of a region because the feature at fc7 layer has effective information for object classification. We extract the feature by the Caffenet from regions cropped from images. Since the similarity between features reflects the similarity of contents of regions, we can select top K similar regions cropped from training samples with a test region. Since regions in training images have manually-annotated ground truth labels, we vote the labels attached to top K similar regions to the test region. The class label with the maximum vote is assigned to each pixel in the test image. In experiments, we use 36 LIDAR intensity images with ground truth labels. We divide 36 images into training (28 images) and test sets (8 images). We use class average accuracy and pixel-wise accuracy as evaluation measures. Our method was able to assign the same label as human beings in 97.8% of the pixels in test LIDAR intensity images.

  3. Making a trillion pixels dance

    NASA Astrophysics Data System (ADS)

    Singh, Vivek; Hu, Bin; Toh, Kenny; Bollepalli, Srinivas; Wagner, Stephan; Borodovsky, Yan

    2008-03-01

    In June 2007, Intel announced a new pixelated mask technology. This technology was created to address the problem caused by the growing gap between the lithography wavelength and the feature sizes patterned with it. As this gap has increased, the quality of the image has deteriorated. About a decade ago, Optical Proximity Correction (OPC) was introduced to bridge this gap, but as this gap continued to increase, one could not rely on the same basic set of techniques to maintain image quality. The computational lithography group at Intel sought to alleviate this problem by experimenting with additional degrees of freedom within the mask. This paper describes the resulting pixelated mask technology, and some of the computational methods used to create it. The first key element of this technology is a thick mask model. We realized very early in the development that, unlike traditional OPC methods, the pixelated mask would require a very accurate thick mask model. Whereas in the traditional methods, one can use the relatively coarse approximations such as the boundary layer method, use of such techniques resulted not just in incorrect sizing of parts of the pattern, but in whole features missing. We built on top of previously published domain decomposition methods, and incorporated limitations of the mask manufacturing process, to create an accurate thick mask model. Several additional computational techniques were invoked to substantially increase the speed of this method to a point that it was feasible for full chip tapeout. A second key element of the computational scheme was the comprehension of mask manufacturability, including the vital issue of the number of colors in the mask. While it is obvious that use of three or more colors will give the best image, one has to be practical about projecting mask manufacturing capabilities for such a complex mask. To circumvent this serious issue, we eventually settled on a two color mask - comprising plain glass and etched

  4. Methods of editing cloud and atmospheric layer affected pixels from satellite data

    NASA Technical Reports Server (NTRS)

    Nixon, P. R. (Principal Investigator); Wiegand, C. L.; Richardson, A. J.; Johnson, M. P.; Goodier, B. G.

    1981-01-01

    The location and migration of cloud, land and water features were examined in spectral space (reflective VIS vs. emissive IR). Daytime HCMM data showed two distinct types of cloud affected pixels in the south Texas test area. High altitude cirrus and/or cirrostratus and "subvisible cirrus" (SCi) reflected the same or only slightly more than land features. In the emissive band, the digital counts ranged from 1 to over 75 and overlapped land features. Pixels consisting of cumulus clouds, or of mixed cumulus and landscape, clustered in a different area of spectral space than the high altitude cloud pixels. Cumulus affected pixels were more reflective than land and water pixels. In August the high altitude clouds and SCi were more emissive than similar clouds were in July. Four-channel TIROS-N data were examined with the objective of developing a multispectral screening technique for removing SCi contaminated data.

  5. Die and telescoping punch form convolutions in thin diaphragm

    NASA Technical Reports Server (NTRS)

    1965-01-01

    Die and punch set forms convolutions in thin dished metal diaphragm without stretching the metal too thin at sharp curvatures. The die corresponds to the metal shape to be formed, and the punch consists of elements that progressively slide against one another under the restraint of a compressed-air cushion to mate with the die.

  6. Stacked Convolutional Denoising Auto-Encoders for Feature Representation.

    PubMed

    Du, Bo; Xiong, Wei; Wu, Jia; Zhang, Lefei; Zhang, Liangpei; Tao, Dacheng

    2016-03-16

    Deep networks have achieved excellent performance in learning representation from visual data. However, the supervised deep models like convolutional neural network require large quantities of labeled data, which are very expensive to obtain. To solve this problem, this paper proposes an unsupervised deep network, called the stacked convolutional denoising auto-encoders, which can map images to hierarchical representations without any label information. The network, optimized by layer-wise training, is constructed by stacking layers of denoising auto-encoders in a convolutional way. In each layer, high dimensional feature maps are generated by convolving features of the lower layer with kernels learned by a denoising auto-encoder. The auto-encoder is trained on patches extracted from feature maps in the lower layer to learn robust feature detectors. To better train the large network, a layer-wise whitening technique is introduced into the model. Before each convolutional layer, a whitening layer is embedded to sphere the input data. By layers of mapping, raw images are transformed into high-level feature representations which would boost the performance of the subsequent support vector machine classifier. The proposed algorithm is evaluated by extensive experimentations and demonstrates superior classification performance to state-of-the-art unsupervised networks.

  7. Active pixel sensor with intra-pixel charge transfer

    NASA Technical Reports Server (NTRS)

    Fossum, Eric R. (Inventor); Mendis, Sunetra (Inventor); Kemeny, Sabrina E. (Inventor)

    1995-01-01

    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, a readout circuit including at least an output field effect transistor formed in the substrate, and a charge coupled device section formed on the substrate adjacent the photogate having a sensing node connected to the output transistor and at least one charge coupled device stage for transferring charge from the underlying portion of the substrate to the sensing node.

  8. Active pixel sensor with intra-pixel charge transfer

    NASA Technical Reports Server (NTRS)

    Fossum, Eric R. (Inventor); Mendis, Sunetra (Inventor); Kemeny, Sabrina E. (Inventor)

    2003-01-01

    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, a readout circuit including at least an output field effect transistor formed in the substrate, and a charge coupled device section formed on the substrate adjacent the photogate having a sensing node connected to the output transistor and at least one charge coupled device stage for transferring charge from the underlying portion of the substrate to the sensing node.

  9. Active pixel sensor with intra-pixel charge transfer

    NASA Technical Reports Server (NTRS)

    Fossum, Eric R. (Inventor); Mendis, Sunetra (Inventor); Kemeny, Sabrina E. (Inventor)

    2004-01-01

    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, a readout circuit including at least an output field effect transistor formed in the substrate, and a charge coupled device section formed on the substrate adjacent the photogate having a sensing node connected to the output transistor and at least one charge coupled device stage for transferring charge from the underlying portion of the substrate to the sensing node.

  10. Proceedings of PIXEL98 -- International pixel detector workshop

    SciTech Connect

    Anderson, D.F.; Kwan, S.

    1998-08-01

    Experiments around the globe face new challenges of more precision in the face of higher interaction rates, greater track densities, and higher radiation doses, as they look for rarer and rarer processes, leading many to incorporate pixelated solid-state detectors into their plans. The highest-readout rate devices require new technologies for implementation. This workshop reviewed recent, significant progress in meeting these technical challenges. Participants presented many new results; many of them from the weeks--even days--just before the workshop. Brand new at this workshop were results on cryogenic operation of radiation-damaged silicon detectors (dubbed the Lazarus effect). Other new work included a diamond sensor with 280-micron collection distance; new results on breakdown in p-type silicon detectors; testing of the latest versions of read-out chip and interconnection designs; and the radiation hardness of deep-submicron processes.

  11. Serial Pixel Analog-to-Digital Converter

    SciTech Connect

    Larson, E D

    2010-02-01

    This method reduces the data path from the counter to the pixel register of the analog-to-digital converter (ADC) from as many as 10 bits to a single bit. The reduction in data path width is accomplished by using a coded serial data stream similar to a pseudo random number (PRN) generator. The resulting encoded pixel data is then decoded into a standard hexadecimal format before storage. The high-speed serial pixel ADC concept is based on the single-slope integrating pixel ADC architecture. Previous work has described a massively parallel pixel readout of a similar architecture. The serial ADC connection is similar to the state-of-the art method with the exception that the pixel ADC register is a shift register and the data path is a single bit. A state-of-the-art individual-pixel ADC uses a single-slope charge integration converter architecture with integral registers and “one-hot” counters. This implies that parallel data bits are routed among the counter and the individual on-chip pixel ADC registers. The data path bit-width to the pixel is therefore equivalent to the pixel ADC bit resolution.

  12. Characterization of Pixelated Cadmium-Zinc-Telluride Detectors for Astrophysical Applications

    NASA Technical Reports Server (NTRS)

    Gaskin, Jessica; Sharma, Dharma; Ramsey, Brian; Seller, Paul

    2003-01-01

    Comparisons of charge sharing and charge loss measurements between two pixelated Cadmium-Zinc-Telluride (CdZnTe) detectors are discussed. These properties along with the detector geometry help to define the limiting energy resolution and spatial resolution of the detector in question. The first detector consists of a 1-mm-thick piece of CdZnTe sputtered with a 4x4 array of pixels with pixel pitch of 750 microns (inter-pixel gap is 100 microns). Signal readout is via discrete ultra-low-noise preamplifiers, one for each of the 16 pixels. The second detector consists of a 2-mm-thick piece of CdZnTe sputtered with a 16x16 array of pixels with a pixel pitch of 300 microns (inter-pixel gap is 50 microns). This crystal is bonded to a custom-built readout chip (ASIC) providing all front-end electronics to each of the 256 independent pixels. These detectors act as precursors to that which will be used at the focal plane of the High Energy Replicated Optics (HERO) telescope currently being developed at Marshall Space Flight Center. With a telescope focal length of 6 meters, the detector needs to have a spatial resolution of around 200 microns in order to take full advantage of the HERO angular resolution. We discuss to what degree charge sharing will degrade energy resolution but will improve our spatial resolution through position interpolation.

  13. The probabilistic convolution tree: efficient exact Bayesian inference for faster LC-MS/MS protein inference.

    PubMed

    Serang, Oliver

    2014-01-01

    Exact Bayesian inference can sometimes be performed efficiently for special cases where a function has commutative and associative symmetry of its inputs (called "causal independence"). For this reason, it is desirable to exploit such symmetry on big data sets. Here we present a method to exploit a general form of this symmetry on probabilistic adder nodes by transforming those probabilistic adder nodes into a probabilistic convolution tree with which dynamic programming computes exact probabilities. A substantial speedup is demonstrated using an illustration example that can arise when identifying splice forms with bottom-up mass spectrometry-based proteomics. On this example, even state-of-the-art exact inference algorithms require a runtime more than exponential in the number of splice forms considered. By using the probabilistic convolution tree, we reduce the runtime to O(k log(k)2) and the space to O(k log(k)) where k is the number of variables joined by an additive or cardinal operator. This approach, which can also be used with junction tree inference, is applicable to graphs with arbitrary dependency on counting variables or cardinalities and can be used on diverse problems and fields like forward error correcting codes, elemental decomposition, and spectral demixing. The approach also trivially generalizes to multiple dimensions.

  14. Dead pixel replacement in LWIR microgrid polarimeters.

    PubMed

    Ratliff, Bradley M; Tyo, J Scott; Boger, James K; Black, Wiley T; Bowers, David L; Fetrow, Matthew P

    2007-06-11

    LWIR imaging arrays are often affected by nonresponsive pixels, or "dead pixels." These dead pixels can severely degrade the quality of imagery and often have to be replaced before subsequent image processing and display of the imagery data. For LWIR arrays that are integrated with arrays of micropolarizers, the problem of dead pixels is amplified. Conventional dead pixel replacement (DPR) strategies cannot be employed since neighboring pixels are of different polarizations. In this paper we present two DPR schemes. The first is a modified nearest-neighbor replacement method. The second is a method based on redundancy in the polarization measurements.We find that the redundancy-based DPR scheme provides an order-of-magnitude better performance for typical LWIR polarimetric data.

  15. Equivalence of a Bit Pixel Image to a Quantum Pixel Image

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

    We propose a new method to transform a pixel image to the corresponding quantum-pixel using a qubit per pixel to represent each pixels classical weight in a quantum image matrix weight. All qubits are linear superposition, changing the coefficients level by level to the entire longitude of the gray scale with respect to the base states of the qubit. Classically, these states are just bytes represented in a binary matrix, having code combinations of 1 or 0 at all pixel locations. This method introduces a qubit-pixel image representation of images captured by classical optoelectronic methods. Supported partially by the project 20150964-SIP-IPN, Mexico

  16. Lung nodule detection using 3D convolutional neural networks trained on weakly labeled data

    NASA Astrophysics Data System (ADS)

    Anirudh, Rushil; Thiagarajan, Jayaraman J.; Bremer, Timo; Kim, Hyojin

    2016-03-01

    Early detection of lung nodules is currently the one of the most effective ways to predict and treat lung cancer. As a result, the past decade has seen a lot of focus on computer aided diagnosis (CAD) of lung nodules, whose goal is to efficiently detect, segment lung nodules and classify them as being benign or malignant. Effective detection of such nodules remains a challenge due to their arbitrariness in shape, size and texture. In this paper, we propose to employ 3D convolutional neural networks (CNN) to learn highly discriminative features for nodule detection in lieu of hand-engineered ones such as geometric shape or texture. While 3D CNNs are promising tools to model the spatio-temporal statistics of data, they are limited by their need for detailed 3D labels, which can be prohibitively expensive when compared obtaining 2D labels. Existing CAD methods rely on obtaining detailed labels for lung nodules, to train models, which is also unrealistic and time consuming. To alleviate this challenge, we propose a solution wherein the expert needs to provide only a point label, i.e., the central pixel of of the nodule, and its largest expected size. We use unsupervised segmentation to grow out a 3D region, which is used to train the CNN. Using experiments on the SPIE-LUNGx dataset, we show that the network trained using these weak labels can produce reasonably low false positive rates with a high sensitivity, even in the absence of accurate 3D labels.

  17. Method for fabricating pixelated silicon device cells

    SciTech Connect

    Nielson, Gregory N.; Okandan, Murat; Cruz-Campa, Jose Luis; Nelson, Jeffrey S.; Anderson, Benjamin John

    2015-08-18

    A method, apparatus and system for flexible, ultra-thin, and high efficiency pixelated silicon or other semiconductor photovoltaic solar cell array fabrication is disclosed. A structure and method of creation for a pixelated silicon or other semiconductor photovoltaic solar cell array with interconnects is described using a manufacturing method that is simplified compared to previous versions of pixelated silicon photovoltaic cells that require more microfabrication steps.

  18. Commissioning of the CMS Forward Pixel Detector

    SciTech Connect

    Kumar, Ashish; /SUNY, Buffalo

    2008-12-01

    The Compact Muon Solenoid (CMS) experiment is scheduled for physics data taking in summer 2009 after the commissioning of high energy proton-proton collisions at Large Hadron Collider (LHC). At the core of the CMS all-silicon tracker is the silicon pixel detector, comprising three barrel layers and two pixel disks in the forward and backward regions, accounting for a total of 66 million channels. The pixel detector will provide high-resolution, 3D tracking points, essential for pattern recognition and precise vertexing, while being embedded in a hostile radiation environment. The end disks of the pixel detector, known as the Forward Pixel detector, has been assembled and tested at Fermilab, USA. It has 18 million pixel cells with dimension 100 x 150 {micro}m{sup 2}. The complete forward pixel detector was shipped to CERN in December 2007, where it underwent extensive system tests for commissioning prior to the installation. The pixel system was put in its final place inside the CMS following the installation and bake out of the LHC beam pipe in July 2008. It has been integrated with other sub-detectors in the readout since September 2008 and participated in the cosmic data taking. This report covers the strategy and results from commissioning of CMS forward pixel detector at CERN.

  19. Implementation of TDI based digital pixel ROIC with 15μm pixel pitch

    NASA Astrophysics Data System (ADS)

    Ceylan, Omer; Shafique, Atia; Burak, A.; Caliskan, Can; Abbasi, Shahbaz; Yazici, Melik; Gurbuz, Yasar

    2016-05-01

    A 15um pixel pitch digital pixel for LWIR time delay integration (TDI) applications is implemented which occupies one fourth of pixel area compared to previous digital TDI implementation. TDI is implemented on 8 pixels with oversampling rate of 2. ROIC provides 16 bits output with 8 bits of MSB and 8 bits of LSB. Pixel can store 75 M electrons with a quantization noise of 500 electrons. Digital pixel TDI implementation is advantageous over analog counterparts considering power consumption, chip area and signal-to-noise ratio. Digital pixel TDI ROIC is fabricated with 0.18um CMOS process. In digital pixel TDI implementation photocurrent is integrated on a capacitor in pixel and converted to digital data in pixel. This digital data triggers the summation counters which implements TDI addition. After all pixels in a row contribute, the summed data is divided to the number of TDI pixels(N) to have the actual output which is square root of N improved version of a single pixel output in terms of signal-to-noise-ratio (SNR).

  20. Two-dimensional convolute integers for analytical instrumentation

    NASA Technical Reports Server (NTRS)

    Edwards, T. R.

    1982-01-01

    As new analytical instruments and techniques emerge with increased dimensionality, a corresponding need is seen for data processing logic which can appropriately address the data. Two-dimensional measurements reveal enhanced unknown mixture analysis capability as a result of the greater spectral information content over two one-dimensional methods taken separately. It is noted that two-dimensional convolute integers are merely an extension of the work by Savitzky and Golay (1964). It is shown that these low-pass, high-pass and band-pass digital filters are truly two-dimensional and that they can be applied in a manner identical with their one-dimensional counterpart, that is, a weighted nearest-neighbor, moving average with zero phase shifting, convoluted integer (universal number) weighting coefficients.

  1. UFLIC: A Line Integral Convolution Algorithm for Visualizing Unsteady Flows

    NASA Technical Reports Server (NTRS)

    Shen, Han-Wei; Kao, David L.; Chancellor, Marisa K. (Technical Monitor)

    1997-01-01

    This paper presents an algorithm, UFLIC (Unsteady Flow LIC), to visualize vector data in unsteady flow fields. Using the Line Integral Convolution (LIC) as the underlying method, a new convolution algorithm is proposed that can effectively trace the flow's global features over time. The new algorithm consists of a time-accurate value depositing scheme and a successive feed-forward method. The value depositing scheme accurately models the flow advection, and the successive feed-forward method maintains the coherence between animation frames. Our new algorithm can produce time-accurate, highly coherent flow animations to highlight global features in unsteady flow fields. CFD scientists, for the first time, are able to visualize unsteady surface flows using our algorithm.

  2. Spectral density of generalized Wishart matrices and free multiplicative convolution.

    PubMed

    Młotkowski, Wojciech; Nowak, Maciej A; Penson, Karol A; Życzkowski, Karol

    2015-07-01

    We investigate the level density for several ensembles of positive random matrices of a Wishart-like structure, W=XX(†), where X stands for a non-Hermitian random matrix. In particular, making use of the Cauchy transform, we study the free multiplicative powers of the Marchenko-Pastur (MP) distribution, MP(⊠s), which for an integer s yield Fuss-Catalan distributions corresponding to a product of s-independent square random matrices, X=X(1)⋯X(s). New formulas for the level densities are derived for s=3 and s=1/3. Moreover, the level density corresponding to the generalized Bures distribution, given by the free convolution of arcsine and MP distributions, is obtained. We also explain the reason of such a curious convolution. The technique proposed here allows for the derivation of the level densities for several other cases.

  3. Spectral density of generalized Wishart matrices and free multiplicative convolution

    NASA Astrophysics Data System (ADS)

    Młotkowski, Wojciech; Nowak, Maciej A.; Penson, Karol A.; Życzkowski, Karol

    2015-07-01

    We investigate the level density for several ensembles of positive random matrices of a Wishart-like structure, W =X X† , where X stands for a non-Hermitian random matrix. In particular, making use of the Cauchy transform, we study the free multiplicative powers of the Marchenko-Pastur (MP) distribution, MP⊠s, which for an integer s yield Fuss-Catalan distributions corresponding to a product of s -independent square random matrices, X =X1⋯Xs . New formulas for the level densities are derived for s =3 and s =1 /3 . Moreover, the level density corresponding to the generalized Bures distribution, given by the free convolution of arcsine and MP distributions, is obtained. We also explain the reason of such a curious convolution. The technique proposed here allows for the derivation of the level densities for several other cases.

  4. Rationale-Augmented Convolutional Neural Networks for Text Classification

    PubMed Central

    Zhang, Ye; Marshall, Iain; Wallace, Byron C.

    2016-01-01

    We present a new Convolutional Neural Network (CNN) model for text classification that jointly exploits labels on documents and their constituent sentences. Specifically, we consider scenarios in which annotators explicitly mark sentences (or snippets) that support their overall document categorization, i.e., they provide rationales. Our model exploits such supervision via a hierarchical approach in which each document is represented by a linear combination of the vector representations of its component sentences. We propose a sentence-level convolutional model that estimates the probability that a given sentence is a rationale, and we then scale the contribution of each sentence to the aggregate document representation in proportion to these estimates. Experiments on five classification datasets that have document labels and associated rationales demonstrate that our approach consistently outperforms strong baselines. Moreover, our model naturally provides explanations for its predictions. PMID:28191551

  5. Self-Taught convolutional neural networks for short text clustering.

    PubMed

    Xu, Jiaming; Xu, Bo; Wang, Peng; Zheng, Suncong; Tian, Guanhua; Zhao, Jun; Xu, Bo

    2017-04-01

    Short text clustering is a challenging problem due to its sparseness of text representation. Here we propose a flexible Self-Taught Convolutional neural network framework for Short Text Clustering (dubbed STC(2)), which can flexibly and successfully incorporate more useful semantic features and learn non-biased deep text representation in an unsupervised manner. In our framework, the original raw text features are firstly embedded into compact binary codes by using one existing unsupervised dimensionality reduction method. Then, word embeddings are explored and fed into convolutional neural networks to learn deep feature representations, meanwhile the output units are used to fit the pre-trained binary codes in the training process. Finally, we get the optimal clusters by employing K-means to cluster the learned representations. Extensive experimental results demonstrate that the proposed framework is effective, flexible and outperform several popular clustering methods when tested on three public short text datasets.

  6. Deep learning for steganalysis via convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Qian, Yinlong; Dong, Jing; Wang, Wei; Tan, Tieniu

    2015-03-01

    Current work on steganalysis for digital images is focused on the construction of complex handcrafted features. This paper proposes a new paradigm for steganalysis to learn features automatically via deep learning models. We novelly propose a customized Convolutional Neural Network for steganalysis. The proposed model can capture the complex dependencies that are useful for steganalysis. Compared with existing schemes, this model can automatically learn feature representations with several convolutional layers. The feature extraction and classification steps are unified under a single architecture, which means the guidance of classification can be used during the feature extraction step. We demonstrate the effectiveness of the proposed model on three state-of-theart spatial domain steganographic algorithms - HUGO, WOW, and S-UNIWARD. Compared to the Spatial Rich Model (SRM), our model achieves comparable performance on BOSSbase and the realistic and large ImageNet database.

  7. A new computational decoding complexity measure of convolutional codes

    NASA Astrophysics Data System (ADS)

    Benchimol, Isaac B.; Pimentel, Cecilio; Souza, Richard Demo; Uchôa-Filho, Bartolomeu F.

    2014-12-01

    This paper presents a computational complexity measure of convolutional codes well suitable for software implementations of the Viterbi algorithm (VA) operating with hard decision. We investigate the number of arithmetic operations performed by the decoding process over the conventional and minimal trellis modules. A relation between the complexity measure defined in this work and the one defined by McEliece and Lin is investigated. We also conduct a refined computer search for good convolutional codes (in terms of distance spectrum) with respect to two minimal trellis complexity measures. Finally, the computational cost of implementation of each arithmetic operation is determined in terms of machine cycles taken by its execution using a typical digital signal processor widely used for low-power telecommunications applications.

  8. New syndrome decoder for (n, 1) convolutional codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1983-01-01

    The letter presents a new syndrome decoding algorithm for the (n, 1) convolutional codes (CC) that is different and simpler than the previous syndrome decoding algorithm of Schalkwijk and Vinck. The new technique uses the general solution of the polynomial linear Diophantine equation for the error polynomial vector E(D). A recursive, Viterbi-like, algorithm is developed to find the minimum weight error vector E(D). An example is given for the binary nonsystematic (2, 1) CC.

  9. On the growth and form of cortical convolutions

    NASA Astrophysics Data System (ADS)

    Tallinen, Tuomas; Chung, Jun Young; Rousseau, François; Girard, Nadine; Lefèvre, Julien; Mahadevan, L.

    2016-06-01

    The rapid growth of the human cortex during development is accompanied by the folding of the brain into a highly convoluted structure. Recent studies have focused on the genetic and cellular regulation of cortical growth, but understanding the formation of the gyral and sulcal convolutions also requires consideration of the geometry and physical shaping of the growing brain. To study this, we use magnetic resonance images to build a 3D-printed layered gel mimic of the developing smooth fetal brain; when immersed in a solvent, the outer layer swells relative to the core, mimicking cortical growth. This relative growth puts the outer layer into mechanical compression and leads to sulci and gyri similar to those in fetal brains. Starting with the same initial geometry, we also build numerical simulations of the brain modelled as a soft tissue with a growing cortex, and show that this also produces the characteristic patterns of convolutions over a realistic developmental course. All together, our results show that although many molecular determinants control the tangential expansion of the cortex, the size, shape, placement and orientation of the folds arise through iterations and variations of an elementary mechanical instability modulated by early fetal brain geometry.

  10. Fast convolution quadrature for the wave equation in three dimensions

    NASA Astrophysics Data System (ADS)

    Banjai, L.; Kachanovska, M.

    2014-12-01

    This work addresses the numerical solution of time-domain boundary integral equations arising from acoustic and electromagnetic scattering in three dimensions. The semidiscretization of the time-domain boundary integral equations by Runge-Kutta convolution quadrature leads to a lower triangular Toeplitz system of size N. This system can be solved recursively in an almost linear time (O(Nlog2⁡N)), but requires the construction of O(N) dense spatial discretizations of the single layer boundary operator for the Helmholtz equation. This work introduces an improvement of this algorithm that allows to solve the scattering problem in an almost linear time. The new approach is based on two main ingredients: the near-field reuse and the application of data-sparse techniques. Exponential decay of Runge-Kutta convolution weights wnh(d) outside of a neighborhood of d≈nh (where h is a time step) allows to avoid constructing the near-field (i.e. singular and near-singular integrals) for most of the discretizations of the single layer boundary operators (near-field reuse). The far-field of these matrices is compressed with the help of data-sparse techniques, namely, H-matrices and the high-frequency fast multipole method. Numerical experiments indicate the efficiency of the proposed approach compared to the conventional Runge-Kutta convolution quadrature algorithm.

  11. A model of traffic signs recognition with convolutional neural network

    NASA Astrophysics Data System (ADS)

    Hu, Haihe; Li, Yujian; Zhang, Ting; Huo, Yi; Kuang, Wenqing

    2016-10-01

    In real traffic scenes, the quality of captured images are generally low due to some factors such as lighting conditions, and occlusion on. All of these factors are challengeable for automated recognition algorithms of traffic signs. Deep learning has provided a new way to solve this kind of problems recently. The deep network can automatically learn features from a large number of data samples and obtain an excellent recognition performance. We therefore approach this task of recognition of traffic signs as a general vision problem, with few assumptions related to road signs. We propose a model of Convolutional Neural Network (CNN) and apply the model to the task of traffic signs recognition. The proposed model adopts deep CNN as the supervised learning model, directly takes the collected traffic signs image as the input, alternates the convolutional layer and subsampling layer, and automatically extracts the features for the recognition of the traffic signs images. The proposed model includes an input layer, three convolutional layers, three subsampling layers, a fully-connected layer, and an output layer. To validate the proposed model, the experiments are implemented using the public dataset of China competition of fuzzy image processing. Experimental results show that the proposed model produces a recognition accuracy of 99.01 % on the training dataset, and yield a record of 92% on the preliminary contest within the fourth best.

  12. Fine-grained representation learning in convolutional autoencoders

    NASA Astrophysics Data System (ADS)

    Luo, Chang; Wang, Jie

    2016-03-01

    Convolutional autoencoders (CAEs) have been widely used as unsupervised feature extractors for high-resolution images. As a key component in CAEs, pooling is a biologically inspired operation to achieve scale and shift invariances, and the pooled representation directly affects the CAEs' performance. Fine-grained pooling, which uses small and dense pooling regions, encodes fine-grained visual cues and enhances local characteristics. However, it tends to be sensitive to spatial rearrangements. In most previous works, pooled features were obtained by empirically modulating parameters in CAEs. We see the CAE as a whole and propose a fine-grained representation learning law to extract better fine-grained features. This representation learning law suggests two directions for improvement. First, we probabilistically evaluate the discrimination-invariance tradeoff with fine-grained granularity in the pooled feature maps, and suggest the proper filter scale in the convolutional layer and appropriate whitening parameters in preprocessing step. Second, pooling approaches are combined with the sparsity degree in pooling regions, and we propose the preferable pooling approach. Experimental results on two independent benchmark datasets demonstrate that our representation learning law could guide CAEs to extract better fine-grained features and performs better in multiclass classification task. This paper also provides guidance for selecting appropriate parameters to obtain better fine-grained representation in other convolutional neural networks.

  13. Automatic localization of vertebrae based on convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Shen, Wei; Yang, Feng; Mu, Wei; Yang, Caiyun; Yang, Xin; Tian, Jie

    2015-03-01

    Localization of the vertebrae is of importance in many medical applications. For example, the vertebrae can serve as the landmarks in image registration. They can also provide a reference coordinate system to facilitate the localization of other organs in the chest. In this paper, we propose a new vertebrae localization method using convolutional neural networks (CNN). The main advantage of the proposed method is the removal of hand-crafted features. We construct two training sets to train two CNNs that share the same architecture. One is used to distinguish the vertebrae from other tissues in the chest, and the other is aimed at detecting the centers of the vertebrae. The architecture contains two convolutional layers, both of which are followed by a max-pooling layer. Then the output feature vector from the maxpooling layer is fed into a multilayer perceptron (MLP) classifier which has one hidden layer. Experiments were performed on ten chest CT images. We used leave-one-out strategy to train and test the proposed method. Quantitative comparison between the predict centers and ground truth shows that our convolutional neural networks can achieve promising localization accuracy without hand-crafted features.

  14. Calcium transport in the rabbit superficial proximal convoluted tubule

    SciTech Connect

    Ng, R.C.; Rouse, D.; Suki, W.N.

    1984-09-01

    Calcium transport was studied in isolated S2 segments of rabbit superficial proximal convoluted tubules. 45Ca was added to the perfusate for measurement of lumen-to-bath flux (JlbCa), to the bath for bath-to-lumen flux (JblCa), and to both perfusate and bath for net flux (JnetCa). In these studies, the perfusate consisted of an equilibrium solution that was designed to minimize water flux or electrochemical potential differences (PD). Under these conditions, JlbCa (9.1 +/- 1.0 peq/mm X min) was not different from JblCa (7.3 +/- 1.3 peq/mm X min), and JnetCa was not different from zero, which suggests that calcium transport in the superficial proximal convoluted tubule is due primarily to passive transport. The efflux coefficient was 9.5 +/- 1.2 X 10(-5) cm/s, which was not significantly different from the influx coefficient, 7.0 +/- 1.3 X 10(-5) cm/s. When the PD was made positive or negative with use of different perfusates, net calcium absorption or secretion was demonstrated, respectively, which supports a major role for passive transport. These results indicate that in the superficial proximal convoluted tubule of the rabbit, passive driving forces are the major determinants of calcium transport.

  15. Urban Image Classification: Per-Pixel Classifiers, Sub-Pixel Analysis, Object-Based Image Analysis, and Geospatial Methods. 10; Chapter

    NASA Technical Reports Server (NTRS)

    Myint, Soe W.; Mesev, Victor; Quattrochi, Dale; Wentz, Elizabeth A.

    2013-01-01

    Remote sensing methods used to generate base maps to analyze the urban environment rely predominantly on digital sensor data from space-borne platforms. This is due in part from new sources of high spatial resolution data covering the globe, a variety of multispectral and multitemporal sources, sophisticated statistical and geospatial methods, and compatibility with GIS data sources and methods. The goal of this chapter is to review the four groups of classification methods for digital sensor data from space-borne platforms; per-pixel, sub-pixel, object-based (spatial-based), and geospatial methods. Per-pixel methods are widely used methods that classify pixels into distinct categories based solely on the spectral and ancillary information within that pixel. They are used for simple calculations of environmental indices (e.g., NDVI) to sophisticated expert systems to assign urban land covers. Researchers recognize however, that even with the smallest pixel size the spectral information within a pixel is really a combination of multiple urban surfaces. Sub-pixel classification methods therefore aim to statistically quantify the mixture of surfaces to improve overall classification accuracy. While within pixel variations exist, there is also significant evidence that groups of nearby pixels have similar spectral information and therefore belong to the same classification category. Object-oriented methods have emerged that group pixels prior to classification based on spectral similarity and spatial proximity. Classification accuracy using object-based methods show significant success and promise for numerous urban 3 applications. Like the object-oriented methods that recognize the importance of spatial proximity, geospatial methods for urban mapping also utilize neighboring pixels in the classification process. The primary difference though is that geostatistical methods (e.g., spatial autocorrelation methods) are utilized during both the pre- and post

  16. Single-pixel optical imaging with compressed reference intensity patterns

    NASA Astrophysics Data System (ADS)

    Chen, Wen; Chen, Xudong

    2015-03-01

    Ghost imaging with single-pixel bucket detector has attracted more and more current attention due to its marked physical characteristics. However, in ghost imaging, a large number of reference intensity patterns are usually required for object reconstruction, hence many applications based on ghost imaging (such as tomography and optical security) may be tedious since heavy storage or transmission is requested. In this paper, we report that the compressed reference intensity patterns can be used for object recovery in computational ghost imaging (with single-pixel bucket detector), and object verification can be further conducted. Only a small portion (such as 2.0% pixels) of each reference intensity pattern is used for object reconstruction, and the recovered object is verified by using nonlinear correlation algorithm. Since statistical characteristic and speckle averaging property are inherent in ghost imaging, sidelobes or multiple peaks can be effectively suppressed or eliminated in the nonlinear correlation outputs when random pixel positions are selected from each reference intensity pattern. Since pixel positions can be randomly selected from each 2D reference intensity pattern (such as total measurements of 20000), a large key space and high flexibility can be generated when the proposed method is applied for authenticationbased cryptography. When compressive sensing is used to recover the object with a small number of measurements, the proposed strategy could still be feasible through further compressing the recorded data (i.e., reference intensity patterns) followed by object verification. It is expected that the proposed method not only compresses the recorded data and facilitates the storage or transmission, but also can build up novel capability (i.e., classical or quantum information verification) for ghost imaging.

  17. Some physical factors influencing the accuracy of convolution scatter correction in SPECT.

    PubMed

    Msaki, P; Axelsson, B; Larsson, S A

    1989-03-01

    Some important physical factors influencing the accuracy of convolution scatter correction techniques in SPECT are presented. In these techniques scatter correction in the projection relies on filter functions, QF, evaluated by Fourier transforms, from measured scatter functions, Qp, obtained from point spread functions. The spatial resolution has a marginal effect on Qp. Thus a single QF can be used in the scatter correction of SPECT measurements acquired with the low energy high resolution or the low energy general purpose collimators and over a wide range of patient-collimator distances. However, it is necessary to examine the details of the shape of point spread functions during evaluation of Qp. QF is completely described by scatter amplitude AF, slope BF and filter sum SF. SF is obtained by summation of the values of QF occupying a 31 x 31 pixels matrix. Regardless of differences in amplitude and slope, two filter functions are shown to be equivalent in terms of scatter correction ability, whenever their sums are equal. On the basis of filter sum, the observed small influence of ellipticity on QF implies that an average function can be used in scatter correcting SPECT measurements conducted with elliptic objects. SF is shown to increase with a decrease in photon energy and with an increase in window size. Thus, scatter correction by convolution may be severely hampered by photon statistics when SPECT imaging is done with low-energy photons. It is pointless to use unnecessarily large discriminator windows, in the hope of improving photon statistics, since most of the extra events acquired will eventually be subtracted during scatter correction. Regardless of the observed moderate reduction in SF when a lung-equivalent material replaces a portion of a water phantom, further studies are needed to develop a technique that is capable of handling attenuation and scatter corrections simultaneously. Whenever superficial and inner radioactive distributions coexist the

  18. New SOFRADIR 10μm pixel pitch infrared products

    NASA Astrophysics Data System (ADS)

    Lefoul, X.; Pere-Laperne, N.; Augey, T.; Rubaldo, L.; Aufranc, Sébastien; Decaens, G.; Ricard, N.; Mazaleyrat, E.; Billon-Lanfrey, D.; Gravrand, Olivier; Bisotto, Sylvette

    2014-10-01

    Recent advances in miniaturization of IR imaging technology have led to a growing market for mini thermal-imaging sensors. In that respect, Sofradir development on smaller pixel pitch has made much more compact products available to the users. When this competitive advantage is mixed with smaller coolers, made possible by HOT technology, we achieved valuable reductions in the size, weight and power of the overall package. At the same time, we are moving towards a global offer based on digital interfaces that provides our customers simplifications at the IR system design process while freeing up more space. This paper discusses recent developments on hot and small pixel pitch technologies as well as efforts made on compact packaging solution developed by SOFRADIR in collaboration with CEA-LETI.

  19. Sub-pixel mapping of water boundaries using pixel swapping algorithm (case study: Tagliamento River, Italy)

    NASA Astrophysics Data System (ADS)

    Niroumand-Jadidi, Milad; Vitti, Alfonso

    2015-10-01

    Taking the advantages of remotely sensed data for mapping and monitoring of water boundaries is of particular importance in many different management and conservation activities. Imagery data are classified using automatic techniques to produce maps entering the water bodies' analysis chain in several and different points. Very commonly, medium or coarse spatial resolution imagery is used in studies of large water bodies. Data of this kind is affected by the presence of mixed pixels leading to very outstanding problems, in particular when dealing with boundary pixels. A considerable amount of uncertainty inescapably occurs when conventional hard classifiers (e.g., maximum likelihood) are applied on mixed pixels. In this study, Linear Spectral Mixture Model (LSMM) is used to estimate the proportion of water in boundary pixels. Firstly by applying an unsupervised clustering, the water body is identified approximately and a buffer area considered ensuring the selection of entire boundary pixels. Then LSMM is applied on this buffer region to estimate the fractional maps. However, resultant output of LSMM does not provide a sub-pixel map corresponding to water abundances. To tackle with this problem, Pixel Swapping (PS) algorithm is used to allocate sub-pixels within mixed pixels in such a way to maximize the spatial proximity of sub-pixels and pixels in the neighborhood. The water area of two segments of Tagliamento River (Italy) are mapped in sub-pixel resolution (10m) using a 30m Landsat image. To evaluate the proficiency of the proposed approach for sub-pixel boundary mapping, the image is also classified using a conventional hard classifier. A high resolution image of the same area is also classified and used as a reference for accuracy assessment. According to the results, sub-pixel map shows in average about 8 percent higher overall accuracy than hard classification and fits very well in the boundaries with the reference map.

  20. Super-resolution reconstruction algorithm based on adaptive convolution kernel size selection

    NASA Astrophysics Data System (ADS)

    Gao, Hang; Chen, Qian; Sui, Xiubao; Zeng, Junjie; Zhao, Yao

    2016-09-01

    Restricted by the detector technology and optical diffraction limit, the spatial resolution of infrared imaging system is difficult to achieve significant improvement. Super-Resolution (SR) reconstruction algorithm is an effective way to solve this problem. Among them, the SR algorithm based on multichannel blind deconvolution (MBD) estimates the convolution kernel only by low resolution observation images, according to the appropriate regularization constraints introduced by a priori assumption, to realize the high resolution image restoration. The algorithm has been shown effective when each channel is prime. In this paper, we use the significant edges to estimate the convolution kernel and introduce an adaptive convolution kernel size selection mechanism, according to the uncertainty of the convolution kernel size in MBD processing. To reduce the interference of noise, we amend the convolution kernel in an iterative process, and finally restore a clear image. Experimental results show that the algorithm can meet the convergence requirement of the convolution kernel estimation.

  1. It's not the pixel count, you fool

    NASA Astrophysics Data System (ADS)

    Kriss, Michael A.

    2012-01-01

    The first thing a "marketing guy" asks the digital camera engineer is "how many pixels does it have, for we need as many mega pixels as possible since the other guys are killing us with their "umpteen" mega pixel pocket sized digital cameras. And so it goes until the pixels get smaller and smaller in order to inflate the pixel count in the never-ending pixel-wars. These small pixels just are not very good. The truth of the matter is that the most important feature of digital cameras in the last five years is the automatic motion control to stabilize the image on the sensor along with some very sophisticated image processing. All the rest has been hype and some "cool" design. What is the future for digital imaging and what will drive growth of camera sales (not counting the cell phone cameras which totally dominate the market in terms of camera sales) and more importantly after sales profits? Well sit in on the Dark Side of Color and find out what is being done to increase the after sales profits and don't be surprised if has been done long ago in some basement lab of a photographic company and of course, before its time.

  2. Of FFT-based convolutions and correlations, with application to solving Poisson's equation in an open rectangular pipe

    SciTech Connect

    Ryne, Robert D.

    2011-11-07

    A new method is presented for solving Poisson's equation inside an open-ended rectangular pipe. The method uses Fast Fourier Transforms (FFTs)to perform mixed convolutions and correlations of the charge density with the Green function. Descriptions are provided for algorithms based on theordinary Green function and for an integrated Green function (IGF). Due to its similarity to the widely used Hockney algorithm for solving Poisson'sequation in free space, this capability can be easily implemented in many existing particle-in-cell beam dynamics codes.

  3. LISe pixel detector for neutron imaging

    NASA Astrophysics Data System (ADS)

    Herrera, Elan; Hamm, Daniel; Wiggins, Brenden; Milburn, Rob; Burger, Arnold; Bilheux, Hassina; Santodonato, Louis; Chvala, Ondrej; Stowe, Ashley; Lukosi, Eric

    2016-10-01

    Semiconducting lithium indium diselenide, 6LiInSe2 or LISe, has promising characteristics for neutron detection applications. The 95% isotopic enrichment of 6Li results in a highly efficient thermal neutron-sensitive material. In this study, we report on a proof-of-principle investigation of a semiconducting LISe pixel detector to demonstrate its potential as an efficient neutron imager. The LISe pixel detector had a 4×4 of pixels with a 550 μm pitch on a 5×5×0.56 mm3 LISe substrate. An experimentally verified spatial resolution of 300 μm was observed utilizing a super-sampling technique.

  4. Per-Pixel Lighting Data Analysis

    SciTech Connect

    Inanici, Mehlika

    2005-08-01

    This report presents a framework for per-pixel analysis of the qualitative and quantitative aspects of luminous environments. Recognizing the need for better lighting analysis capabilities and appreciating the new measurement abilities developed within the LBNL Lighting Measurement and Simulation Toolbox, ''Per-pixel Lighting Data Analysis'' project demonstrates several techniques for analyzing luminance distribution patterns, luminance ratios, adaptation luminance and glare assessment. The techniques are the syntheses of the current practices in lighting design and the unique practices that can be done with per-pixel data availability. Demonstrated analysis techniques are applicable to both computer-generated and digitally captured images (physically-based renderings and High Dynamic Range photographs).

  5. Anode readout for pixellated CZT detectors

    NASA Astrophysics Data System (ADS)

    Narita, Tomohiko; Grindlay, Jonathan E.; Hong, Jaesub; Niestemski, Francis C.

    2004-02-01

    Determination of the photon interaction depth offers numerous advantages for an astronomical hard X-ray telescope. The interaction depth is typically derived from two signals: anode and cathode, or collecting and non-collecting electrodes. We present some preliminary results from our depth sensing detectors using only the anode pixel signals. By examining several anode pixel signals simultaneously, we find that we can estimate the interaction depth, and get sub-pixel 2-D position resolution. We discuss our findings and the requirements for future ASIC development.

  6. Operational and convolution properties of three-dimensional Fourier transforms in spherical polar coordinates.

    PubMed

    Baddour, Natalie

    2010-10-01

    For functions that are best described with spherical coordinates, the three-dimensional Fourier transform can be written in spherical coordinates as a combination of spherical Hankel transforms and spherical harmonic series. However, to be as useful as its Cartesian counterpart, a spherical version of the Fourier operational toolset is required for the standard operations of shift, multiplication, convolution, etc. This paper derives the spherical version of the standard Fourier operation toolset. In particular, convolution in various forms is discussed in detail as this has important consequences for filtering. It is shown that standard multiplication and convolution rules do apply as long as the correct definition of convolution is applied.

  7. Deep-learning convolution neural network for computer-aided detection of microcalcifications in digital breast tomosynthesis

    NASA Astrophysics Data System (ADS)

    Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Cha, Kenny; Helvie, Mark A.

    2016-03-01

    A deep learning convolution neural network (DLCNN) was designed to differentiate microcalcification candidates detected during the prescreening stage as true calcifications or false positives in a computer-aided detection (CAD) system for clustered microcalcifications. The microcalcification candidates were extracted from the planar projection image generated from the digital breast tomosynthesis volume reconstructed by a multiscale bilateral filtering regularized simultaneous algebraic reconstruction technique. For training and testing of the DLCNN, true microcalcifications are manually labeled for the data sets and false positives were obtained from the candidate objects identified by the CAD system at prescreening after exclusion of the true microcalcifications. The DLCNN architecture was selected by varying the number of filters, filter kernel sizes and gradient computation parameter in the convolution layers, resulting in a parameter space of 216 combinations. The exhaustive grid search method was used to select an optimal architecture within the parameter space studied, guided by the area under the receiver operating characteristic curve (AUC) as a figure-of-merit. The effects of varying different categories of the parameter space were analyzed. The selected DLCNN was compared with our previously designed CNN architecture for the test set. The AUCs of the CNN and DLCNN was 0.89 and 0.93, respectively. The improvement was statistically significant (p < 0.05).

  8. Convolution Algebra for Fluid Modes with Finite Energy

    DTIC Science & Technology

    1992-04-01

    PHILLIPS LABORATORY AIR FORCE SYSTEMS COMMAND UNITED STATES AIR FORCE HANSCOM AIR FORCE BASE, MASSACHIUSETTS 01731-5000 94-22604 "This technical report ’-as...with finite spatial and temporal extents. At Boston University, we have developed a full form of wavelet expansion which has the advantage over more...distribution: 00 bX =00 0l if, TZ< VPf (X) = V •a,,,’(x) = E bnb 𔄀(x) where b, =otherwise (34) V=o ,i=o a._, otherwise 7 The convolution of two

  9. Visualizing Vector Fields Using Line Integral Convolution and Dye Advection

    NASA Technical Reports Server (NTRS)

    Shen, Han-Wei; Johnson, Christopher R.; Ma, Kwan-Liu

    1996-01-01

    We present local and global techniques to visualize three-dimensional vector field data. Using the Line Integral Convolution (LIC) method to image the global vector field, our new algorithm allows the user to introduce colored 'dye' into the vector field to highlight local flow features. A fast algorithm is proposed that quickly recomputes the dyed LIC images. In addition, we introduce volume rendering methods that can map the LIC texture on any contour surface and/or translucent region defined by additional scalar quantities, and can follow the advection of colored dye throughout the volume.

  10. Surrogacy theory and models of convoluted organic systems.

    PubMed

    Konopka, Andrzej K

    2007-03-01

    The theory of surrogacy is briefly outlined as one of the conceptual foundations of systems biology that has been developed for the last 30 years in the context of Hertz-Rosen modeling relationship. Conceptual foundations of modeling convoluted (biologically complex) systems are briefly reviewed and discussed in terms of current and future research in systems biology. New as well as older results that pertain to the concepts of modeling relationship, sequence of surrogacies, cascade of representations, complementarity, analogy, metaphor, and epistemic time are presented together with a classification of models in a cascade. Examples of anticipated future applications of surrogacy theory in life sciences are briefly discussed.

  11. Medical image fusion using the convolution of Meridian distributions.

    PubMed

    Agrawal, Mayank; Tsakalides, Panagiotis; Achim, Alin

    2010-01-01

    The aim of this paper is to introduce a novel non-Gaussian statistical model-based approach for medical image fusion based on the Meridian distribution. The paper also includes a new approach to estimate the parameters of generalized Cauchy distribution. The input images are first decomposed using the Dual-Tree Complex Wavelet Transform (DT-CWT) with the subband coefficients modelled as Meridian random variables. Then, the convolution of Meridian distributions is applied as a probabilistic prior to model the fused coefficients, and the weights used to combine the source images are optimised via Maximum Likelihood (ML) estimation. The superior performance of the proposed method is demonstrated using medical images.

  12. Convolution seal for transition duct in turbine system

    DOEpatents

    Flanagan, James Scott; LeBegue, Jeffrey Scott; McMahan, Kevin Weston; Dillard, Daniel Jackson; Pentecost, Ronnie Ray

    2015-05-26

    A turbine system is disclosed. In one embodiment, the turbine system includes a transition duct. The transition duct includes an inlet, an outlet, and a passage extending between the inlet and the outlet and defining a longitudinal axis, a radial axis, and a tangential axis. The outlet of the transition duct is offset from the inlet along the longitudinal axis and the tangential axis. The transition duct further includes an interface feature for interfacing with an adjacent transition duct. The turbine system further includes a convolution seal contacting the interface feature to provide a seal between the interface feature and the adjacent transition duct.

  13. New Syndrome Decoding Techniques for the (n, K) Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1983-01-01

    This paper presents a new syndrome decoding algorithm for the (n,k) convolutional codes (CC) which differs completely from an earlier syndrome decoding algorithm of Schalkwijk and Vinck. The new algorithm is based on the general solution of the syndrome equation, a linear Diophantine equation for the error polynomial vector E(D). The set of Diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like algorithm is developed to find the minimum weight error vector (circumflex)E(D). An example, illustrating the new decoding algorithm, is given for the binary nonsystemmatic (3,1)CC.

  14. New syndrome decoding techniques for the (n, k) convolutional codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Truong, T. K.

    1984-01-01

    This paper presents a new syndrome decoding algorithm for the (n, k) convolutional codes (CC) which differs completely from an earlier syndrome decoding algorithm of Schalkwijk and Vinck. The new algorithm is based on the general solution of the syndrome equation, a linear Diophantine equation for the error polynomial vector E(D). The set of Diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like algorithm is developed to find the minimum weight error vector (circumflex)E(D). An example, illustrating the new decoding algorithm, is given for the binary nonsystemmatic (3, 1)CC. Previously announced in STAR as N83-34964

  15. Continuous speech recognition based on convolutional neural network

    NASA Astrophysics Data System (ADS)

    Zhang, Qing-qing; Liu, Yong; Pan, Jie-lin; Yan, Yong-hong

    2015-07-01

    Convolutional Neural Networks (CNNs), which showed success in achieving translation invariance for many image processing tasks, are investigated for continuous speech recognitions in the paper. Compared to Deep Neural Networks (DNNs), which have been proven to be successful in many speech recognition tasks nowadays, CNNs can reduce the NN model sizes significantly, and at the same time achieve even better recognition accuracies. Experiments on standard speech corpus TIMIT showed that CNNs outperformed DNNs in the term of the accuracy when CNNs had even smaller model size.

  16. Convolution seal for transition duct in turbine system

    DOEpatents

    Flanagan, James Scott; LeBegue, Jeffrey Scott; McMahan, Kevin Weston; Dillard, Daniel Jackson; Pentecost, Ronnie Ray

    2015-03-10

    A turbine system is disclosed. In one embodiment, the turbine system includes a transition duct. The transition duct includes an inlet, an outlet, and a passage extending between the inlet and the outlet and defining a longitudinal axis, a radial axis, and a tangential axis. The outlet of the transition duct is offset from the inlet along the longitudinal axis and the tangential axis. The transition duct further includes an interface member for interfacing with a turbine section. The turbine system further includes a convolution seal contacting the interface member to provide a seal between the interface member and the turbine section.

  17. Convolutional neural networks for synthetic aperture radar classification

    NASA Astrophysics Data System (ADS)

    Profeta, Andrew; Rodriguez, Andres; Clouse, H. Scott

    2016-05-01

    For electro-optical object recognition, convolutional neural networks (CNNs) are the state-of-the-art. For large datasets, CNNs are able to learn meaningful features used for classification. However, their application to synthetic aperture radar (SAR) has been limited. In this work we experimented with various CNN architectures on the MSTAR SAR dataset. As the input to the CNN we used the magnitude and phase (2 channels) of the SAR imagery. We used the deep learning toolboxes CAFFE and Torch7. Our results show that we can achieve 93% accuracy on the MSTAR dataset using CNNs.

  18. Pixels, Imagers and Related Fabrication Methods

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

  19. Pixels, Imagers and Related Fabrication Methods

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

  20. Toward Multispectral Imaging with Colloidal Metasurface Pixels.

    PubMed

    Stewart, Jon W; Akselrod, Gleb M; Smith, David R; Mikkelsen, Maiken H

    2017-02-01

    Multispectral colloidal metasurfaces are fabricated that exhibit greater than 85% absorption and ≈100 nm linewidths by patterning film-coupled nanocubes in pixels using a fusion of bottom-up and top-down fabrication techniques over wafer-scale areas. With this technique, the authors realize a multispectral pixel array consisting of six resonances between 580 and 1125 nm and reconstruct an RGB image with 9261 color combinations.

  1. Design of the small pixel pitch ROIC

    NASA Astrophysics Data System (ADS)

    Liang, Qinghua; Jiang, Dazhao; Chen, Honglei; Zhai, Yongcheng; Gao, Lei; Ding, Ruijun

    2014-11-01

    Since the technology trend of the third generation IRFPA towards resolution enhancing has steadily progressed,the pixel pitch of IRFPA has been greatly reduced.A 640×512 readout integrated circuit(ROIC) of IRFPA with 15μm pixel pitch is presented in this paper.The 15μm pixel pitch ROIC design will face many challenges.As we all known,the integrating capacitor is a key performance parameter when considering pixel area,charge capacity and dynamic range,so we adopt the effective method of 2 by 2 pixels sharing an integrating capacitor to solve this problem.The input unit cell architecture will contain two paralleled sample and hold parts,which not only allow the FPA to be operated in full frame snapshot mode but also save relatively unit circuit area.Different applications need more matching input unit circuits. Because the dimension of 2×2 pixels is 30μm×30μm, an input stage based on direct injection (DI) which has medium injection ratio and small layout area is proved to be suitable for middle wave (MW) while BDI with three-transistor cascode amplifier for long wave(LW). By adopting the 0.35μm 2P4M mixed signal process, the circuit architecture can make the effective charge capacity of 7.8Me- per pixel with 2.2V output range for MW and 7.3 Me- per pixel with 2.6V output range for LW. According to the simulation results, this circuit works well under 5V power supply and achieves less than 0.1% nonlinearity.

  2. Readout and DAQ for Pixel Detectors

    NASA Astrophysics Data System (ADS)

    Platkevic, Michal

    2010-01-01

    Data readout and acquisition control of pixel detectors demand the transfer of significantly a large amounts of bits between the detector and the computer. For this purpose dedicated interfaces are used which are designed with focus on features like speed, small dimensions or flexibility of use such as digital signal processors, field-programmable gate arrays (FPGA) and USB communication ports. This work summarizes the readout and DAQ system built for state-of-the-art pixel detectors of the Medipix family.

  3. SU-E-T-423: Fast Photon Convolution Calculation with a 3D-Ideal Kernel On the GPU

    SciTech Connect

    Moriya, S; Sato, M; Tachibana, H

    2015-06-15

    Purpose: The calculation time is a trade-off for improving the accuracy of convolution dose calculation with fine calculation spacing of the KERMA kernel. We investigated to accelerate the convolution calculation using an ideal kernel on the Graphic Processing Units (GPU). Methods: The calculation was performed on the AMD graphics hardware of Dual FirePro D700 and our algorithm was implemented using the Aparapi that convert Java bytecode to OpenCL. The process of dose calculation was separated with the TERMA and KERMA steps. The dose deposited at the coordinate (x, y, z) was determined in the process. In the dose calculation running on the central processing unit (CPU) of Intel Xeon E5, the calculation loops were performed for all calculation points. On the GPU computation, all of the calculation processes for the points were sent to the GPU and the multi-thread computation was done. In this study, the dose calculation was performed in a water equivalent homogeneous phantom with 150{sup 3} voxels (2 mm calculation grid) and the calculation speed on the GPU to that on the CPU and the accuracy of PDD were compared. Results: The calculation time for the GPU and the CPU were 3.3 sec and 4.4 hour, respectively. The calculation speed for the GPU was 4800 times faster than that for the CPU. The PDD curve for the GPU was perfectly matched to that for the CPU. Conclusion: The convolution calculation with the ideal kernel on the GPU was clinically acceptable for time and may be more accurate in an inhomogeneous region. Intensity modulated arc therapy needs dose calculations for different gantry angles at many control points. Thus, it would be more practical that the kernel uses a coarse spacing technique if the calculation is faster while keeping the similar accuracy to a current treatment planning system.

  4. Holographic imaging with single pixel sensor

    NASA Astrophysics Data System (ADS)

    Leportier, Thibault; Lee, Young Tack; Hwang, Do Kyung; Park, Min-Chul

    2016-09-01

    Imaging techniques based on CCD sensors presenting very high number of pixels enable to record images with high resolution. However, the huge storage load and high bandwidth required to store and transmit digital holographic information are technical bottlenecks that should be overcome for the future of holographic display. Techniques to capture images with single pixel sensors have been greatly improved recently with the development of compressive sensing algorithm (CS). Since interference patterns may be considered sparse, the number of measurements required to recover the information with CS is lower than the number of pixels of the reconstructed image. In addition, this method does not need any scanning system. One other advantage of single pixel imaging is that the cost of recording system can be dramatically reduced since high-resolution cameras are expensive while compressive sensing exploits only one pixel. In this paper, we present an imaging system based on phase-shifting holography. First, simulations were performed to confirm that hologram could be reconstructed by compressive sensing even if the number of measurements was smaller than the number of pixels. Then, experimental set-up was realized. Several holograms with different phase shifts introduced by quarter and half wave plates in the reference beam were acquired. We demonstrated that our system enables the reconstruction of the object.

  5. Simulation study of pixel detector charge digitization

    NASA Astrophysics Data System (ADS)

    Wang, Fuyue; Nachman, Benjamin; Sciveres, Maurice; Lawrence Berkeley National Laboratory Team

    2017-01-01

    Reconstruction of tracks from nearly overlapping particles, called Tracking in Dense Environments (TIDE), is an increasingly important component of many physics analyses at the Large Hadron Collider as signatures involving highly boosted jets are investigated. TIDE makes use of the charge distribution inside a pixel cluster to resolve tracks that share one of more of their pixel detector hits. In practice, the pixel charge is discretized using the Time-over-Threshold (ToT) technique. More charge information is better for discrimination, but more challenging for designing and operating the detector. A model of the silicon pixels has been developed in order to study the impact of the precision of the digitized charge distribution on distinguishing multi-particle clusters. The output of the GEANT4-based simulation is used to train neutral networks that predict the multiplicity and location of particles depositing energy inside one cluster of pixels. By studying the multi-particle cluster identification efficiency and position resolution, we quantify the trade-off between the number of ToT bits and low-level tracking inputs. As both ATLAS and CMS are designing upgraded detectors, this work provides guidance for the pixel module designs to meet TIDE needs. Work funded by the China Scholarship Council and the Office of High Energy Physics of the U.S. Department of Energy under contract DE-AC02-05CH11231.

  6. Steganography based on pixel intensity value decomposition

    NASA Astrophysics Data System (ADS)

    Abdulla, Alan Anwar; Sellahewa, Harin; Jassim, Sabah A.

    2014-05-01

    This paper focuses on steganography based on pixel intensity value decomposition. A number of existing schemes such as binary, Fibonacci, Prime, Natural, Lucas, and Catalan-Fibonacci (CF) are evaluated in terms of payload capacity and stego quality. A new technique based on a specific representation is proposed to decompose pixel intensity values into 16 (virtual) bit-planes suitable for embedding purposes. The proposed decomposition has a desirable property whereby the sum of all bit-planes does not exceed the maximum pixel intensity value, i.e. 255. Experimental results demonstrate that the proposed technique offers an effective compromise between payload capacity and stego quality of existing embedding techniques based on pixel intensity value decomposition. Its capacity is equal to that of binary and Lucas, while it offers a higher capacity than Fibonacci, Prime, Natural, and CF when the secret bits are embedded in 1st Least Significant Bit (LSB). When the secret bits are embedded in higher bit-planes, i.e., 2nd LSB to 8th Most Significant Bit (MSB), the proposed scheme has more capacity than Natural numbers based embedding. However, from the 6th bit-plane onwards, the proposed scheme offers better stego quality. In general, the proposed decomposition scheme has less effect in terms of quality on pixel value when compared to most existing pixel intensity value decomposition techniques when embedding messages in higher bit-planes.

  7. New CMOS digital pixel sensor architecture dedicated to a visual cortical implant

    NASA Astrophysics Data System (ADS)

    Trépanier, Annie; Trépanier, Jean-Luc; Sawan, Mohamad; Audet, Yves

    2004-10-01

    A CMOS image sensor with pixel level analog to digital conversion is presented. Each 16μm x 16μm pixel area contains a photodiode, with a fill factor of 22%, a comparator and an 8-bit DRAM, resulting in a total of 44 transistors per pixel. A digital to analog converter is used to deliver a voltage reference to compare with the pixel voltage for the analog to digital conversion. This sensor is required by a visual cortical stimulator, primarily to capture the image which is dedicated to stimulate the visual cortex of a blind patient. An active range finder system will be added to the implant, requiring the difference information between two images, in order to obtain the 3D information useful to the patient. For this purpose, three selectable operation modes are combined in the same pixel circuit. The linear integration, resulting from image capture at multiple exposure times, allows a high intrascene dynamic range. Random accessibility, in space and time, of the array of sensors is possible with the logarithmic mode. And the new differential mode makes the difference between two consecutive images. The circuit of a pixel has been fabricated in CMOS 0.18μm technology and it is under test to validate the full operation of the 3 modes. Also, a matrix of 45 x 90 pixels is currently being implemented for fabrication.

  8. Construction of the Phase I Forward Pixel Detector

    NASA Astrophysics Data System (ADS)

    Neylon, Ashton; Bartek, Rachel

    2017-01-01

    The silicon pixel detector is the innermost component of the CMS tracking system, providing high precision space point measurements of charged particle trajectories. The original CMS detector was designed for the nominal instantaneous LHC luminosity of 1 x 1034 cm-2s-1 . The LHC has already started to exceed this luminosity causing the CMS pixel detector to see a dynamic inefficiency caused by data losses due to buffer overflows. For this reason the CMS Collaboration has been building an upgraded pixel detector which is scheduled for installation during an extended year end technical stop during winter 2016/2017. The phase 1 upgrade includes four barrel layers and three forward disks, providing robust tracking and vertexing for LHC luminosities up to 2 x 1034 cm-2s-1 . The upgrade incorporates new readout chips, front-end electronics, DC-DC powering, and dual-phase CO2 cooling to achieve performance exceeding that of the present detector with a lower material budget. This contribution will review the design and technology choices of the Phase I detector and discuss the status of the detector. The challenges and difficulties encountered during the construction will also be presented, as well as the lessons learned for future upgrades. National Science Foundation.

  9. Focal plane array with modular pixel array components for scalability

    SciTech Connect

    Kay, Randolph R; Campbell, David V; Shinde, Subhash L; Rienstra, Jeffrey L; Serkland, Darwin K; Holmes, Michael L

    2014-12-09

    A modular, scalable focal plane array is provided as an array of integrated circuit dice, wherein each die includes a given amount of modular pixel array circuitry. The array of dice effectively multiplies the amount of modular pixel array circuitry to produce a larger pixel array without increasing die size. Desired pixel pitch across the enlarged pixel array is preserved by forming die stacks with each pixel array circuitry die stacked on a separate die that contains the corresponding signal processing circuitry. Techniques for die stack interconnections and die stack placement are implemented to ensure that the desired pixel pitch is preserved across the enlarged pixel array.

  10. A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images.

    PubMed

    Xu, Jun; Luo, Xiaofei; Wang, Guanhao; Gilmore, Hannah; Madabhushi, Anant

    2016-05-26

    Epithelial (EP) and stromal (ST) are two types of tissues in histological images. Automated segmentation or classification of EP and ST tissues is important when developing computerized system for analyzing the tumor microenvironment. In this paper, a Deep Convolutional Neural Networks (DCNN) based feature learning is presented to automatically segment or classify EP and ST regions from digitized tumor tissue microarrays (TMAs). Current approaches are based on handcraft feature representation, such as color, texture, and Local Binary Patterns (LBP) in classifying two regions. Compared to handcrafted feature based approaches, which involve task dependent representation, DCNN is an end-to-end feature extractor that may be directly learned from the raw pixel intensity value of EP and ST tissues in a data driven fashion. These high-level features contribute to the construction of a supervised classifier for discriminating the two types of tissues. In this work we compare DCNN based models with three handcraft feature extraction based approaches on two different datasets which consist of 157 Hematoxylin and Eosin (H&E) stained images of breast cancer and 1376 immunohistological (IHC) stained images of colorectal cancer, respectively. The DCNN based feature learning approach was shown to have a F1 classification score of 85%, 89%, and 100%, accuracy (ACC) of 84%, 88%, and 100%, and Matthews Correlation Coefficient (MCC) of 86%, 77%, and 100% on two H&E stained (NKI and VGH) and IHC stained data, respectively. Our DNN based approach was shown to outperform three handcraft feature extraction based approaches in terms of the classification of EP and ST regions.

  11. A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images

    PubMed Central

    Xu, Jun; Luo, Xiaofei; Wang, Guanhao; Gilmore, Hannah; Madabhushi, Anant

    2016-01-01

    Epithelial (EP) and stromal (ST) are two types of tissues in histological images. Automated segmentation or classification of EP and ST tissues is important when developing computerized system for analyzing the tumor microenvironment. In this paper, a Deep Convolutional Neural Networks (DCNN) based feature learning is presented to automatically segment or classify EP and ST regions from digitized tumor tissue microarrays (TMAs). Current approaches are based on handcraft feature representation, such as color, texture, and Local Binary Patterns (LBP) in classifying two regions. Compared to handcrafted feature based approaches, which involve task dependent representation, DCNN is an end-to-end feature extractor that may be directly learned from the raw pixel intensity value of EP and ST tissues in a data driven fashion. These high-level features contribute to the construction of a supervised classifier for discriminating the two types of tissues. In this work we compare DCNN based models with three handcraft feature extraction based approaches on two different datasets which consist of 157 Hematoxylin and Eosin (H&E) stained images of breast cancer and 1376 immunohistological (IHC) stained images of colorectal cancer, respectively. The DCNN based feature learning approach was shown to have a F1 classification score of 85%, 89%, and 100%, accuracy (ACC) of 84%, 88%, and 100%, and Matthews Correlation Coefficient (MCC) of 86%, 77%, and 100% on two H&E stained (NKI and VGH) and IHC stained data, respectively. Our DNN based approach was shown to outperform three handcraft feature extraction based approaches in terms of the classification of EP and ST regions. PMID:28154470

  12. Convolutional neural network architectures for predicting DNA–protein binding

    PubMed Central

    Zeng, Haoyang; Edwards, Matthew D.; Liu, Ge; Gifford, David K.

    2016-01-01

    Motivation: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications. Results: We present a systematic exploration of CNN architectures for predicting DNA sequence binding using a large compendium of transcription factor datasets. We identify the best-performing architectures by varying CNN width, depth and pooling designs. We find that adding convolutional kernels to a network is important for motif-based tasks. We show the benefits of CNNs in learning rich higher-order sequence features, such as secondary motifs and local sequence context, by comparing network performance on multiple modeling tasks ranging in difficulty. We also demonstrate how careful construction of sequence benchmark datasets, using approaches that control potentially confounding effects like positional or motif strength bias, is critical in making fair comparisons between competing methods. We explore how to establish the sufficiency of training data for these learning tasks, and we have created a flexible cloud-based framework that permits the rapid exploration of alternative neural network architectures for problems in computational biology. Availability and Implementation: All the models analyzed are available at http://cnn.csail.mit.edu. Contact: gifford@mit.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307608

  13. Multichannel Convolutional Neural Network for Biological Relation Extraction

    PubMed Central

    Quan, Chanqin; Sun, Xiao; Bai, Wenjun

    2016-01-01

    The plethora of biomedical relations which are embedded in medical logs (records) demands researchers' attention. Previous theoretical and practical focuses were restricted on traditional machine learning techniques. However, these methods are susceptible to the issues of “vocabulary gap” and data sparseness and the unattainable automation process in feature extraction. To address aforementioned issues, in this work, we propose a multichannel convolutional neural network (MCCNN) for automated biomedical relation extraction. The proposed model has the following two contributions: (1) it enables the fusion of multiple (e.g., five) versions in word embeddings; (2) the need for manual feature engineering can be obviated by automated feature learning with convolutional neural network (CNN). We evaluated our model on two biomedical relation extraction tasks: drug-drug interaction (DDI) extraction and protein-protein interaction (PPI) extraction. For DDI task, our system achieved an overall f-score of 70.2% compared to the standard linear SVM based system (e.g., 67.0%) on DDIExtraction 2013 challenge dataset. And for PPI task, we evaluated our system on Aimed and BioInfer PPI corpus; our system exceeded the state-of-art ensemble SVM system by 2.7% and 5.6% on f-scores. PMID:28053977

  14. Deep Convolutional Neural Networks for large-scale speech tasks.

    PubMed

    Sainath, Tara N; Kingsbury, Brian; Saon, George; Soltau, Hagen; Mohamed, Abdel-rahman; Dahl, George; Ramabhadran, Bhuvana

    2015-04-01

    Convolutional Neural Networks (CNNs) are an alternative type of neural network that can be used to reduce spectral variations and model spectral correlations which exist in signals. Since speech signals exhibit both of these properties, we hypothesize that CNNs are a more effective model for speech compared to Deep Neural Networks (DNNs). In this paper, we explore applying CNNs to large vocabulary continuous speech recognition (LVCSR) tasks. First, we determine the appropriate architecture to make CNNs effective compared to DNNs for LVCSR tasks. Specifically, we focus on how many convolutional layers are needed, what is an appropriate number of hidden units, what is the best pooling strategy. Second, investigate how to incorporate speaker-adapted features, which cannot directly be modeled by CNNs as they do not obey locality in frequency, into the CNN framework. Third, given the importance of sequence training for speech tasks, we introduce a strategy to use ReLU+dropout during Hessian-free sequence training of CNNs. Experiments on 3 LVCSR tasks indicate that a CNN with the proposed speaker-adapted and ReLU+dropout ideas allow for a 12%-14% relative improvement in WER over a strong DNN system, achieving state-of-the art results in these 3 tasks.

  15. A Mathematical Motivation for Complex-Valued Convolutional Networks.

    PubMed

    Tygert, Mark; Bruna, Joan; Chintala, Soumith; LeCun, Yann; Piantino, Serkan; Szlam, Arthur

    2016-05-01

    A complex-valued convolutional network (convnet) implements the repeated application of the following composition of three operations, recursively applying the composition to an input vector of nonnegative real numbers: (1) convolution with complex-valued vectors, followed by (2) taking the absolute value of every entry of the resulting vectors, followed by (3) local averaging. For processing real-valued random vectors, complex-valued convnets can be viewed as data-driven multiscale windowed power spectra, data-driven multiscale windowed absolute spectra, data-driven multiwavelet absolute values, or (in their most general configuration) data-driven nonlinear multiwavelet packets. Indeed, complex-valued convnets can calculate multiscale windowed spectra when the convnet filters are windowed complex-valued exponentials. Standard real-valued convnets, using rectified linear units (ReLUs), sigmoidal (e.g., logistic or tanh) nonlinearities, or max pooling, for example, do not obviously exhibit the same exact correspondence with data-driven wavelets (whereas for complex-valued convnets, the correspondence is much more than just a vague analogy). Courtesy of the exact correspondence, the remarkably rich and rigorous body of mathematical analysis for wavelets applies directly to (complex-valued) convnets.

  16. Fluence-convolution broad-beam (FCBB) dose calculation.

    PubMed

    Lu, Weiguo; Chen, Mingli

    2010-12-07

    IMRT optimization requires a fast yet relatively accurate algorithm to calculate the iteration dose with small memory demand. In this paper, we present a dose calculation algorithm that approaches these goals. By decomposing the infinitesimal pencil beam (IPB) kernel into the central axis (CAX) component and lateral spread function (LSF) and taking the beam's eye view (BEV), we established a non-voxel and non-beamlet-based dose calculation formula. Both LSF and CAX are determined by a commissioning procedure using the collapsed-cone convolution/superposition (CCCS) method as the standard dose engine. The proposed dose calculation involves a 2D convolution of a fluence map with LSF followed by ray tracing based on the CAX lookup table with radiological distance and divergence correction, resulting in complexity of O(N(3)) both spatially and temporally. This simple algorithm is orders of magnitude faster than the CCCS method. Without pre-calculation of beamlets, its implementation is also orders of magnitude smaller than the conventional voxel-based beamlet-superposition (VBS) approach. We compared the presented algorithm with the CCCS method using simulated and clinical cases. The agreement was generally within 3% for a homogeneous phantom and 5% for heterogeneous and clinical cases. Combined with the 'adaptive full dose correction', the algorithm is well suitable for calculating the iteration dose during IMRT optimization.

  17. Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks.

    PubMed

    Dürr, Oliver; Sick, Beate

    2016-10-01

    Deep learning methods are currently outperforming traditional state-of-the-art computer vision algorithms in diverse applications and recently even surpassed human performance in object recognition. Here we demonstrate the potential of deep learning methods to high-content screening-based phenotype classification. We trained a deep learning classifier in the form of convolutional neural networks with approximately 40,000 publicly available single-cell images from samples treated with compounds from four classes known to lead to different phenotypes. The input data consisted of multichannel images. The construction of appropriate feature definitions was part of the training and carried out by the convolutional network, without the need for expert knowledge or handcrafted features. We compare our results against the recent state-of-the-art pipeline in which predefined features are extracted from each cell using specialized software and then fed into various machine learning algorithms (support vector machine, Fisher linear discriminant, random forest) for classification. The performance of all classification approaches is evaluated on an untouched test image set with known phenotype classes. Compared to the best reference machine learning algorithm, the misclassification rate is reduced from 8.9% to 6.6%.

  18. Selective Convolutional Descriptor Aggregation for Fine-Grained Image Retrieval.

    PubMed

    Wei, Xiu-Shen; Luo, Jian-Hao; Wu, Jianxin; Zhou, Zhi-Hua

    2017-03-27

    Deep convolutional neural network models pretrained for the ImageNet classification task have been successfully adopted to tasks in other domains, such as texture description and object proposal generation, but these tasks require annotations for images in the new domain. In this paper, we focus on a novel and challenging task in the pure unsupervised setting: fine-grained image retrieval. Even with image labels, fine-grained images are difficult to classify, let alone the unsupervised retrieval task. We propose the Selective Convolutional Descriptor Aggregation (SCDA) method. SCDA firstly localizes the main object in fine-grained images, a step that discards the noisy background and keeps useful deep descriptors. The selected descriptors are then aggregated and dimensionality reduced into a short feature vector using the best practices we found. SCDA is unsupervised, using no image label or bounding box annotation. Experiments on six fine-grained datasets confirm the effectiveness of SCDA for fine-grained image retrieval. Besides, visualization of the SCDA features shows that they correspond to visual attributes (even subtle ones), which might explain SCDA's high mean average precision in fine-grained retrieval. Moreover, on general image retrieval datasets, SCDA achieves comparable retrieval results with state-of-the-art general image retrieval approaches.

  19. Enhancing Neutron Beam Production with a Convoluted Moderator

    SciTech Connect

    Iverson, Erik B; Baxter, David V; Muhrer, Guenter; Ansell, Stuart; Gallmeier, Franz X; Dalgliesh, Robert; Lu, Wei; Kaiser, Helmut

    2014-10-01

    We describe a new concept for a neutron moderating assembly resulting in the more efficient production of slow neutron beams. The Convoluted Moderator, a heterogeneous stack of interleaved moderating material and nearly transparent single-crystal spacers, is a directionally-enhanced neutron beam source, improving beam effectiveness over an angular range comparable to the range accepted by neutron beam lines and guides. We have demonstrated gains of 50% in slow neutron intensity for a given fast neutron production rate while simultaneously reducing the wavelength-dependent emission time dispersion by 25%, both coming from a geometric effect in which the neutron beam lines view a large surface area of moderating material in a relatively small volume. Additionally, we have confirmed a Bragg-enhancement effect arising from coherent scattering within the single-crystal spacers. We have not observed hypothesized refractive effects leading to additional gains at long wavelength. In addition to confirmation of the validity of the Convoluted Moderator concept, our measurements provide a series of benchmark experiments suitable for developing simulation and analysis techniques for practical optimization and eventual implementation at slow neutron source facilities.

  20. Classifications of Multispectral Colorectal Cancer Tissues Using Convolution Neural Network

    PubMed Central

    Haj-Hassan, Hawraa; Chaddad, Ahmad; Harkouss, Youssef; Desrosiers, Christian; Toews, Matthew; Tanougast, Camel

    2017-01-01

    Background: Colorectal cancer (CRC) is the third most common cancer among men and women. Its diagnosis in early stages, typically done through the analysis of colon biopsy images, can greatly improve the chances of a successful treatment. This paper proposes to use convolution neural networks (CNNs) to predict three tissue types related to the progression of CRC: benign hyperplasia (BH), intraepithelial neoplasia (IN), and carcinoma (Ca). Methods: Multispectral biopsy images of thirty CRC patients were retrospectively analyzed. Images of tissue samples were divided into three groups, based on their type (10 BH, 10 IN, and 10 Ca). An active contour model was used to segment image regions containing pathological tissues. Tissue samples were classified using a CNN containing convolution, max-pooling, and fully-connected layers. Available tissue samples were split into a training set, for learning the CNN parameters, and test set, for evaluating its performance. Results: An accuracy of 99.17% was obtained from segmented image regions, outperforming existing approaches based on traditional feature extraction, and classification techniques. Conclusions: Experimental results demonstrate the effectiveness of CNN for the classification of CRC tissue types, in particular when using presegmented regions of interest.

  1. Convolutional Neural Network Based Fault Detection for Rotating Machinery

    NASA Astrophysics Data System (ADS)

    Janssens, Olivier; Slavkovikj, Viktor; Vervisch, Bram; Stockman, Kurt; Loccufier, Mia; Verstockt, Steven; Van de Walle, Rik; Van Hoecke, Sofie

    2016-09-01

    Vibration analysis is a well-established technique for condition monitoring of rotating machines as the vibration patterns differ depending on the fault or machine condition. Currently, mainly manually-engineered features, such as the ball pass frequencies of the raceway, RMS, kurtosis an crest, are used for automatic fault detection. Unfortunately, engineering and interpreting such features requires a significant level of human expertise. To enable non-experts in vibration analysis to perform condition monitoring, the overhead of feature engineering for specific faults needs to be reduced as much as possible. Therefore, in this article we propose a feature learning model for condition monitoring based on convolutional neural networks. The goal of this approach is to autonomously learn useful features for bearing fault detection from the data itself. Several types of bearing faults such as outer-raceway faults and lubrication degradation are considered, but also healthy bearings and rotor imbalance are included. For each condition, several bearings are tested to ensure generalization of the fault-detection system. Furthermore, the feature-learning based approach is compared to a feature-engineering based approach using the same data to objectively quantify their performance. The results indicate that the feature-learning system, based on convolutional neural networks, significantly outperforms the classical feature-engineering based approach which uses manually engineered features and a random forest classifier. The former achieves an accuracy of 93.61 percent and the latter an accuracy of 87.25 percent.

  2. Planar slim-edge pixel sensors for the ATLAS upgrades

    NASA Astrophysics Data System (ADS)

    Altenheiner, S.; Goessling, C.; Jentzsch, J.; Klingenberg, R.; Lapsien, T.; Muenstermann, D.; Rummler, A.; Troska, G.; Wittig, T.

    2012-02-01

    The ATLAS detector at CERN is a general-purpose experiment at the Large Hadron Collider (LHC). The ATLAS Pixel Detector is the innermost tracking detector of ATLAS and requires a sufficient level of hermeticity to achieve superb track reconstruction performance. The current planar n-type pixel sensors feature a pixel matrix of n+-implantations which is (on the opposite p-side) surrounded by so-called guard rings to reduce the high voltage stepwise towards the cutting edge and an additional safety margin. Because of the inactive region around the active area, the sensor modules have been shingled on top of each other's edge which limits the thermal performance and adds complexity in the present detector. The first upgrade phase of the ATLAS pixel detector will consist of the insertable b-layer (IBL), an additional b-layer which will be inserted into the present detector in 2013. Several changes in the sensor design with respect to the existing detector had to be applied to comply with the IBL's specifications and are described in detail. A key issue for the ATLAS upgrades is a flat arrangement of the sensors. To maintain the required level of hermeticity in the detector, the inactive sensor edges have to be reduced to minimize the dead space between the adjacent detector modules. Unirradiated and irradiated sensors with the IBL design have been operated in test beams to study the efficiency performance in the sensor edge region and it was found that the inactive edge width could be reduced from 1100 μm to less than 250 μm.

  3. Charge Sharing and Charge Loss in a Cadmium-Zinc-Telluride Fine-Pixel Detector Array

    NASA Technical Reports Server (NTRS)

    Gaskin, J. A.; Sharma, D. P.; Ramsey, B. D.; Six, N. Frank (Technical Monitor)

    2002-01-01

    Because of its high atomic number, room temperature operation, low noise, and high spatial resolution a Cadmium-Zinc-Telluride (CZT) multi-pixel detector is ideal for hard x-ray astrophysical observation. As part of on-going research at MSFC (Marshall Space Flight Center) to develop multi-pixel CdZnTe detectors for this purpose, we have measured charge sharing and charge loss for a 4x4 (750micron pitch), lmm thick pixel array and modeled these results using a Monte-Carlo simulation. This model was then used to predict the amount of charge sharing for a much finer pixel array (with a 300micron pitch). Future work will enable us to compare the simulated results for the finer array to measured values.

  4. Spatial clustering of pixels of a multispectral image

    DOEpatents

    Conger, James Lynn

    2014-08-19

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

  5. Charge Loss and Charge Sharing Measurements for Two Different Pixelated Cadmium-Zinc-Telluride Detectors

    NASA Technical Reports Server (NTRS)

    Gaskin, Jessica; Sharma, Dharma; Ramsey, Brian; Seller, Paul

    2003-01-01

    As part of ongoing research at Marshall Space Flight Center, Cadmium-Zinc- Telluride (CdZnTe) pixilated detectors are being developed for use at the focal plane of the High Energy Replicated Optics (HERO) telescope. HERO requires a 64x64 pixel array with a spatial resolution of around 200 microns (with a 6m focal length) and high energy resolution (< 2% at 60keV). We are currently testing smaller arrays as a necessary first step towards this goal. In this presentation, we compare charge sharing and charge loss measurements between two devices that differ both electronically and geometrically. The first device consists of a 1-mm-thick piece of CdZnTe that is sputtered with a 4x4 array of pixels with pixel pitch of 750 microns (inter-pixel gap is 100 microns). The signal is read out using discrete ultra-low-noise preamplifiers, one for each of the 16 pixels. The second detector consists of a 2-mm-thick piece of CdZnTe that is sputtered with a 16x16 array of pixels with a pixel pitch of 300 microns (inter-pixel gap is 50 microns). Instead of using discrete preamplifiers, the crystal is bonded to an ASIC that provides all of the front-end electronics to each of the 256 pixels. what degree the bias voltage (i.e. the electric field) and hence the drift and diffusion coefficients affect our measurements. Further, we compare the measured results with simulated results and discuss to

  6. Experimental study of current loss and plasma formation in the Z machine post-hole convolute

    NASA Astrophysics Data System (ADS)

    Gomez, M. R.; Gilgenbach, R. M.; Cuneo, M. E.; Jennings, C. A.; McBride, R. D.; Waisman, E. M.; Hutsel, B. T.; Stygar, W. A.; Rose, D. V.; Maron, Y.

    2017-01-01

    The Z pulsed-power generator at Sandia National Laboratories drives high energy density physics experiments with load currents of up to 26 MA. Z utilizes a double post-hole convolute to combine the current from four parallel magnetically insulated transmission lines into a single transmission line just upstream of the load. Current loss is observed in most experiments and is traditionally attributed to inefficient convolute performance. The apparent loss current varies substantially for z-pinch loads with different inductance histories; however, a similar convolute impedance history is observed for all load types. This paper details direct spectroscopic measurements of plasma density, temperature, and apparent and actual plasma closure velocities within the convolute. Spectral measurements indicate a correlation between impedance collapse and plasma formation in the convolute. Absorption features in the spectra show the convolute plasma consists primarily of hydrogen, which likely forms from desorbed electrode contaminant species such as H2O , H2 , and hydrocarbons. Plasma densities increase from 1 ×1016 cm-3 (level of detectability) just before peak current to over 1 ×1017 cm-3 at stagnation (tens of ns later). The density seems to be highest near the cathode surface, with an apparent cathode to anode plasma velocity in the range of 35 - 50 cm /μ s . Similar plasma conditions and convolute impedance histories are observed in experiments with high and low losses, suggesting that losses are driven largely by load dynamics, which determine the voltage on the convolute.

  7. There is no MacWilliams identity for convolutional codes. [transmission gain comparison

    NASA Technical Reports Server (NTRS)

    Shearer, J. B.; Mceliece, R. J.

    1977-01-01

    An example is provided of two convolutional codes that have the same transmission gain but whose dual codes do not. This shows that no analog of the MacWilliams identity for block codes can exist relating the transmission gains of a convolutional code and its dual.

  8. Using convolutional decoding to improve time delay and phase estimation in digital communications

    DOEpatents

    Ormesher, Richard C.; Mason, John J.

    2010-01-26

    The time delay and/or phase of a communication signal received by a digital communication receiver can be estimated based on a convolutional decoding operation that the communication receiver performs on the received communication signal. If the original transmitted communication signal has been spread according to a spreading operation, a corresponding despreading operation can be integrated into the convolutional decoding operation.

  9. An estimation error bound for pixelated sensing

    NASA Astrophysics Data System (ADS)

    Kreucher, Chris; Bell, Kristine

    2016-05-01

    This paper considers the ubiquitous problem of estimating the state (e.g., position) of an object based on a series of noisy measurements. The standard approach is to formulate this problem as one of measuring the state (or a function of the state) corrupted by additive Gaussian noise. This model assumes both (i) the sensor provides a measurement of the true target (or, alternatively, a separate signal processing step has eliminated false alarms), and (ii) The error source in the measurement is accurately described by a Gaussian model. In reality, however, sensor measurement are often formed on a grid of pixels - e.g., Ground Moving Target Indication (GMTI) measurements are formed for a discrete set of (angle, range, velocity) voxels, and EO imagery is made on (x, y) grids. When a target is present in a pixel, therefore, uncertainty is not Gaussian (instead it is a boxcar function) and unbiased estimation is not generally possible as the location of the target within the pixel defines the bias of the estimator. It turns out that this small modification to the measurement model makes traditional bounding approaches not applicable. This paper discusses pixelated sensing in more detail and derives the minimum mean squared error (MMSE) bound for estimation in the pixelated scenario. We then use this error calculation to investigate the utility of using non-thresholded measurements.

  10. Mapping Electrical Crosstalk in Pixelated Sensor Arrays

    NASA Technical Reports Server (NTRS)

    Seshadri, S.; Cole, D. M.; Hancock, B. R.; Smith, R. M.

    2008-01-01

    Electronic coupling effects such as Inter-Pixel Capacitance (IPC) affect the quantitative interpretation of image data from CMOS, hybrid visible and infrared imagers alike. Existing methods of characterizing IPC do not provide a map of the spatial variation of IPC over all pixels. We demonstrate a deterministic method that provides a direct quantitative map of the crosstalk across an imager. The approach requires only the ability to reset single pixels to an arbitrary voltage, different from the rest of the imager. No illumination source is required. Mapping IPC independently for each pixel is also made practical by the greater S/N ratio achievable for an electrical stimulus than for an optical stimulus, which is subject to both Poisson statistics and diffusion effects of photo-generated charge. The data we present illustrates a more complex picture of IPC in Teledyne HgCdTe and HyViSi focal plane arrays than is presently understood, including the presence of a newly discovered, long range IPC in the HyViSi FPA that extends tens of pixels in distance, likely stemming from extended field effects in the fully depleted substrate. The sensitivity of the measurement approach has been shown to be good enough to distinguish spatial structure in IPC of the order of 0.1%.

  11. Pixels, Blocks of Pixels, and Polygons: Choosing a Spatial Unit for Thematic Accuracy Assessment

    EPA Science Inventory

    Pixels, polygons, and blocks of pixels are all potentially viable spatial assessment units for conducting an accuracy assessment. We develop a statistical population-based framework to examine how the spatial unit chosen affects the outcome of an accuracy assessment. The populati...

  12. Radiation tolerance of CMOS monolithic active pixel sensors with self-biased pixels

    NASA Astrophysics Data System (ADS)

    Deveaux, M.; Amar-Youcef, S.; Besson, A.; Claus, G.; Colledani, C.; Dorokhov, M.; Dritsa, C.; Dulinski, W.; Fröhlich, I.; Goffe, M.; Grandjean, D.; Heini, S.; Himmi, A.; Hu, C.; Jaaskelainen, K.; Müntz, C.; Shabetai, A.; Stroth, J.; Szelezniak, M.; Valin, I.; Winter, M.

    2010-12-01

    CMOS monolithic active pixel sensors (MAPS) are proposed as a technology for various vertex detectors in nuclear and particle physics. We discuss the mechanisms of ionizing radiation damage on MAPS hosting the dead time free, so-called self bias pixel. Moreover, we introduce radiation hardened sensor designs which allow operating detectors after exposing them to irradiation doses above 1 Mrad.

  13. Adaptive Multi-Objective Sub-Pixel Mapping Framework Based on Memetic Algorithm for Hyperspectral Remote Sensing Imagery

    NASA Astrophysics Data System (ADS)

    Zhong, Y.; Zhang, L.

    2012-07-01

    Sub-pixel mapping technique can specify the location of each class within the pixels based on the assumption of spatial dependence. Traditional sub-pixel mapping algorithms only consider the spatial dependence at the pixel level. The spatial dependence of each sub-pixel is ignored and sub-pixel spatial relation is lost. In this paper, a novel multi-objective sub-pixel mapping framework based on memetic algorithm, namely MSMF, is proposed. In MSMF, the sub-pixel mapping is transformed to a multi-objective optimization problem, which maximizing the spatial dependence index (SDI) and Moran's I, synchronously. Memetic algorithm is utilized to solve the multi-objective problem, which combines global search strategies with local search heuristics. In this framework, the sub-pixel mapping problem can be solved using different evolutionary algorithms and local algorithms. In this paper, memetic algorithm based on clonal selection algorithm (CSA) and random swapping as an example is designed and applied simultaneously in the proposed MSMF. In MSMF, CSA inherits the biologic properties of human immune systems, i.e. clone, mutation, memory, to search the possible sub-pixel mapping solution in the global space. After the exploration based on CSA, the local search based on random swapping is employed to dynamically decide which neighbourhood should be selected to stress exploitation in each generation. In addition, a solution set is used in MSMF to hold and update the obtained non-dominated solutions for multi-objective problem. Experimental results demonstrate that the proposed approach outperform traditional sub-pixel mapping algorithms, and hence provide an effective option for sub-pixel mapping of hyperspectral remote sensing imagery.

  14. Active Pixel Sensors: Are CCD's Dinosaurs?

    NASA Technical Reports Server (NTRS)

    Fossum, Eric R.

    1993-01-01

    Charge-coupled devices (CCD's) are presently the technology of choice for most imaging applications. In the 23 years since their invention in 1970, they have evolved to a sophisticated level of performance. However, as with all technologies, we can be certain that they will be supplanted someday. In this paper, the Active Pixel Sensor (APS) technology is explored as a possible successor to the CCD. An active pixel is defined as a detector array technology that has at least one active transistor within the pixel unit cell. The APS eliminates the need for nearly perfect charge transfer -- the Achilles' heel of CCDs. This perfect charge transfer makes CCD's radiation 'soft,' difficult to use under low light conditions, difficult to manufacture in large array sizes, difficult to integrate with on-chip electronics, difficult to use at low temperatures, difficult to use at high frame rates, and difficult to manufacture in non-silicon materials that extend wavelength response.

  15. Towards spark-proof gaseous pixel detectors

    NASA Astrophysics Data System (ADS)

    Tsigaridas, S.; Beuzekom, M. v.; Chan, H. W.; Graaf, H. v. d.; Hartjes, F.; Heijhoff, K.; Hessey, N. P.; Prodanovic, V.

    2016-11-01

    The micro-pattern gaseous pixel detector, is a promising technology for imaging and particle tracking applications. It is a combination of a gas layer acting as detection medium and a CMOS pixelated readout-chip. As a prevention against discharges we deposit a protection layer on the chip and then integrate on top a micromegas-like amplification structure. With this technology we are able to reconstruct 3D track segments of particles passing through the gas thanks to the functionality of the chip. We have turned a Timepix3 chip into a gaseous pixel detector and tested it at the SPS at Cern. The preliminary results are promising and within the expectations. However, the spark protection layer needs further improvement to make reliable detectors. For this reason, we have created a setup for spark-testing. We present the first results obtained from the lab-measurements along with preliminary results from the testbeam.

  16. Pixel lensing observations towards globular clusters

    NASA Astrophysics Data System (ADS)

    Cardone, V. F.; Cantiello, M.

    2003-07-01

    It has been suggested that a monitoring program employing the pixel lensing method to search for microlensing events towards galactic globular clusters may increase the statistics and discriminate among different halo models. Stimulated by this proposal, we evaluate an upper limit to the pixel lensing event rate for such a survey. Four different dark halo models have been considered changing both the flattening and the slope of the mass density profile. The lens mass function has been modelled as a homogenous power - law for mu in (mul, muu) and both the mass limits and the slope of the mass function have been varied to investigate their effect on the rate. The target globular clusters have been selected in order to minimize the disk contribution to the event rate. We find that a pixel lensing survey towards globular clusters is unable to discriminate among different halo models since the number of detectable events is too small to allow any reliable statistical analysis.

  17. Vivid, full-color aluminum plasmonic pixels

    PubMed Central

    Olson, Jana; Manjavacas, Alejandro; Liu, Lifei; Chang, Wei-Shun; Foerster, Benjamin; King, Nicholas S.; Knight, Mark W.; Nordlander, Peter; Halas, Naomi J.; Link, Stephan

    2014-01-01

    Aluminum is abundant, low in cost, compatible with complementary metal-oxide semiconductor manufacturing methods, and capable of supporting tunable plasmon resonance structures that span the entire visible spectrum. However, the use of Al for color displays has been limited by its intrinsically broad spectral features. Here we show that vivid, highly polarized, and broadly tunable color pixels can be produced from periodic patterns of oriented Al nanorods. Whereas the nanorod longitudinal plasmon resonance is largely responsible for pixel color, far-field diffractive coupling is used to narrow the plasmon linewidth, enabling monochromatic coloration and significantly enhancing the far-field scattering intensity of the individual nanorod elements. The bright coloration can be observed with p-polarized white light excitation, consistent with the use of this approach in display devices. The resulting color pixels are constructed with a simple design, are compatible with scalable fabrication methods, and provide contrast ratios exceeding 100:1. PMID:25225385

  18. GALAPAGOS: from pixels to parameters

    NASA Astrophysics Data System (ADS)

    Barden, Marco; Häußler, Boris; Peng, Chien Y.; McIntosh, Daniel H.; Guo, Yicheng

    2012-05-01

    To automate source detection, two-dimensional light profile Sérsic modelling and catalogue compilation in large survey applications, we introduce a new code Galaxy Analysis over Large Areas: Parameter Assessment by GALFITting Objects from SEXTRACTOR (GALAPAGOS). Based on a single set-up, GALAPAGOS can process a complete set of survey images. It detects sources in the data, estimates a local sky background, cuts postage stamp images for all sources, prepares object masks, performs Sérsic fitting including neighbours and compiles all objects in a final output catalogue. For the initial source detection, GALAPAGOS applies SEXTRACTOR, while GALFIT is incorporated for modelling Sérsic profiles. It measures the background sky involved in the Sérsic fitting by means of a flux growth curve. GALAPAGOS determines postage stamp sizes based on SEXTRACTOR shape parameters. In order to obtain precise model parameters, GALAPAGOS incorporates a complex sorting mechanism and makes use of modern CPU's multiplexing capabilities. It combines SEXTRACTOR and GALFIT data in a single output table. When incorporating information from overlapping tiles, GALAPAGOS automatically removes multiple entries from identical sources. GALAPAGOS is programmed in the Interactive Data Language (IDL). We test the stability and the ability to properly recover structural parameters extensively with artificial image simulations. Moreover, we apply GALAPAGOS successfully to the STAGES data set. For one-orbit Hubble Space Telescope data, a single 2.2-GHz CPU processes about 1000 primary sources per 24 h. Note that GALAPAGOS results depend critically on the user-defined parameter set-up. This paper provides useful guidelines to help the user make sensible choices.

  19. Modulation transfer function of a trapezoidal pixel array detector

    NASA Astrophysics Data System (ADS)

    Wang, Fan; Guo, Rongli; Ni, Jinping; Dong, Tao

    2016-01-01

    The modulation transfer function (MTF) is the tool most commonly used for quantifying the performance of an electro-optical imaging system. Recently, trapezoid-shaped pixels were designed and used in a retina-like sensor in place of rectangular-shaped pixels. The MTF of a detector with a trapezoidal pixel array is determined according to its definition. Additionally, the MTFs of detectors with differently shaped pixels, but the same pixel areas, are compared. The results show that the MTF values of the trapezoidal pixel array detector are obviously larger than those of rectangular and triangular pixel array detectors at the same frequencies.

  20. Low-dose CT via convolutional neural network

    PubMed Central

    Chen, Hu; Zhang, Yi; Zhang, Weihua; Liao, Peixi; Li, Ke; Zhou, Jiliu; Wang, Ge

    2017-01-01

    In order to reduce the potential radiation risk, low-dose CT has attracted an increasing attention. However, simply lowering the radiation dose will significantly degrade the image quality. In this paper, we propose a new noise reduction method for low-dose CT via deep learning without accessing original projection data. A deep convolutional neural network is here used to map low-dose CT images towards its corresponding normal-dose counterparts in a patch-by-patch fashion. Qualitative results demonstrate a great potential of the proposed method on artifact reduction and structure preservation. In terms of the quantitative metrics, the proposed method has showed a substantial improvement on PSNR, RMSE and SSIM than the competing state-of-art methods. Furthermore, the speed of our method is one order of magnitude faster than the iterative reconstruction and patch-based image denoising methods. PMID:28270976

  1. Drug-Drug Interaction Extraction via Convolutional Neural Networks

    PubMed Central

    Liu, Shengyu; Tang, Buzhou; Chen, Qingcai; Wang, Xiaolong

    2016-01-01

    Drug-drug interaction (DDI) extraction as a typical relation extraction task in natural language processing (NLP) has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM) with a large number of manually defined features. Recently, convolutional neural networks (CNN), a robust machine learning method which almost does not need manually defined features, has exhibited great potential for many NLP tasks. It is worth employing CNN for DDI extraction, which has never been investigated. We proposed a CNN-based method for DDI extraction. Experiments conducted on the 2013 DDIExtraction challenge corpus demonstrate that CNN is a good choice for DDI extraction. The CNN-based DDI extraction method achieves an F-score of 69.75%, which outperforms the existing best performing method by 2.75%. PMID:26941831

  2. Small convolution kernels for high-fidelity image restoration

    NASA Technical Reports Server (NTRS)

    Reichenbach, Stephen E.; Park, Stephen K.

    1991-01-01

    An algorithm is developed for computing the mean-square-optimal values for small, image-restoration kernels. The algorithm is based on a comprehensive, end-to-end imaging system model that accounts for the important components of the imaging process: the statistics of the scene, the point-spread function of the image-gathering device, sampling effects, noise, and display reconstruction. Subject to constraints on the spatial support of the kernel, the algorithm generates the kernel values that restore the image with maximum fidelity, that is, the kernel minimizes the expected mean-square restoration error. The algorithm is consistent with the derivation of the spatially unconstrained Wiener filter, but leads to a small, spatially constrained kernel that, unlike the unconstrained filter, can be efficiently implemented by convolution. Simulation experiments demonstrate that for a wide range of imaging systems these small kernels can restore images with fidelity comparable to images restored with the unconstrained Wiener filter.

  3. Convolution quadrature for the wave equation with impedance boundary conditions

    NASA Astrophysics Data System (ADS)

    Sauter, S. A.; Schanz, M.

    2017-04-01

    We consider the numerical solution of the wave equation with impedance boundary conditions and start from a boundary integral formulation for its discretization. We develop the generalized convolution quadrature (gCQ) to solve the arising acoustic retarded potential integral equation for this impedance problem. For the special case of scattering from a spherical object, we derive representations of analytic solutions which allow to investigate the effect of the impedance coefficient on the acoustic pressure analytically. We have performed systematic numerical experiments to study the convergence rates as well as the sensitivity of the acoustic pressure from the impedance coefficients. Finally, we apply this method to simulate the acoustic pressure in a building with a fairly complicated geometry and to study the influence of the impedance coefficient also in this situation.

  4. Discovering characteristic landmarks on ancient coins using convolutional networks

    NASA Astrophysics Data System (ADS)

    Kim, Jongpil; Pavlovic, Vladimir

    2017-01-01

    We propose a method to find characteristic landmarks and recognize ancient Roman imperial coins using deep convolutional neural networks (CNNs) combined with expert-designed domain hierarchies. We first propose a framework to recognize Roman coins that exploits the hierarchical knowledge structure embedded in the coin domain, which we combine with the CNN-based category classifiers. We next formulate an optimization problem to discover class-specific salient coin regions. Analysis of discovered salient regions confirms that they are largely consistent with human expert annotations. Experimental results show that the proposed framework is able to effectively recognize ancient Roman coins as well as successfully identify landmarks on the coins. For this research, we have collected a Roman coin dataset where all coins are annotated and consist of obverse (head) and reverse (tail) images.

  5. Tomography by iterative convolution - Empirical study and application to interferometry

    NASA Technical Reports Server (NTRS)

    Vest, C. M.; Prikryl, I.

    1984-01-01

    An algorithm for computer tomography has been developed that is applicable to reconstruction from data having incomplete projections because an opaque object blocks some of the probing radiation as it passes through the object field. The algorithm is based on iteration between the object domain and the projection (Radon transform) domain. Reconstructions are computed during each iteration by the well-known convolution method. Although it is demonstrated that this algorithm does not converge, an empirically justified criterion for terminating the iteration when the most accurate estimate has been computed is presented. The algorithm has been studied by using it to reconstruct several different object fields with several different opaque regions. It also has been used to reconstruct aerodynamic density fields from interferometric data recorded in wind tunnel tests.

  6. Finding the complete path and weight enumerators of convolutional codes

    NASA Technical Reports Server (NTRS)

    Onyszchuk, I.

    1990-01-01

    A method for obtaining the complete path enumerator T(D, L, I) of a convolutional code is described. A system of algebraic equations is solved, using a new algorithm for computing determinants, to obtain T(D, L, I) for the (7,1/2) NASA standard code. Generating functions, derived from T(D, L, I) are used to upper bound Viterbi decoder error rates. This technique is currently feasible for constraint length K less than 10 codes. A practical, fast algorithm is presented for computing the leading nonzero coefficients of the generating functions used to bound the performance of constraint length K less than 20 codes. Code profiles with about 50 nonzero coefficients are obtained with this algorithm for the experimental K = 15, rate 1/4, code in the Galileo mission and for the proposed K = 15, rate 1/6, 2-dB code.

  7. Enhanced Line Integral Convolution with Flow Feature Detection

    NASA Technical Reports Server (NTRS)

    Lane, David; Okada, Arthur

    1996-01-01

    The Line Integral Convolution (LIC) method, which blurs white noise textures along a vector field, is an effective way to visualize overall flow patterns in a 2D domain. The method produces a flow texture image based on the input velocity field defined in the domain. Because of the nature of the algorithm, the texture image tends to be blurry. This sometimes makes it difficult to identify boundaries where flow separation and reattachments occur. We present techniques to enhance LIC texture images and use colored texture images to highlight flow separation and reattachment boundaries. Our techniques have been applied to several flow fields defined in 3D curvilinear multi-block grids and scientists have found the results to be very useful.

  8. Learning to Generate Chairs, Tables and Cars with Convolutional Networks.

    PubMed

    Dosovitskiy, Alexey; Springenberg, Jost; Tatarchenko, Maxim; Brox, Thomas

    2016-05-12

    We train generative 'up-convolutional' neural networks which are able to generate images of objects given object style, viewpoint, and color. We train the networks on rendered 3D models of chairs, tables, and cars. Our experiments show that the networks do not merely learn all images by heart, but rather find a meaningful representation of 3D models allowing them to assess the similarity of different models, interpolate between given views to generate the missing ones, extrapolate views, and invent new objects not present in the training set by recombining training instances, or even two different object classes. Moreover, we show that such generative networks can be used to find correspondences between different objects from the dataset, outperforming existing approaches on this task.

  9. Modifying real convolutional codes for protecting digital filtering systems

    NASA Technical Reports Server (NTRS)

    Redinbo, G. R.; Zagar, Bernhard

    1993-01-01

    A novel method is proposed for protecting digital filters from temporary and permanent failures that are not easily detected by conventional fault-tolerant computer design principles, on the basis of the error-detecting properties of real convolutional codes. Erroneous behavior is detected by externally comparing the calculated and regenerated parity samples. Great simplifications are obtainable by modifying the code structure to yield simplified parity channels with finite impulse response structures. A matrix equation involving the original parity values of the code and the polynomial of the digital filter's transfer function is formed, and row manipulations separate this equation into a set of homogeneous equations constraining the modifying scaling coefficients and another set which defines the code parity values' implementation.

  10. Stability Training for Convolutional Neural Nets in LArTPC

    NASA Astrophysics Data System (ADS)

    Lindsay, Matt; Wongjirad, Taritree

    2017-01-01

    Convolutional Neural Nets (CNNs) are the state of the art for many problems in computer vision and are a promising method for classifying interactions in Liquid Argon Time Projection Chambers (LArTPCs) used in neutrino oscillation experiments. Despite the good performance of CNN's, they are not without drawbacks, chief among them is vulnerability to noise and small perturbations to the input. One solution to this problem is a modification to the learning process called Stability Training developed by Zheng et al. We verify existing work and demonstrate volatility caused by simple Gaussian noise and also that the volatility can be nearly eliminated with Stability Training. We then go further and show that a traditional CNN is also vulnerable to realistic experimental noise and that a stability trained CNN remains accurate despite noise. This further adds to the optimism for CNNs for work in LArTPCs and other applications.

  11. Convolutional Neural Networks for patient-specific ECG classification.

    PubMed

    Kiranyaz, Serkan; Ince, Turker; Hamila, Ridha; Gabbouj, Moncef

    2015-01-01

    We propose a fast and accurate patient-specific electrocardiogram (ECG) classification and monitoring system using an adaptive implementation of 1D Convolutional Neural Networks (CNNs) that can fuse feature extraction and classification into a unified learner. In this way, a dedicated CNN will be trained for each patient by using relatively small common and patient-specific training data and thus it can also be used to classify long ECG records such as Holter registers in a fast and accurate manner. Alternatively, such a solution can conveniently be used for real-time ECG monitoring and early alert system on a light-weight wearable device. The experimental results demonstrate that the proposed system achieves a superior classification performance for the detection of ventricular ectopic beats (VEB) and supraventricular ectopic beats (SVEB).

  12. Rapid Exact Signal Scanning With Deep Convolutional Neural Networks

    NASA Astrophysics Data System (ADS)

    Thom, Markus; Gritschneder, Franz

    2017-03-01

    A rigorous formulation of the dynamics of a signal processing scheme aimed at dense signal scanning without any loss in accuracy is introduced and analyzed. Related methods proposed in the recent past lack a satisfactory analysis of whether they actually fulfill any exactness constraints. This is improved through an exact characterization of the requirements for a sound sliding window approach. The tools developed in this paper are especially beneficial if Convolutional Neural Networks are employed, but can also be used as a more general framework to validate related approaches to signal scanning. The proposed theory helps to eliminate redundant computations and renders special case treatment unnecessary, resulting in a dramatic boost in efficiency particularly on massively parallel processors. This is demonstrated both theoretically in a computational complexity analysis and empirically on modern parallel processors.

  13. Plane-wave decomposition by spherical-convolution microphone array

    NASA Astrophysics Data System (ADS)

    Rafaely, Boaz; Park, Munhum

    2004-05-01

    Reverberant sound fields are widely studied, as they have a significant influence on the acoustic performance of enclosures in a variety of applications. For example, the intelligibility of speech in lecture rooms, the quality of music in auditoria, the noise level in offices, and the production of 3D sound in living rooms are all affected by the enclosed sound field. These sound fields are typically studied through frequency response measurements or statistical measures such as reverberation time, which do not provide detailed spatial information. The aim of the work presented in this seminar is the detailed analysis of reverberant sound fields. A measurement and analysis system based on acoustic theory and signal processing, designed around a spherical microphone array, is presented. Detailed analysis is achieved by decomposition of the sound field into waves, using spherical Fourier transform and spherical convolution. The presentation will include theoretical review, simulation studies, and initial experimental results.

  14. Truncation Depth Rule-of-Thumb for Convolutional Codes

    NASA Technical Reports Server (NTRS)

    Moision, Bruce

    2009-01-01

    In this innovation, it is shown that a commonly used rule of thumb (that the truncation depth of a convolutional code should be five times the memory length, m, of the code) is accurate only for rate 1/2 codes. In fact, the truncation depth should be 2.5 m/(1 - r), where r is the code rate. The accuracy of this new rule is demonstrated by tabulating the distance properties of a large set of known codes. This new rule was derived by bounding the losses due to truncation as a function of the code rate. With regard to particular codes, a good indicator of the required truncation depth is the path length at which all paths that diverge from a particular path have accumulated the minimum distance of the code. It is shown that the new rule of thumb provides an accurate prediction of this depth for codes of varying rates.

  15. Radio frequency interference mitigation using deep convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Akeret, J.; Chang, C.; Lucchi, A.; Refregier, A.

    2017-01-01

    We propose a novel approach for mitigating radio frequency interference (RFI) signals in radio data using the latest advances in deep learning. We employ a special type of Convolutional Neural Network, the U-Net, that enables the classification of clean signal and RFI signatures in 2D time-ordered data acquired from a radio telescope. We train and assess the performance of this network using the HIDE &SEEK radio data simulation and processing packages, as well as early Science Verification data acquired with the 7m single-dish telescope at the Bleien Observatory. We find that our U-Net implementation is showing competitive accuracy to classical RFI mitigation algorithms such as SEEK's SUMTHRESHOLD implementation. We publish our U-Net software package on GitHub under GPLv3 license.

  16. Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition.

    PubMed

    He, Kaiming; Zhang, Xiangyu; Ren, Shaoqing; Sun, Jian

    2015-09-01

    Existing deep convolutional neural networks (CNNs) require a fixed-size (e.g., 224 × 224) input image. This requirement is "artificial" and may reduce the recognition accuracy for the images or sub-images of an arbitrary size/scale. In this work, we equip the networks with another pooling strategy, "spatial pyramid pooling", to eliminate the above requirement. The new network structure, called SPP-net, can generate a fixed-length representation regardless of image size/scale. Pyramid pooling is also robust to object deformations. With these advantages, SPP-net should in general improve all CNN-based image classification methods. On the ImageNet 2012 dataset, we demonstrate that SPP-net boosts the accuracy of a variety of CNN architectures despite their different designs. On the Pascal VOC 2007 and Caltech101 datasets, SPP-net achieves state-of-the-art classification results using a single full-image representation and no fine-tuning. The power of SPP-net is also significant in object detection. Using SPP-net, we compute the feature maps from the entire image only once, and then pool features in arbitrary regions (sub-images) to generate fixed-length representations for training the detectors. This method avoids repeatedly computing the convolutional features. In processing test images, our method is 24-102 × faster than the R-CNN method, while achieving better or comparable accuracy on Pascal VOC 2007. In ImageNet Large Scale Visual Recognition Challenge (ILSVRC) 2014, our methods rank #2 in object detection and #3 in image classification among all 38 teams. This manuscript also introduces the improvement made for this competition.

  17. Commissioning of the ATLAS pixel detector

    SciTech Connect

    ATLAS Collaboration; Golling, Tobias

    2008-09-01

    The ATLAS pixel detector is a high precision silicon tracking device located closest to the LHC interaction point. It belongs to the first generation of its kind in a hadron collider experiment. It will provide crucial pattern recognition information and will largely determine the ability of ATLAS to precisely track particle trajectories and find secondary vertices. It was the last detector to be installed in ATLAS in June 2007, has been fully connected and tested in-situ during spring and summer 2008, and is ready for the imminent LHC turn-on. The highlights of the past and future commissioning activities of the ATLAS pixel system are presented.

  18. Physics performance of the ATLAS pixel detector

    NASA Astrophysics Data System (ADS)

    Tsuno, S.

    2017-01-01

    In preparation for LHC Run-2 the ATLAS detector introduced a new pixel detector, the Insertable B-Layer (IBL). This detector is located between the beampipe and what was the innermost pixel layer. The tracking and vertex reconstruction are significantly improved and good performance is expected in high level objects such a b-quark jet tagging. This in turn, leads to better physics results. This note summarizes the impact of the IBL detector on physics results, especially focusing on the analyses using b-quark jets throughout 2016 summer physics program.

  19. HST/WFC3 Characteristics: gain, post-flash stability, UVIS low-sensitivity pixels, persistence, IR flats and bad pixel table

    NASA Astrophysics Data System (ADS)

    Gunning, Heather C.; Baggett, Sylvia; Gosmeyer, Catherine M.; Long, Knox S.; Ryan, Russell E.; MacKenty, John W.; Durbin, Meredith

    2015-08-01

    The Wide Field Camera 3 (WFC3) is a fourth-generation imaging instrument on the Hubble Space Telescope (HST). Installed in May 2009, WFC3 is comprised of two observational channels covering wavelengths from UV/Visible (UVIS) to infrared (IR); both have been performing well on-orbit. We discuss the gain stability of both WFC3 channel detectors from ground testing through present day. For UVIS, we detail a low-sensitivity pixel population that evolves during the time between anneals, but is largely reset by the annealing procedure. We characterize the post-flash LED lamp stability, used and recommended to mitigate CTE effects for observations with less than 12e-/pixel backgrounds. We present mitigation options for IR persistence during and after observations. Finally, we give an overview on the construction of the IR flats and provide updates on the bad pixel table.

  20. Cantilever tilt causing amplitude related convolution in dynamic mode atomic force microscopy.

    PubMed

    Wang, Chunmei; Sun, Jielin; Itoh, Hiroshi; Shen, Dianhong; Hu, Jun

    2011-01-01

    It is well known that the topography in atomic force microscopy (AFM) is a convolution of the tip's shape and the sample's geometry. The classical convolution model was established in contact mode assuming a static probe, but it is no longer valid in dynamic mode AFM. It is still not well understood whether or how the vibration of the probe in dynamic mode affects the convolution. Such ignorance complicates the interpretation of the topography. Here we propose a convolution model for dynamic mode by taking into account the typical design of the cantilever tilt in AFMs, which leads to a different convolution from that in contact mode. Our model indicates that the cantilever tilt results in a dynamic convolution affected by the absolute value of the amplitude, especially in the case that corresponding contact convolution has sharp edges beyond certain angle. The effect was experimentally demonstrated by a perpendicular SiO(2)/Si super-lattice structure. Our model is useful for quantitative characterizations in dynamic mode, especially in probe characterization and critical dimension measurements.

  1. Dynamic holography using pixelated light modulators.

    PubMed

    Zwick, Susanne; Haist, Tobias; Warber, Michael; Osten, Wolfgang

    2010-09-01

    Dynamic holography using spatial light modulators is a very flexible technique that offers various new applications compared to static holography. We give an overview on the technical background of dynamic holography focusing on pixelated spatial light modulators and their technical restrictions, and we present a selection of the numerous applications of dynamic holography.

  2. Pixel telescope test in STAR at RHIC

    NASA Astrophysics Data System (ADS)

    Sun, Xiangming; Szelezniak, Michal; Greiner, Leo; Matis, Howard; Vu, Chinh; Stezelberger, Thorsten; Wieman, Howard

    2007-10-01

    The STAR experiment at RHIC is designing a new inner vertex detector called the Heavy Flavor Tracker (HFT). The HFT's innermost two layers is called the PIXEL detector which uses Monolithic Active Pixel Sensor technology (MAPS). To test the MAPS technology, we just constructed and tested a telescope. The telescope uses a stack of three MIMOSTAR2 chips, Each MIMOSTAR2 sensor, which was designed by IPHC, is an array of 132x128 pixels with a square pixel size of 30 μ. The readout of the telescope makes use of the ALICE DDL/SIU cards, which is compatible with the future STAR data acquisition system called DAQ1000. The telescope was first studied in a 1.2 GeV/c electron beam at LBNL's Advanced Light Source. Afterwards, the telescope was outside the STAR magnet, and then later inside it, 145 cm away from STAR's center. We will describe this first test of MAPS technology in a collider environment, and report on the occupancy, particle flux, and performance of the telescope.

  3. Convolution representation of the relation between total electron density and that of s states in closed-shell atoms

    NASA Astrophysics Data System (ADS)

    Pucci, R.; March, N. H.

    1987-01-01

    Motivated by the Coulomb-field result that the derivative of the density ρ(r) for an arbitrary number of closed shells is directly proportional to the s-state density ρs(r), we have explored for closed-shell atoms a convolution relation between ρs(r) and ∂ρ/∂r. This relation is most readily expressed in K space, and we thereby establish certain relations between the scattering factors f(K) and fs(K) corresponding to total density and s density, respectively. The method is illustrated by using near-Hartree-Fock accuracy data of Clementi for closed-shell atoms Ne and Ar. For the Hartree-Fock theory, it is shown that at large r, ρs(r)~r-4ρ(r). Use is made in the convolution representation of the electron-nuclear potential energy of the closed-shell atom and the second derivative ∂2ρ/∂r2 evaluated at the nucleus.

  4. Optimal convolution SOR acceleration of waveform relaxation with application to semiconductor device simulation

    NASA Technical Reports Server (NTRS)

    Reichelt, Mark

    1993-01-01

    In this paper we describe a novel generalized SOR (successive overrelaxation) algorithm for accelerating the convergence of the dynamic iteration method known as waveform relaxation. A new convolution SOR algorithm is presented, along with a theorem for determining the optimal convolution SOR parameter. Both analytic and experimental results are given to demonstrate that the convergence of the convolution SOR algorithm is substantially faster than that of the more obvious frequency-independent waveform SOR algorithm. Finally, to demonstrate the general applicability of this new method, it is used to solve the differential-algebraic system generated by spatial discretization of the time-dependent semiconductor device equations.

  5. A near-infrared 64-pixel superconducting nanowire single photon detector array with integrated multiplexed readout

    SciTech Connect

    Allman, M. S. Verma, V. B.; Stevens, M.; Gerrits, T.; Horansky, R. D.; Lita, A. E.; Mirin, R.; Nam, S. W.; Marsili, F.; Beyer, A.; Shaw, M. D.; Kumor, D.

    2015-05-11

    We demonstrate a 64-pixel free-space-coupled array of superconducting nanowire single photon detectors optimized for high detection efficiency in the near-infrared range. An integrated, readily scalable, multiplexed readout scheme is employed to reduce the number of readout lines to 16. The cryogenic, optical, and electronic packaging to read out the array as well as characterization measurements are discussed.

  6. Adaptive bad pixel correction algorithm for IRFPA based on PCNN

    NASA Astrophysics Data System (ADS)

    Leng, Hanbing; Zhou, Zuofeng; Cao, Jianzhong; Yi, Bo; Yan, Aqi; Zhang, Jian

    2013-10-01

    Bad pixels and response non-uniformity are the primary obstacles when IRFPA is used in different thermal imaging systems. The bad pixels of IRFPA include fixed bad pixels and random bad pixels. The former is caused by material or manufacture defect and their positions are always fixed, the latter is caused by temperature drift and their positions are always changing. Traditional radiometric calibration-based bad pixel detection and compensation algorithm is only valid to the fixed bad pixels. Scene-based bad pixel correction algorithm is the effective way to eliminate these two kinds of bad pixels. Currently, the most used scene-based bad pixel correction algorithm is based on adaptive median filter (AMF). In this algorithm, bad pixels are regarded as image noise and then be replaced by filtered value. However, missed correction and false correction often happens when AMF is used to handle complex infrared scenes. To solve this problem, a new adaptive bad pixel correction algorithm based on pulse coupled neural networks (PCNN) is proposed. Potential bad pixels are detected by PCNN in the first step, then image sequences are used periodically to confirm the real bad pixels and exclude the false one, finally bad pixels are replaced by the filtered result. With the real infrared images obtained from a camera, the experiment results show the effectiveness of the proposed algorithm.

  7. Design Methodology: ASICs with complex in-pixel processing for Pixel Detectors

    SciTech Connect

    Fahim, Farah

    2014-10-31

    The development of Application Specific Integrated Circuits (ASIC) for pixel detectors with complex in-pixel processing using Computer Aided Design (CAD) tools that are, themselves, mainly developed for the design of conventional digital circuits requires a specialized approach. Mixed signal pixels often require parasitically aware detailed analog front-ends and extremely compact digital back-ends with more than 1000 transistors in small areas below 100μm x 100μm. These pixels are tiled to create large arrays, which have the same clock distribution and data readout speed constraints as in, for example, micro-processors. The methodology uses a modified mixed-mode on-top digital implementation flow to not only harness the tool efficiency for timing and floor-planning but also to maintain designer control over compact parasitically aware layout.

  8. WFC3/IR Cycle 19 Bad Pixel Table Update

    NASA Astrophysics Data System (ADS)

    Hilbert, B.

    2012-06-01

    Using data from Cycles 17, 18, and 19, we have updated the IR channel bad pixel table for WFC3. The bad pixel table contains flags that mark the position of pixels that are dead, unstable, have a bad zeroth read value, or are affected by "blobs". In all, 28,500 of the science pixels (2.77%) are flagged as bad. Observers are encouraged to dither their observations as a means of lessening the effects of these bad pixels. The new bad pixel table is in the calibration database system (CDBS) as w681807ii_bpx.fits.

  9. Design methodology: edgeless 3D ASICs with complex in-pixel processing for pixel detectors

    SciTech Connect

    Fahim Farah, Fahim Farah; Deptuch, Grzegorz W.; Hoff, James R.; Mohseni, Hooman

    2015-08-28

    The design methodology for the development of 3D integrated edgeless pixel detectors with in-pixel processing using Electronic Design Automation (EDA) tools is presented. A large area 3 tier 3D detector with one sensor layer and two ASIC layers containing one analog and one digital tier, is built for x-ray photon time of arrival measurement and imaging. A full custom analog pixel is 65μm x 65μm. It is connected to a sensor pixel of the same size on one side, and on the other side it has approximately 40 connections to the digital pixel. A 32 x 32 edgeless array without any peripheral functional blocks constitutes a sub-chip. The sub-chip is an indivisible unit, which is further arranged in a 6 x 6 array to create the entire 1.248cm x 1.248cm ASIC. Each chip has 720 bump-bond I/O connections, on the back of the digital tier to the ceramic PCB. All the analog tier power and biasing is conveyed through the digital tier from the PCB. The assembly has no peripheral functional blocks, and hence the active area extends to the edge of the detector. This was achieved by using a few flavors of almost identical analog pixels (minimal variation in layout) to allow for peripheral biasing blocks to be placed within pixels. The 1024 pixels within a digital sub-chip array have a variety of full custom, semi-custom and automated timing driven functional blocks placed together. The methodology uses a modified mixed-mode on-top digital implementation flow to not only harness the tool efficiency for timing and floor-planning but also to maintain designer control over compact parasitically aware layout. The methodology uses the Cadence design platform, however it is not limited to this tool.

  10. The Luminous Convolution Model-The light side of dark matter

    NASA Astrophysics Data System (ADS)

    Cisneros, Sophia; Oblath, Noah; Formaggio, Joe; Goedecke, George; Chester, David; Ott, Richard; Ashley, Aaron; Rodriguez, Adrianna

    2014-03-01

    We present a heuristic model for predicting the rotation curves of spiral galaxies. The Luminous Convolution Model (LCM) utilizes Lorentz-type transformations of very small changes in the photon's frequencies from curved space-times to construct a dynamic mass model of galaxies. These frequency changes are derived using the exact solution to the exterior Kerr wave equation, as opposed to a linearized treatment. The LCM Lorentz-type transformations map between the emitter and the receiver rotating galactic frames, and then to the associated flat frames in each galaxy where the photons are emitted and received. This treatment necessarily rests upon estimates of the luminous matter in both the emitter and the receiver galaxies. The LCM is tested on a sample of 22 randomly chosen galaxies, represented in 33 different data sets. LCM fits are compared to the Navarro, Frenk & White (NFW) Dark Matter Model and to the Modified Newtonian Dynamics (MOND) model when possible. The high degree of sensitivity of the LCM to the initial assumption of a luminous mass to light ratios (M/L), of the given galaxy, is demonstrated. We demonstrate that the LCM is successful across a wide range of spiral galaxies for predicting the observed rotation curves. Through the generous support of the MIT Dr. Martin Luther King Jr. Fellowship program.

  11. Image Classification Using Biomimetic Pattern Recognition with Convolutional Neural Networks Features

    PubMed Central

    Huo, Guanying

    2017-01-01

    As a typical deep-learning model, Convolutional Neural Networks (CNNs) can be exploited to automatically extract features from images using the hierarchical structure inspired by mammalian visual system. For image classification tasks, traditional CNN models employ the softmax function for classification. However, owing to the limited capacity of the softmax function, there are some shortcomings of traditional CNN models in image classification. To deal with this problem, a new method combining Biomimetic Pattern Recognition (BPR) with CNNs is proposed for image classification. BPR performs class recognition by a union of geometrical cover sets in a high-dimensional feature space and therefore can overcome some disadvantages of traditional pattern recognition. The proposed method is evaluated on three famous image classification benchmarks, that is, MNIST, AR, and CIFAR-10. The classification accuracies of the proposed method for the three datasets are 99.01%, 98.40%, and 87.11%, respectively, which are much higher in comparison with the other four methods in most cases. PMID:28316614

  12. Toward content-based image retrieval with deep convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Sklan, Judah E. S.; Plassard, Andrew J.; Fabbri, Daniel; Landman, Bennett A.

    2015-03-01

    Content-based image retrieval (CBIR) offers the potential to identify similar case histories, understand rare disorders, and eventually, improve patient care. Recent advances in database capacity, algorithm efficiency, and deep Convolutional Neural Networks (dCNN), a machine learning technique, have enabled great CBIR success for general photographic images. Here, we investigate applying the leading ImageNet CBIR technique to clinically acquired medical images captured by the Vanderbilt Medical Center. Briefly, we (1) constructed a dCNN with four hidden layers, reducing dimensionality of an input scaled to 128x128 to an output encoded layer of 4x384, (2) trained the network using back-propagation 1 million random magnetic resonance (MR) and computed tomography (CT) images, (3) labeled an independent set of 2100 images, and (4) evaluated classifiers on the projection of the labeled images into manifold space. Quantitative results were disappointing (averaging a true positive rate of only 20%); however, the data suggest that improvements would be possible with more evenly distributed sampling across labels and potential re-grouping of label structures. This preliminary effort at automated classification of medical images with ImageNet is promising, but shows that more work is needed beyond direct adaptation of existing techniques.

  13. Single-Image Super Resolution for Multispectral Remote Sensing Data Using Convolutional Neural Networks

    NASA Astrophysics Data System (ADS)

    Liebel, L.; Körner, M.

    2016-06-01

    In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN), can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.

  14. Crosswell electromagnetic modeling from impulsive source: Optimization strategy for dispersion suppression in convolutional perfectly matched layer

    PubMed Central

    Fang, Sinan; Pan, Heping; Du, Ting; Konaté, Ahmed Amara; Deng, Chengxiang; Qin, Zhen; Guo, Bo; Peng, Ling; Ma, Huolin; Li, Gang; Zhou, Feng

    2016-01-01

    This study applied the finite-difference time-domain (FDTD) method to forward modeling of the low-frequency crosswell electromagnetic (EM) method. Specifically, we implemented impulse sources and convolutional perfectly matched layer (CPML). In the process to strengthen CPML, we observed that some dispersion was induced by the real stretch κ, together with an angular variation of the phase velocity of the transverse electric plane wave; the conclusion was that this dispersion was positively related to the real stretch and was little affected by grid interval. To suppress the dispersion in the CPML, we first derived the analytical solution for the radiation field of the magneto-dipole impulse source in the time domain. Then, a numerical simulation of CPML absorption with high-frequency pulses qualitatively amplified the dispersion laws through wave field snapshots. A numerical simulation using low-frequency pulses suggested an optimal parameter strategy for CPML from the established criteria. Based on its physical nature, the CPML method of simply warping space-time was predicted to be a promising approach to achieve ideal absorption, although it was still difficult to entirely remove the dispersion. PMID:27585538

  15. Crosswell electromagnetic modeling from impulsive source: Optimization strategy for dispersion suppression in convolutional perfectly matched layer

    NASA Astrophysics Data System (ADS)

    Fang, Sinan; Pan, Heping; Du, Ting; Konaté, Ahmed Amara; Deng, Chengxiang; Qin, Zhen; Guo, Bo; Peng, Ling; Ma, Huolin; Li, Gang; Zhou, Feng

    2016-09-01

    This study applied the finite-difference time-domain (FDTD) method to forward modeling of the low-frequency crosswell electromagnetic (EM) method. Specifically, we implemented impulse sources and convolutional perfectly matched layer (CPML). In the process to strengthen CPML, we observed that some dispersion was induced by the real stretch κ, together with an angular variation of the phase velocity of the transverse electric plane wave; the conclusion was that this dispersion was positively related to the real stretch and was little affected by grid interval. To suppress the dispersion in the CPML, we first derived the analytical solution for the radiation field of the magneto-dipole impulse source in the time domain. Then, a numerical simulation of CPML absorption with high-frequency pulses qualitatively amplified the dispersion laws through wave field snapshots. A numerical simulation using low-frequency pulses suggested an optimal parameter strategy for CPML from the established criteria. Based on its physical nature, the CPML method of simply warping space-time was predicted to be a promising approach to achieve ideal absorption, although it was still difficult to entirely remove the dispersion.

  16. Pixel-by-pixel absolute phase retrieval using three phase-shifted fringe patterns without markers

    NASA Astrophysics Data System (ADS)

    Jiang, Chufan; Li, Beiwen; Zhang, Song

    2017-04-01

    This paper presents a method that can recover absolute phase pixel by pixel without embedding markers on three phase-shifted fringe patterns, acquiring additional images, or introducing additional hardware component(s). The proposed three-dimensional (3D) absolute shape measurement technique includes the following major steps: (1) segment the measured object into different regions using rough priori knowledge of surface geometry; (2) artificially create phase maps at different z planes using geometric constraints of structured light system; (3) unwrap the phase pixel by pixel for each region by properly referring to the artificially created phase map; and (4) merge unwrapped phases from all regions into a complete absolute phase map for 3D reconstruction. We demonstrate that conventional three-step phase-shifted fringe patterns can be used to create absolute phase map pixel by pixel even for large depth range objects. We have successfully implemented our proposed computational framework to achieve absolute 3D shape measurement at 40 Hz.

  17. ACS/WFC Pixel Stability - Bringing the Pixels Back to the Science

    NASA Astrophysics Data System (ADS)

    Borncamp, David; Grogin, Norman A.; Bourque, Matthew; Ogaz, Sara

    2016-06-01

    Electrical current that has been trapped within the lattice structure of a Charged Coupled Device (CCD) can be present through multiple exposures, which will have an adverse effect on its science performance. The traditional way to correct for this extra charge is to take an image with the camera shutter closed periodically throughout the lifetime of the instrument. These images, generally referred to as dark images, allow for the characterization of the extra charge that is trapped within the CCD at the time of observation. This extra current can then be subtracted out of science images to correct for the extra charge that was there at this time. Pixels that have a charge above a certain threshold of current are marked as “hot” and flagged in the data quality array. However, these pixels may not be "bad" in the traditional sense that they cannot be reliably dark-subtracted. If these pixels are shown to be stable over an anneal period, the charge can be properly subtracted and the extra noise from this dark current can be taken into account. We present the results of a pixel history study that analyzes every pixel of ACS/WFC individually and allows pixels that were marked as bad to be brought back into the science image.

  18. Operational and convolution properties of two-dimensional Fourier transforms in polar coordinates.

    PubMed

    Baddour, Natalie

    2009-08-01

    For functions that are best described in terms of polar coordinates, the two-dimensional Fourier transform can be written in terms of polar coordinates as a combination of Hankel transforms and Fourier series-even if the function does not possess circular symmetry. However, to be as useful as its Cartesian counterpart, a polar version of the Fourier operational toolset is required for the standard operations of shift, multiplication, convolution, etc. This paper derives the requisite polar version of the standard Fourier operations. In particular, convolution-two dimensional, circular, and radial one dimensional-is discussed in detail. It is shown that standard multiplication/convolution rules do apply as long as the correct definition of convolution is applied.

  19. Convoluted nozzle design for the RL10 derivative 2B engine

    NASA Technical Reports Server (NTRS)

    1985-01-01

    The convoluted nozzle is a conventional refractory metal nozzle extension that is formed with a portion of the nozzle convoluted to show the extendible nozzle within the length of the rocket engine. The convoluted nozzle (CN) was deployed by a system of four gas driven actuators. For spacecraft applications the optimum CN may be self-deployed by internal pressure retained, during deployment, by a jettisonable exit closure. The convoluted nozzle is included in a study of extendible nozzles for the RL10 Engine Derivative 2B for use in an early orbit transfer vehicle (OTV). Four extendible nozzle configurations for the RL10-2B engine were evaluated. Three configurations of the two position nozzle were studied including a hydrogen dump cooled metal nozzle and radiation cooled nozzles of refractory metal and carbon/carbon composite construction respectively.

  20. Convolution of large 3D images on GPU and its decomposition

    NASA Astrophysics Data System (ADS)

    Karas, Pavel; Svoboda, David

    2011-12-01

    In this article, we propose a method for computing convolution of large 3D images. The convolution is performed in a frequency domain using a convolution theorem. The algorithm is accelerated on a graphic card by means of the CUDA parallel computing model. Convolution is decomposed in a frequency domain using the decimation in frequency algorithm. We pay attention to keeping our approach efficient in terms of both time and memory consumption and also in terms of memory transfers between CPU and GPU which have a significant inuence on overall computational time. We also study the implementation on multiple GPUs and compare the results between the multi-GPU and multi-CPU implementations.

  1. Directional Radiometry and Radiative Transfer: the Convoluted Path From Centuries-old Phenomenology to Physical Optics

    NASA Technical Reports Server (NTRS)

    Mishchenko, Michael I.

    2014-01-01

    This Essay traces the centuries-long history of the phenomenological disciplines of directional radiometry and radiative transfer in turbid media, discusses their fundamental weaknesses, and outlines the convoluted process of their conversion into legitimate branches of physical optics.

  2. Comparison of bladder segmentation using deep-learning convolutional neural network with and without level sets

    NASA Astrophysics Data System (ADS)

    Cha, Kenny H.; Hadjiiski, Lubomir M.; Samala, Ravi K.; Chan, Heang-Ping; Cohan, Richard H.; Caoili, Elaine M.

    2016-03-01

    We are developing a CAD system for detection of bladder cancer in CTU. In this study we investigated the application of deep-learning convolutional neural network (DL-CNN) to the segmentation of the bladder, which is a challenging problem because of the strong boundary between the non-contrast and contrast-filled regions in the bladder. We trained a DL-CNN to estimate the likelihood of a pixel being inside the bladder using neighborhood information. The segmented bladder was obtained from thresholding and hole-filling of the likelihood map. We compared the segmentation performance of the DL-CNN alone and with additional cascaded 3D and 2D level sets to refine the segmentation using 3D hand-segmented contours as reference standard. The segmentation accuracy was evaluated by five performance measures: average volume intersection %, average % volume error, average absolute % error, average minimum distance, and average Jaccard index for a data set of 81 training and 92 test cases. For the training set, DLCNN with level sets achieved performance measures of 87.2+/-6.1%, 6.0+/-9.1%, 8.7+/-6.1%, 3.0+/-1.2 mm, and 81.9+/-7.6%, respectively, while the DL-CNN alone obtained the values of 73.6+/-8.5%, 23.0+/-8.5%, 23.0+/-8.5%, 5.1+/-1.5 mm, and 71.5+/-9.2%, respectively. For the test set, the DL-CNN with level sets achieved performance measures of 81.9+/-12.1%, 10.2+/-16.2%, 14.0+/-13.0%, 3.6+/-2.0 mm, and 76.2+/-11.8%, respectively, while DL-CNN alone obtained 68.7+/-12.0%, 27.2+/-13.7%, 27.4+/-13.6%, 5.7+/-2.2 mm, and 66.2+/-11.8%, respectively. DL-CNN alone is effective in segmenting bladders but may not follow the details of the bladder wall. The combination of DL-CNN with level sets provides highly accurate bladder segmentation.

  3. Iterative algorithm for reconstructing rotationally asymmetric surface deviation with pixel-level spatial resolution

    NASA Astrophysics Data System (ADS)

    Quan, Haiyang; Wu, Fan; Hou, Xi

    2015-10-01

    New method for reconstructing rotationally asymmetric surface deviation with pixel-level spatial resolution is proposed. It is based on basic iterative scheme and accelerates the Gauss-Seidel method by introducing an acceleration parameter. This modified Successive Over-relaxation (SOR) is effective for solving the rotationally asymmetric components with pixel-level spatial resolution, without the usage of a fitting procedure. Compared to the Jacobi and Gauss-Seidel method, the modified SOR method with an optimal relaxation factor converges much faster and saves more computational costs and memory space without reducing accuracy. It has been proved by real experimental results.

  4. Forecasting natural aquifer discharge using a numerical model and convolution.

    PubMed

    Boggs, Kevin G; Johnson, Gary S; Van Kirk, Rob; Fairley, Jerry P

    2014-01-01

    If the nature of groundwater sources and sinks can be determined or predicted, the data can be used to forecast natural aquifer discharge. We present a procedure to forecast the relative contribution of individual aquifer sources and sinks to natural aquifer discharge. Using these individual aquifer recharge components, along with observed aquifer heads for each January, we generate a 1-year, monthly spring discharge forecast for the upcoming year with an existing numerical model and convolution. The results indicate that a forecast of natural aquifer discharge can be developed using only the dominant aquifer recharge sources combined with the effects of aquifer heads (initial conditions) at the time the forecast is generated. We also estimate how our forecast will perform in the future using a jackknife procedure, which indicates that the future performance of the forecast is good (Nash-Sutcliffe efficiency of 0.81). We develop a forecast and demonstrate important features of the procedure by presenting an application to the Eastern Snake Plain Aquifer in southern Idaho.

  5. Remote Sensing Image Fusion with Convolutional Neural Network

    NASA Astrophysics Data System (ADS)

    Zhong, Jinying; Yang, Bin; Huang, Guoyu; Zhong, Fei; Chen, Zhongze

    2016-12-01

    Remote sensing image fusion (RSIF) is referenced as restoring the high-resolution multispectral image from its corresponding low-resolution multispectral (LMS) image aided by the panchromatic (PAN) image. Most RSIF methods assume that the missing spatial details of the LMS image can be obtained from the high resolution PAN image. However, the distortions would be produced due to the much difference between the structural component of LMS image and that of PAN image. Actually, the LMS image can fully utilize its spatial details to improve the resolution. In this paper, a novel two-stage RSIF algorithm is proposed, which makes full use of both spatial details and spectral information of the LMS image itself. In the first stage, the convolutional neural network based super-resolution is used to increase the spatial resolution of the LMS image. In the second stage, Gram-Schmidt transform is employed to fuse the enhanced MS and the PAN images for further improvement the resolution of MS image. Since the spatial resolution enhancement in the first stage, the spectral distortions in the fused image would be decreased in evidence. Moreover, the spatial details can be preserved to construct the fused images. The QuickBird satellite source images are used to test the performances of the proposed method. The experimental results demonstrate that the proposed method can achieve better spatial details and spectral information simultaneously compared with other well-known methods.

  6. Delta function convolution method (DFCM) for fluorescence decay experiments

    NASA Astrophysics Data System (ADS)

    Zuker, M.; Szabo, A. G.; Bramall, L.; Krajcarski, D. T.; Selinger, B.

    1985-01-01

    A rigorous and convenient method of correcting for the wavelength variation of the instrument response function in time correlated photon counting fluorescence decay measurements is described. The method involves convolution of a modified functional form F˜s of the physical model with a reference data set measured under identical conditions as the measurement of the sample. The method is completely general in that an appropriate functional form may be found for any physical model of the excited state decay process. The modified function includes a term which is a Dirac delta function and terms which give the correct decay times and preexponential values in which one is interested. None of the data is altered in any way, permitting correct statistical analysis of the fitting. The method is readily adaptable to standard deconvolution procedures. The paper describes the theory and application of the method together with fluorescence decay results obtained from measurements of a number of different samples including diphenylhexatriene, myoglobin, hemoglobin, 4', 6-diamidine-2-phenylindole (DAPI), and lysine-trytophan-lysine.

  7. Visualizing Flow Over Parametric Surfaces Using Line Integral Convolution

    NASA Technical Reports Server (NTRS)

    Forssell, Lisa; Lasinski, T. A. (Technical Monitor)

    1994-01-01

    Line Integral Convolution (LIC) is a powerful technique for imaging and animating vector fields. We extend the LIC paradigm in three ways: (1) The existing technique is limited to vector fields over a regular Cartesian grid. We extend it to vector fields over parametric surfaces, such as those found in curvilinear grids, used in computational fluid dynamics simulations; (2) Periodic motion filters can be used to animate the flow visualization. When the flow lies on a parametric surface, however, the motion appears misleading. We explain why this problem arises and show how to adjust the LIC algorithm to handle it; (3) We introduce a technique to visualize vector magnitudes as well as vector direction. Cabral and Leedom have suggested a method for variable-speed animation, which is based on varying the frequency of the filter function. We develop a different technique based on kernel phase shifts which we have found to show substantially better results. Our implementation of these algorithms utilizes texture-mapping hardware to run in real time, which allows them to be included in interactive applications.

  8. Interleaved convolutional coding for the turbulent atmospheric optical communication channel

    NASA Astrophysics Data System (ADS)

    Davidson, Frederic M.; Koh, Yutai T.

    1988-09-01

    The coding gain of a constraint-length-three, rate one-half convolutional code over a long clear-air atmospheric direct-detection optical communication channel using binary pulse-position modulation signaling was directly measured as a function of interleaving delay for both hard- and soft-decision Viterbi decoding. Maximum coding gains theoretically possible for this code with perfect interleaving and physically unrealizable perfect-measurement decoding were about 7 dB under conditions of weak clear-air turbulence, and 11 dB at moderate turbulence levels. The time scale of the fading (memory) of the channel was directly measured to be tens to hundreds of milliseconds, depending on turbulence levels. Interleaving delays of 5 ms between transmission of the first and second channel bits output by the encoder yield coding gains within 1.5 dB of theoretical limits with soft-decision Viterbi decoding. Coding gains of 4-5 dB were observed with only 100 microseconds of interleaving delay. Soft-decision Viterbi decoding always yielded 1-2 dB more coding gain than hard-decision Viterbi decoding.

  9. Multi-resolution Convolution Methodology for ICP Waveform Morphology Analysis.

    PubMed

    Shaw, Martin; Piper, Ian; Hawthorne, Christopher

    2016-01-01

    Intracranial pressure (ICP) monitoring is a key clinical tool in the assessment and treatment of patients in neurointensive care. ICP morphology analysis can be useful in the classification of waveform features.A methodology for the decomposition of an ICP signal into clinically relevant dimensions has been devised that allows the identification of important ICP waveform types. It has three main components. First, multi-resolution convolution analysis is used for the main signal decomposition. Then, an impulse function is created, with multiple parameters, that can represent any form in the signal under analysis. Finally, a simple, localised optimisation technique is used to find morphologies of interest in the decomposed data.A pilot application of this methodology using a simple signal has been performed. This has shown that the technique works with performance receiver operator characteristic area under the curve values for each of the waveform types: plateau wave, B wave and high and low compliance states of 0.936, 0.694, 0.676 and 0.698, respectively.This is a novel technique that showed some promise during the pilot analysis. However, it requires further optimisation to become a usable clinical tool for the automated analysis of ICP signals.

  10. Toward an optimal convolutional neural network for traffic sign recognition

    NASA Astrophysics Data System (ADS)

    Habibi Aghdam, Hamed; Jahani Heravi, Elnaz; Puig, Domenec

    2015-12-01

    Convolutional Neural Networks (CNN) beat the human performance on German Traffic Sign Benchmark competition. Both the winner and the runner-up teams trained CNNs to recognize 43 traffic signs. However, both networks are not computationally efficient since they have many free parameters and they use highly computational activation functions. In this paper, we propose a new architecture that reduces the number of the parameters 27% and 22% compared with the two networks. Furthermore, our network uses Leaky Rectified Linear Units (ReLU) as the activation function that only needs a few operations to produce the result. Specifically, compared with the hyperbolic tangent and rectified sigmoid activation functions utilized in the two networks, Leaky ReLU needs only one multiplication operation which makes it computationally much more efficient than the two other functions. Our experiments on the Gertman Traffic Sign Benchmark dataset shows 0:6% improvement on the best reported classification accuracy while it reduces the overall number of parameters 85% compared with the winner network in the competition.

  11. Study of multispectral convolution scatter correction in high resolution PET

    SciTech Connect

    Yao, R.; Lecomte, R.; Bentourkia, M.

    1996-12-31

    PET images acquired with a high resolution scanner based on arrays of small discrete detectors are obtained at the cost of low sensitivity and increased detector scatter. It has been postulated that these limitations can be overcome by using enlarged discrimination windows to include more low energy events and by developing more efficient energy-dependent methods to correct for scatter. In this work, we investigate one such method based on the frame-by-frame scatter correction of multispectral data. Images acquired in the conventional, broad and multispectral window modes were processed by the stationary and nonstationary consecutive convolution scatter correction methods. Broad and multispectral window acquisition with a low energy threshold of 129 keV improved system sensitivity by up to 75% relative to conventional window with a {approximately}350 keV threshold. The degradation of image quality due to the added scatter events can almost be fully recovered by the subtraction-restoration scatter correction. The multispectral method was found to be more sensitive to the nonstationarity of scatter and its performance was not as good as that of the broad window. It is concluded that new scatter degradation models and correction methods need to be established to fully take advantage of multispectral data.

  12. Cell volume regulation in the proximal convoluted tubule.

    PubMed

    Gagnon, J; Ouimet, D; Nguyen, H; Laprade, R; Le Grimellec, C; Carrière, S; Cardinal, J

    1982-10-01

    To evaluate the effect of hyper- and hypotonicity on proximal convoluted tubule (PCT) cell volume, nonperfused PCT were studied in vitro with hypertonic solutions containing sodium chloride, urea, or mannitol (450 mosmol/kg H2O) and with hypotonic low sodium chloride solutions (160 mosmol/kg H2O). When the tubules were subjected to hypertonic peritubular solutions containing NaCl, cell volume immediately decreased by 15.5% and remained constant throughout the experimental period (60 min). With mannitol, the initial decrease was identical to that with NaCl (17.7%), but the PCT volume increased slightly during the experimental period. With urea, the decrease in cell volume was smaller (7%) and transient. In hypotonicity, the PCT swelled rapidly, but this swelling was followed by a rapid regulatory phase in which PCT volume nearly returned to control values after less than 10 min. With a potassium-free peritubular medium or 10(-3) M ouabain, the regulatory phase of hypotonicity completely disappeared, whereas the cells did not maintain their reduced volume in NaCl-induced hypertonicity. These results suggest that Na-K-ATPase plays an important role in the maintenance of a reduced cellular volume in hypertonicity and in the regulatory phase of hypotonicity, probably by an active extrusion of sodium and water from the cell.

  13. Convolutional networks for fast, energy-efficient neuromorphic computing

    PubMed Central

    Esser, Steven K.; Merolla, Paul A.; Arthur, John V.; Cassidy, Andrew S.; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J.; McKinstry, Jeffrey L.; Melano, Timothy; Barch, Davis R.; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D.; Modha, Dharmendra S.

    2016-01-01

    Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware’s underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer. PMID:27651489

  14. Method for Veterbi decoding of large constraint length convolutional codes

    NASA Technical Reports Server (NTRS)

    Hsu, In-Shek (Inventor); Truong, Trieu-Kie (Inventor); Reed, Irving S. (Inventor); Jing, Sun (Inventor)

    1988-01-01

    A new method of Viterbi decoding of convolutional codes lends itself to a pipline VLSI architecture using a single sequential processor to compute the path metrics in the Viterbi trellis. An array method is used to store the path information for NK intervals where N is a number, and K is constraint length. The selected path at the end of each NK interval is then selected from the last entry in the array. A trace-back method is used for returning to the beginning of the selected path back, i.e., to the first time unit of the interval NK to read out the stored branch metrics of the selected path which correspond to the message bits. The decoding decision made in this way is no longer maximum likelihood, but can be almost as good, provided that constraint length K in not too small. The advantage is that for a long message, it is not necessary to provide a large memory to store the trellis derived information until the end of the message to select the path that is to be decoded; the selection is made at the end of every NK time unit, thus decoding a long message in successive blocks.

  15. Fully automated quantitative cephalometry using convolutional neural networks.

    PubMed

    Arık, Sercan Ö; Ibragimov, Bulat; Xing, Lei

    2017-01-01

    Quantitative cephalometry plays an essential role in clinical diagnosis, treatment, and surgery. Development of fully automated techniques for these procedures is important to enable consistently accurate computerized analyses. We study the application of deep convolutional neural networks (CNNs) for fully automated quantitative cephalometry for the first time. The proposed framework utilizes CNNs for detection of landmarks that describe the anatomy of the depicted patient and yield quantitative estimation of pathologies in the jaws and skull base regions. We use a publicly available cephalometric x-ray image dataset to train CNNs for recognition of landmark appearance patterns. CNNs are trained to output probabilistic estimations of different landmark locations, which are combined using a shape-based model. We evaluate the overall framework on the test set and compare with other proposed techniques. We use the estimated landmark locations to assess anatomically relevant measurements and classify them into different anatomical types. Overall, our results demonstrate high anatomical landmark detection accuracy ([Formula: see text] to 2% higher success detection rate for a 2-mm range compared with the top benchmarks in the literature) and high anatomical type classification accuracy ([Formula: see text] average classification accuracy for test set). We demonstrate that CNNs, which merely input raw image patches, are promising for accurate quantitative cephalometry.

  16. Deep convolutional neural networks for classifying GPR B-scans

    NASA Astrophysics Data System (ADS)

    Besaw, Lance E.; Stimac, Philip J.

    2015-05-01

    Symmetric and asymmetric buried explosive hazards (BEHs) present real, persistent, deadly threats on the modern battlefield. Current approaches to mitigate these threats rely on highly trained operatives to reliably detect BEHs with reasonable false alarm rates using handheld Ground Penetrating Radar (GPR) and metal detectors. As computers become smaller, faster and more efficient, there exists greater potential for automated threat detection based on state-of-the-art machine learning approaches, reducing the burden on the field operatives. Recent advancements in machine learning, specifically deep learning artificial neural networks, have led to significantly improved performance in pattern recognition tasks, such as object classification in digital images. Deep convolutional neural networks (CNNs) are used in this work to extract meaningful signatures from 2-dimensional (2-D) GPR B-scans and classify threats. The CNNs skip the traditional "feature engineering" step often associated with machine learning, and instead learn the feature representations directly from the 2-D data. A multi-antennae, handheld GPR with centimeter-accurate positioning data was used to collect shallow subsurface data over prepared lanes containing a wide range of BEHs. Several heuristics were used to prevent over-training, including cross validation, network weight regularization, and "dropout." Our results show that CNNs can extract meaningful features and accurately classify complex signatures contained in GPR B-scans, complementing existing GPR feature extraction and classification techniques.

  17. HEp-2 Cell Image Classification with Deep Convolutional Neural Networks.

    PubMed

    Gao, Zhimin; Wang, Lei; Zhou, Luping; Zhang, Jianjia

    2016-02-08

    Efficient Human Epithelial-2 (HEp-2) cell image classification can facilitate the diagnosis of many autoimmune diseases. This paper proposes an automatic framework for this classification task, by utilizing the deep convolutional neural networks (CNNs) which have recently attracted intensive attention in visual recognition. In addition to describing the proposed classification framework, this paper elaborates several interesting observations and findings obtained by our investigation. They include the important factors that impact network design and training, the role of rotation-based data augmentation for cell images, the effectiveness of cell image masks for classification, and the adaptability of the CNN-based classification system across different datasets. Extensive experimental study is conducted to verify the above findings and compares the proposed framework with the well-established image classification models in the literature. The results on benchmark datasets demonstrate that i) the proposed framework can effectively outperform existing models by properly applying data augmentation; ii) our CNN-based framework has excellent adaptability across different datasets, which is highly desirable for cell image classification under varying laboratory settings. Our system is ranked high in the cell image classification competition hosted by ICPR 2014.

  18. A quantum algorithm for Viterbi decoding of classical convolutional codes

    NASA Astrophysics Data System (ADS)

    Grice, Jon R.; Meyer, David A.

    2015-07-01

    We present a quantum Viterbi algorithm (QVA) with better than classical performance under certain conditions. In this paper, the proposed algorithm is applied to decoding classical convolutional codes, for instance, large constraint length and short decode frames . Other applications of the classical Viterbi algorithm where is large (e.g., speech processing) could experience significant speedup with the QVA. The QVA exploits the fact that the decoding trellis is similar to the butterfly diagram of the fast Fourier transform, with its corresponding fast quantum algorithm. The tensor-product structure of the butterfly diagram corresponds to a quantum superposition that we show can be efficiently prepared. The quantum speedup is possible because the performance of the QVA depends on the fanout (number of possible transitions from any given state in the hidden Markov model) which is in general much less than . The QVA constructs a superposition of states which correspond to all legal paths through the decoding lattice, with phase as a function of the probability of the path being taken given received data. A specialized amplitude amplification procedure is applied one or more times to recover a superposition where the most probable path has a high probability of being measured.

  19. Designing the optimal convolution kernel for modeling the motion blur

    NASA Astrophysics Data System (ADS)

    Jelinek, Jan

    2011-06-01

    Motion blur acts on an image like a two dimensional low pass filter, whose spatial frequency characteristic depends both on the trajectory of the relative motion between the scene and the camera and on the velocity vector variation along it. When motion during exposure is permitted, the conventional, static notions of both the image exposure and the scene-toimage mapping become unsuitable and must be revised to accommodate the image formation dynamics. This paper develops an exact image formation model for arbitrary object-camera relative motion with arbitrary velocity profiles. Moreover, for any motion the camera may operate in either continuous or flutter shutter exposure mode. Its result is a convolution kernel, which is optimally designed for both the given motion and sensor array geometry, and hence permits the most accurate computational undoing of the blurring effects for the given camera required in forensic and high security applications. The theory has been implemented and a few examples are shown in the paper.

  20. A deep convolutional neural network for recognizing foods

    NASA Astrophysics Data System (ADS)

    Jahani Heravi, Elnaz; Habibi Aghdam, Hamed; Puig, Domenec

    2015-12-01

    Controlling the food intake is an efficient way that each person can undertake to tackle the obesity problem in countries worldwide. This is achievable by developing a smartphone application that is able to recognize foods and compute their calories. State-of-art methods are chiefly based on hand-crafted feature extraction methods such as HOG and Gabor. Recent advances in large-scale object recognition datasets such as ImageNet have revealed that deep Convolutional Neural Networks (CNN) possess more representation power than the hand-crafted features. The main challenge with CNNs is to find the appropriate architecture for each problem. In this paper, we propose a deep CNN which consists of 769; 988 parameters. Our experiments show that the proposed CNN outperforms the state-of-art methods and improves the best result of traditional methods 17%. Moreover, using an ensemble of two CNNs that have been trained two different times, we are able to improve the classification performance 21:5%.

  1. Convolutional networks for fast, energy-efficient neuromorphic computing.

    PubMed

    Esser, Steven K; Merolla, Paul A; Arthur, John V; Cassidy, Andrew S; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J; McKinstry, Jeffrey L; Melano, Timothy; Barch, Davis R; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D; Modha, Dharmendra S

    2016-10-11

    Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware's underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer.

  2. MTF evaluation of white pixel sensors

    NASA Astrophysics Data System (ADS)

    Lindner, Albrecht; Atanassov, Kalin; Luo, Jiafu; Goma, Sergio

    2015-01-01

    We present a methodology to compare image sensors with traditional Bayer RGB layouts to sensors with alternative layouts containing white pixels. We focused on the sensors' resolving powers, which we measured in the form of a modulation transfer function for variations in both luma and chroma channels. We present the design of the test chart, the acquisition of images, the image analysis, and an interpretation of results. We demonstrate the approach at the example of two sensors that only differ in their color filter arrays. We confirmed that the sensor with white pixels and the corresponding demosaicing result in a higher resolving power in the luma channel, but a lower resolving power in the chroma channels when compared to the traditional Bayer sensor.

  3. Advanced monolithic pixel sensors using SOI technology

    NASA Astrophysics Data System (ADS)

    Miyoshi, Toshinobu; Arai, Yasuo; Asano, Mari; Fujita, Yowichi; Hamasaki, Ryutaro; Hara, Kazuhiko; Honda, Shunsuke; Ikegami, Yoichi; Kurachi, Ikuo; Mitsui, Shingo; Nishimura, Ryutaro; Tauchi, Kazuya; Tobita, Naoshi; Tsuboyama, Toru; Yamada, Miho

    2016-07-01

    We are developing advanced pixel sensors using silicon-on-insulator (SOI) technology. A SOI wafer is used; top silicon is used for electric circuit and bottom silicon is used as a sensor. Target applications are high-energy physics, X-ray astronomy, material science, non-destructive inspection, medical application and so on. We have developed two integration-type pixel sensors, FPIXb and INTPIX7. These sensors were processed on single SOI wafers with various substrates in n- or p-type and double SOI wafers. The development status of double SOI sensors and some up-to-date test results of n-type and p-type SOI sensors are shown.

  4. A convolution model for computing the far-field directivity of a parametric loudspeaker array.

    PubMed

    Shi, Chuang; Kajikawa, Yoshinobu

    2015-02-01

    This paper describes a method to compute the far-field directivity of a parametric loudspeaker array (PLA), whereby the steerable parametric loudspeaker can be implemented when phased array techniques are applied. The convolution of the product directivity and the Westervelt's directivity is suggested, substituting for the past practice of using the product directivity only. Computed directivity of a PLA using the proposed convolution model achieves significant improvement in agreement to measured directivity at a negligible computational cost.

  5. Error Analysis of Padding Schemes for DFT’s of Convolutions and Derivatives

    DTIC Science & Technology

    2012-01-31

    Geodaetica, 18,263-279. Oppenheim AV, Schafer RW (1975) Digital Signal Processing . Prentice-Hall, Inc., Englewood Cliffs, New Jersey. Schwarz KP... Oppenheim and Schäfer (1975). Many numerical tests have been done to show that this so-called zero padding improves the computation of Stokes...and (19) relate linear convolutions to corresponding cyclic convolutions. Equation (19) is the justification, originating in Oppenheim and Schäfer

  6. The Silicon Pixel Detector for ALICE Experiment

    SciTech Connect

    Fabris, D.; Bombonati, C.; Dima, R.; Lunardon, M.; Moretto, S.; Pepato, A.; Bohus, L. Sajo; Scarlassara, F.; Segato, G.; Shen, D.; Turrisi, R.; Viesti, G.; Anelli, G.; Boccardi, A.; Burns, M.; Campbell, M.; Ceresa, S.; Conrad, J.; Kluge, A.; Kral, M.

    2007-10-26

    The Inner Tracking System (ITS) of the ALICE experiment is made of position sensitive detectors which have to operate in a region where the track density may be as high as 50 tracks/cm{sup 2}. To handle such densities detectors with high precision and granularity are mandatory. The Silicon Pixel Detector (SPD), the innermost part of the ITS, has been designed to provide tracking information close to primary interaction point. The assembly of the entire SPD has been completed.

  7. The Belle II DEPFET pixel detector

    NASA Astrophysics Data System (ADS)

    Moser, Hans-Günther

    2016-09-01

    The Belle II experiment at KEK (Tsukuba, Japan) will explore heavy flavour physics (B, charm and tau) at the starting of 2018 with unprecedented precision. Charged particles are tracked by a two-layer DEPFET pixel device (PXD), a four-layer silicon strip detector (SVD) and the central drift chamber (CDC). The PXD will consist of two layers at radii of 14 mm and 22 mm with 8 and 12 ladders, respectively. The pixel sizes will vary, between 50 μm×(55-60) μm in the first layer and between 50 μm×(70-85) μm in the second layer, to optimize the charge sharing efficiency. These innermost layers have to cope with high background occupancy, high radiation and must have minimal material to reduce multiple scattering. These challenges are met using the DEPFET technology. Each pixel is a FET integrated on a fully depleted silicon bulk. The signal charge collected in the 'internal gate' modulates the FET current resulting in a first stage amplification and therefore very low noise. This allows very thin sensors (75 μm) reducing the overall material budget of the detector (0.21% X0). Four fold multiplexing of the column parallel readout allows read out a full frame of the pixel matrix in only 20 μs while keeping the power consumption low enough for air cooling. Only the active electronics outside the detector acceptance has to be cooled actively with a two phase CO2 system. Furthermore the DEPFET technology offers the unique feature of an electronic shutter which allows the detector to operate efficiently in the continuous injection mode of superKEKB.

  8. Local Histograms for Per-Pixel Classification

    DTIC Science & Technology

    2012-03-01

    Domain-Knowledge-Inspired Math - ematical Framework for the Description and Classification of H&E Stained Histopathology Images,” Proceedings of SPIE, 8138... computed over discrete images as the number of pixels in a particular bin. In order to obtain a “density” independent of the bin-width, one can divide the...Notes in Computer Science , 5112: 688–696 (2008). [12] van Ginneken, Bram and Bart M. ter Haar Romeny. “Applications of Locally Orderless Images

  9. Photovoltaic Retinal Prosthesis with High Pixel Density

    PubMed Central

    Mathieson, Keith; Loudin, James; Goetz, Georges; Huie, Philip; Wang, Lele; Kamins, Theodore I.; Galambos, Ludwig; Smith, Richard; Harris, James S.; Sher, Alexander; Palanker, Daniel

    2012-01-01

    Retinal degenerative diseases lead to blindness due to loss of the “image capturing” photoreceptors, while neurons in the “image processing” inner retinal layers are relatively well preserved. Electronic retinal prostheses seek to restore sight by electrically stimulating surviving neurons. Most implants are powered through inductive coils, requiring complex surgical methods to implant the coil-decoder-cable-array systems, which deliver energy to stimulating electrodes via intraocular cables. We present a photovoltaic subretinal prosthesis, in which silicon photodiodes in each pixel receive power and data directly through pulsed near-infrared illumination and electrically stimulate neurons. Stimulation was produced in normal and degenerate rat retinas, with pulse durations from 0.5 to 4 ms, and threshold peak irradiances from 0.2 to 10 mW/mm2, two orders of magnitude below the ocular safety limit. Neural responses were elicited by illuminating a single 70 μm bipolar pixel, demonstrating the possibility of a fully-integrated photovoltaic retinal prosthesis with high pixel density. PMID:23049619

  10. Soil moisture variability within remote sensing pixels

    SciTech Connect

    Charpentier, M.A.; Groffman, P.M. )

    1992-11-30

    This work is part of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), an international land-surface-atmosphere experiment aimed at improving the way climate models represent energy, water, heat, and carbon exchanges, and improving the utilization of satellite based remote sensing to monitor such parameters. This paper addresses the question of soil moisture variation within the field of view of a remote sensing pixel. Remote sensing is the only practical way to sense soil moisture over large areas, but it is known that there can be large variations of soil moisture within the field of view of a pixel. The difficulty with this is that many processes, such as gas exchange between surface and atmosphere can vary dramatically with moisture content, and a small wet spot, for example, can have a dramatic impact on such processes, and thereby bias remote sensing data results. Here the authors looked at the impact of surface topography on the level of soil moisture, and the interaction of both on the variability of soil moisture sensed by a push broom microwave radiometer (PBMR). In addition the authors looked at the question of whether variations of soil moisture within pixel size areas could be used to assign errors to PBMR generated soil moisture data.

  11. Photovoltaic retinal prosthesis with high pixel density

    NASA Astrophysics Data System (ADS)

    Mathieson, Keith; Loudin, James; Goetz, Georges; Huie, Philip; Wang, Lele; Kamins, Theodore I.; Galambos, Ludwig; Smith, Richard; Harris, James S.; Sher, Alexander; Palanker, Daniel

    2012-06-01

    Retinal degenerative diseases lead to blindness due to loss of the `image capturing' photoreceptors, while neurons in the `image-processing' inner retinal layers are relatively well preserved. Electronic retinal prostheses seek to restore sight by electrically stimulating the surviving neurons. Most implants are powered through inductive coils, requiring complex surgical methods to implant the coil-decoder-cable-array systems that deliver energy to stimulating electrodes via intraocular cables. We present a photovoltaic subretinal prosthesis, in which silicon photodiodes in each pixel receive power and data directly through pulsed near-infrared illumination and electrically stimulate neurons. Stimulation is produced in normal and degenerate rat retinas, with pulse durations of 0.5-4 ms, and threshold peak irradiances of 0.2-10 mW mm-2, two orders of magnitude below the ocular safety limit. Neural responses were elicited by illuminating a single 70 µm bipolar pixel, demonstrating the possibility of a fully integrated photovoltaic retinal prosthesis with high pixel density.

  12. Status of the CMS pixel project

    SciTech Connect

    Uplegger, Lorenzo; /Fermilab

    2008-01-01

    The Compact Muon Solenoid Experiment (CMS) will start taking data at the Large Hadron Collider (LHC) in 2008. The closest detector to the interaction point is the silicon pixel detector which is the heart of the tracking system. It consists of three barrel layers and two pixel disks on each side of the interaction point for a total of 66 million channels. Its proximity to the interaction point means there will be very large particle fluences and therefore a radiation-tolerant design is necessary. The pixel detector will be crucial to achieve a good vertex resolution and will play a key role in pattern recognition and track reconstruction. The results from test beam runs prove that the expected performances can be achieved. The detector is currently being assembled and will be ready for insertion into CMS in early 2008. During the assembly phase, a thorough electronic test is being done to check the functionality of each channel to guarantee the performance required to achieve the physics goals. This report will present the final detector design, the status of the production as well as results from test beam runs to validate the expected performance.

  13. Pixel electronics for the ATLAS experiment

    NASA Astrophysics Data System (ADS)

    Fischer, P.

    2001-06-01

    The ATLAS experiment at LHC will use 3 barrel layers and 2×5 disks of silicon pixel detectors as the innermost elements of the semiconductor tracker. The basic building blocks are pixel modules with an active area of 16.4 mm×60.8 mm which include an n + on n-type silicon sensor and 16 VLSI front-end (FE) chips. Every FE chip contains a low power, high speed charge sensitive preamplifier, a fast discriminator, and a readout system which operates at the 40 MHz rate of LHC. The addresses of hit pixels (as well as a low resolution pulse height information) are stored on the FE chips until arrival of a level 1 trigger signal. Hits are then transferred to a module controller chip (MCC) which collects the data of all 16 FE chips, builds complete events and sends the data through two optical links to the data acquisition system. The MCC receives clock and data through an additional optical link and provides timing and configuration information for the FE chips. Two additional chips are used to amplify and decode the pin diode signal and to drive the VCSEL laser diodes of the optical links.

  14. Minimal-memory realization of pearl-necklace encoders of general quantum convolutional codes

    SciTech Connect

    Houshmand, Monireh; Hosseini-Khayat, Saied

    2011-02-15

    Quantum convolutional codes, like their classical counterparts, promise to offer higher error correction performance than block codes of equivalent encoding complexity, and are expected to find important applications in reliable quantum communication where a continuous stream of qubits is transmitted. Grassl and Roetteler devised an algorithm to encode a quantum convolutional code with a ''pearl-necklace'' encoder. Despite their algorithm's theoretical significance as a neat way of representing quantum convolutional codes, it is not well suited to practical realization. In fact, there is no straightforward way to implement any given pearl-necklace structure. This paper closes the gap between theoretical representation and practical implementation. In our previous work, we presented an efficient algorithm to find a minimal-memory realization of a pearl-necklace encoder for Calderbank-Shor-Steane (CSS) convolutional codes. This work is an extension of our previous work and presents an algorithm for turning a pearl-necklace encoder for a general (non-CSS) quantum convolutional code into a realizable quantum convolutional encoder. We show that a minimal-memory realization depends on the commutativity relations between the gate strings in the pearl-necklace encoder. We find a realization by means of a weighted graph which details the noncommutative paths through the pearl necklace. The weight of the longest path in this graph is equal to the minimal amount of memory needed to implement the encoder. The algorithm has a polynomial-time complexity in the number of gate strings in the pearl-necklace encoder.

  15. CMOS Active Pixel Sensor Technology and Reliability Characterization Methodology

    NASA Technical Reports Server (NTRS)

    Chen, Yuan; Guertin, Steven M.; Pain, Bedabrata; Kayaii, Sammy

    2006-01-01

    This paper describes the technology, design features and reliability characterization methodology of a CMOS Active Pixel Sensor. Both overall chip reliability and pixel reliability are projected for the imagers.

  16. A PFM based digital pixel with off-pixel residue measurement for 15μm pitch MWIR FPAs

    NASA Astrophysics Data System (ADS)

    Abbasi, Shahbaz; Shafique, Atia; Galioglu, Arman; Ceylan, Omer; Yazici, Melik; Gurbuz, Yasar

    2016-05-01

    Digital pixels based on pulse frequency modulation (PFM) employ counting techniques to achieve very high charge handling capability compared to their analog counterparts. Moreover, extended counting methods making use of leftover charge (residue) on the integration capacitor help improve the noise performance of these pixels. However, medium wave infrared (MWIR) focal plane arrays (FPAs) having smaller pixel pitch are constrained in terms of pixel area which makes it difficult to add extended counting circuitry to the pixel. Thus, this paper investigates the performance of digital pixels employing off-pixel residue measurement. A circuit prototype of such a pixel has been designed for 15μm pixel pitch and fabricated in 90nm CMOS. The prototype is composed of a pixel front-end based on a PFM loop. The frontend is a modified version of conventional design providing a means for buffering the signal that needs to be converted to a digital value by an off-pixel ADC. The pixel has an integration phase and a residue measurement phase. Measured integration performance of the pixel has been reported in this paper for various detector currents and integration times.

  17. Characterization of a 2-mm thick, 16x16 Cadmium-Zinc-Telluride Pixel Array

    NASA Technical Reports Server (NTRS)

    Gaskin, Jessica; Richardson, Georgia; Mitchell, Shannon; Ramsey, Brian; Seller, Paul; Sharma, Dharma

    2003-01-01

    The detector under study is a 2-mm-thick, 16x16 Cadmium-Zinc-Telluride pixel array with a pixel pitch of 300 microns and inter-pixel gap of 50 microns. This detector is a precursor to that which will be used at the focal plane of the High Energy Replicated Optics (HERO) telescope currently being developed at Marshall Space Flight Center. With a telescope focal length of 6 meters, the detector needs to have a spatial resolution of around 200 microns in order to take full advantage of the HERO angular resolution. We discuss to what degree charge sharing will degrade energy resolution but will improve our spatial resolution through position interpolation. In addition, we discuss electric field modeling for this specific detector geometry and the role this mapping will play in terms of charge sharing and charge loss in the detector.

  18. A self-adaptive image encryption scheme with half-pixel interchange permutation operation

    NASA Astrophysics Data System (ADS)

    Ye, Ruisong; Liu, Li; Liao, Minyu; Li, Yafang; Liao, Zikang

    2017-01-01

    A plain-image dependent image encryption scheme with half-pixel-level swapping permutation strategy is proposed. In the new permutation operation, a pixel-swapping operation between four higher bit-planes and four lower bit-planes is employed to replace the traditional confusion operation, which not only improves the conventional permutation efficiency within the plain-image, but also changes all the pixel gray values. The control parameters of generalized Arnold map applied for the permutation operation are related to the plain-image content and consequently can resist chosen-plaintext and known-plaintext attacks effectively. To enhance the security of the proposed image encryption, one multimodal skew tent map is applied to generate pseudo-random gray value sequence for diffusion operation. Simulations have been carried out thoroughly to demonstrate that the proposed image encryption scheme is highly secure thanks to its large key space and efficient permutation-diffusion operations.

  19. Development of Kilo-Pixel Arrays of Transition-Edge Sensors for X-Ray Spectroscopy

    NASA Technical Reports Server (NTRS)

    Adams, J. S.; Bandler, S. R.; Busch, S. E.; Chervenak, J. A.; Chiao, M. P.; Eckart, M. E.; Ewin, A. J.; Finkbeiner, F. M.; Kelley, R. L.; Kelly, D. P.; Kilbourne, C. A.; Leutenegger, M. A.; Porst, J.-P.; Porter, F. S.; Ray, C. A.; Sadleir, J. E.; Smith, S. J.; Wassell, E. J.; Doriese, W. B.; Fowler, J. W.; Hilton, G. C.; Irwin, K. D.; Reintsema, C. D.; Smith, D. R.; Swetz, D. S.

    2012-01-01

    We are developing kilo-pixel arrays of transition-edge sensor (TES) microcalorimeters for future X-ray astronomy observatories or for use in laboratory astrophysics applications. For example, Athena/XMS (currently under study by the european space agency) would require a close-packed 32x32 pixel array on a 250-micron pitch with < 3.0 eV full-width-half-maximum energy resolution at 6 keV and at count-rates of up to 50 counts/pixel/second. We present characterization of 32x32 arrays. These detectors will be readout using state of the art SQUID based time-domain multiplexing (TDM). We will also present the latest results in integrating these detectors and the TDM readout technology into a 16 row x N column field-able instrument.

  20. Methods of editing cloud and atmospheric layer affected pixels from satellite data

    NASA Technical Reports Server (NTRS)

    Nixon, P. R. (Principal Investigator); Wiegand, C. L.; Richardson, A. J.; Johnson, M. P.

    1981-01-01

    Plotted transects made from south Texas daytime HCMM data show the effect of subvisible cirrus (SCI) clouds in the emissive (IR) band but the effect is unnoticable in the reflective (VIS) band. The depression of satellite indicated temperatures ws greatest in the center of SCi streamers and tapered off at the edges. Pixels of uncontaminated land and water features in the HCMM test area shared identical VIS and IR digital count combinations with other pixels representing similar features. A minimum of 0.015 percent repeats of identical VIS-IR combinations are characteristic of land and water features in a scene of 30 percent cloud cover. This increases to 0.021 percent of more when the scene is clear. Pixels having shared VIS-IR combinations less than these amounts are considered to be cloud contaminated in the cluster screening method. About twenty percent of SCi was machine indistinguishable from land features in two dimensional spectral space (VIS vs IR).

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

  2. Text-Attentional Convolutional Neural Network for Scene Text Detection.

    PubMed

    He, Tong; Huang, Weilin; Qiao, Yu; Yao, Jian

    2016-06-01

    Recent deep learning models have demonstrated strong capabilities for classifying text and non-text components in natural images. They extract a high-level feature globally computed from a whole image component (patch), where the cluttered background information may dominate true text features in the deep representation. This leads to less discriminative power and poorer robustness. In this paper, we present a new system for scene text detection by proposing a novel text-attentional convolutional neural network (Text-CNN) that particularly focuses on extracting text-related regions and features from the image components. We develop a new learning mechanism to train the Text-CNN with multi-level and rich supervised information, including text region mask, character label, and binary text/non-text information. The rich supervision information enables the Text-CNN with a strong capability for discriminating ambiguous texts, and also increases its robustness against complicated background components. The training process is formulated as a multi-task learning problem, where low-level supervised information greatly facilitates the main task of text/non-text classification. In addition, a powerful low-level detector called contrast-enhancement maximally stable extremal regions (MSERs) is developed, which extends the widely used MSERs by enhancing intensity contrast between text patterns and background. This allows it to detect highly challenging text patterns, resulting in a higher recall. Our approach achieved promising results on the ICDAR 2013 data set, with an F-measure of 0.82, substantially improving the state-of-the-art results.

  3. Text-Attentional Convolutional Neural Networks for Scene Text Detection.

    PubMed

    He, Tong; Huang, Weilin; Qiao, Yu; Yao, Jian

    2016-03-28

    Recent deep learning models have demonstrated strong capabilities for classifying text and non-text components in natural images. They extract a high-level feature computed globally from a whole image component (patch), where the cluttered background information may dominate true text features in the deep representation. This leads to less discriminative power and poorer robustness. In this work, we present a new system for scene text detection by proposing a novel Text-Attentional Convolutional Neural Network (Text-CNN) that particularly focuses on extracting text-related regions and features from the image components. We develop a new learning mechanism to train the Text-CNN with multi-level and rich supervised information, including text region mask, character label, and binary text/nontext information. The rich supervision information enables the Text-CNN with a strong capability for discriminating ambiguous texts, and also increases its robustness against complicated background components. The training process is formulated as a multi-task learning problem, where low-level supervised information greatly facilitates main task of text/non-text classification. In addition, a powerful low-level detector called Contrast- Enhancement Maximally Stable Extremal Regions (CE-MSERs) is developed, which extends the widely-used MSERs by enhancing intensity contrast between text patterns and background. This allows it to detect highly challenging text patterns, resulting in a higher recall. Our approach achieved promising results on the ICDAR 2013 dataset, with a F-measure of 0.82, improving the state-of-the-art results substantially.

  4. Deep convolutional networks for pancreas segmentation in CT imaging

    NASA Astrophysics Data System (ADS)

    Roth, Holger R.; Farag, Amal; Lu, Le; Turkbey, Evrim B.; Summers, Ronald M.

    2015-03-01

    Automatic organ segmentation is an important prerequisite for many computer-aided diagnosis systems. The high anatomical variability of organs in the abdomen, such as the pancreas, prevents many segmentation methods from achieving high accuracies when compared to state-of-the-art segmentation of organs like the liver, heart or kidneys. Recently, the availability of large annotated training sets and the accessibility of affordable parallel computing resources via GPUs have made it feasible for "deep learning" methods such as convolutional networks (ConvNets) to succeed in image classification tasks. These methods have the advantage that used classification features are trained directly from the imaging data. We present a fully-automated bottom-up method for pancreas segmentation in computed tomography (CT) images of the abdomen. The method is based on hierarchical coarse-to-fine classification of local image regions (superpixels). Superpixels are extracted from the abdominal region using Simple Linear Iterative Clustering (SLIC). An initial probability response map is generated, using patch-level confidences and a two-level cascade of random forest classifiers, from which superpixel regions with probabilities larger 0.5 are retained. These retained superpixels serve as a highly sensitive initial input of the pancreas and its surroundings to a ConvNet that samples a bounding box around each superpixel at different scales (and random non-rigid deformations at training time) in order to assign a more distinct probability of each superpixel region being pancreas or not. We evaluate our method on CT images of 82 patients (60 for training, 2 for validation, and 20 for testing). Using ConvNets we achieve maximum Dice scores of an average 68% +/- 10% (range, 43-80%) in testing. This shows promise for accurate pancreas segmentation, using a deep learning approach and compares favorably to state-of-the-art methods.

  5. Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images.

    PubMed

    Pereira, Sergio; Pinto, Adriano; Alves, Victor; Silva, Carlos A

    2016-05-01

    Among brain tumors, gliomas are the most common and aggressive, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of oncological patients. Magnetic resonance imaging (MRI) is a widely used imaging technique to assess these tumors, but the large amount of data produced by MRI prevents manual segmentation in a reasonable time, limiting the use of precise quantitative measurements in the clinical practice. So, automatic and reliable segmentation methods are required; however, the large spatial and structural variability among brain tumors make automatic segmentation a challenging problem. In this paper, we propose an automatic segmentation method based on Convolutional Neural Networks (CNN), exploring small 3 ×3 kernels. The use of small kernels allows designing a deeper architecture, besides having a positive effect against overfitting, given the fewer number of weights in the network. We also investigated the use of intensity normalization as a pre-processing step, which though not common in CNN-based segmentation methods, proved together with data augmentation to be very effective for brain tumor segmentation in MRI images. Our proposal was validated in the Brain Tumor Segmentation Challenge 2013 database (BRATS 2013), obtaining simultaneously the first position for the complete, core, and enhancing regions in Dice Similarity Coefficient metric (0.88, 0.83, 0.77) for the Challenge data set. Also, it obtained the overall first position by the online evaluation platform. We also participated in the on-site BRATS 2015 Challenge using the same model, obtaining the second place, with Dice Similarity Coefficient metric of 0.78, 0.65, and 0.75 for the complete, core, and enhancing regions, respectively.

  6. Brain Tumor Segmentation using Convolutional Neural Networks in MRI Images.

    PubMed

    Pereira, Sergio; Pinto, Adriano; Alves, Victor; Silva, Carlos A

    2016-03-04

    Among brain tumors, gliomas are the most common and aggressive, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of oncological patients. Magnetic Resonance Imaging (MRI) is a widely used imaging technique to assess these tumors, but the large amount of data produced by MRI prevents manual segmentation in a reasonable time, limiting the use of precise quantitative measurements in the clinical practice. So, automatic and reliable segmentation methods are required; however, the large spatial and structural variability among brain tumors make automatic segmentation a challenging problem. In this paper, we propose an automatic segmentation method based on Convolutional Neural Networks (CNN), exploring small 33 kernels. The use of small kernels allows designing a deeper architecture, besides having a positive effect against overfitting, given the fewer number of weights in the network. We also investigated the use of intensity normalization as a pre-processing step, which though not common in CNN-based segmentation methods, proved together with data augmentation to be very effective for brain tumor segmentation in MRI images. Our proposal was validated in the Brain Tumor Segmentation Challenge 2013 database (BRATS 2013), obtaining simultaneously the first position for the complete, core, and enhancing regions in Dice Similarity Coefficient metric (0:88, 0:83, 0:77) for the Challenge data set. Also, it obtained the overall first position by the online evaluation platform. We also participated in the on-site BRATS 2015 Challenge using the same model, obtaining the second place, with Dice Similarity Coefficient metric of 0:78, 0:65, and 0:75 for the complete, core, and enhancing regions, respectively.

  7. A staggered-grid convolutional differentiator for elastic wave modelling

    NASA Astrophysics Data System (ADS)

    Sun, Weijia; Zhou, Binzhong; Fu, Li-Yun

    2015-11-01

    The computation of derivatives in governing partial differential equations is one of the most investigated subjects in the numerical simulation of physical wave propagation. An analytical staggered-grid convolutional differentiator (CD) for first-order velocity-stress elastic wave equations is derived in this paper by inverse Fourier transformation of the band-limited spectrum of a first derivative operator. A taper window function is used to truncate the infinite staggered-grid CD stencil. The truncated CD operator is almost as accurate as the analytical solution, and as efficient as the finite-difference (FD) method. The selection of window functions will influence the accuracy of the CD operator in wave simulation. We search for the optimal Gaussian windows for different order CDs by minimizing the spectral error of the derivative and comparing the windows with the normal Hanning window function for tapering the CD operators. It is found that the optimal Gaussian window appears to be similar to the Hanning window function for tapering the same CD operator. We investigate the accuracy of the windowed CD operator and the staggered-grid FD method with different orders. Compared to the conventional staggered-grid FD method, a short staggered-grid CD operator achieves an accuracy equivalent to that of a long FD operator, with lower computational costs. For example, an 8th order staggered-grid CD operator can achieve the same accuracy of a 16th order staggered-grid FD algorithm but with half of the computational resources and time required. Numerical examples from a homogeneous model and a crustal waveguide model are used to illustrate the superiority of the CD operators over the conventional staggered-grid FD operators for the simulation of wave propagations.

  8. Single-trial EEG RSVP classification using convolutional neural networks

    NASA Astrophysics Data System (ADS)

    Shamwell, Jared; Lee, Hyungtae; Kwon, Heesung; Marathe, Amar R.; Lawhern, Vernon; Nothwang, William

    2016-05-01

    Traditionally, Brain-Computer Interfaces (BCI) have been explored as a means to return function to paralyzed or otherwise debilitated individuals. An emerging use for BCIs is in human-autonomy sensor fusion where physiological data from healthy subjects is combined with machine-generated information to enhance the capabilities of artificial systems. While human-autonomy fusion of physiological data and computer vision have been shown to improve classification during visual search tasks, to date these approaches have relied on separately trained classification models for each modality. We aim to improve human-autonomy classification performance by developing a single framework that builds codependent models of human electroencephalograph (EEG) and image data to generate fused target estimates. As a first step, we developed a novel convolutional neural network (CNN) architecture and applied it to EEG recordings of subjects classifying target and non-target image presentations during a rapid serial visual presentation (RSVP) image triage task. The low signal-to-noise ratio (SNR) of EEG inherently limits the accuracy of single-trial classification and when combined with the high dimensionality of EEG recordings, extremely large training sets are needed to prevent overfitting and achieve accurate classification from raw EEG data. This paper explores a new deep CNN architecture for generalized multi-class, single-trial EEG classification across subjects. We compare classification performance from the generalized CNN architecture trained across all subjects to the individualized XDAWN, HDCA, and CSP neural classifiers which are trained and tested on single subjects. Preliminary results show that our CNN meets and slightly exceeds the performance of the other classifiers despite being trained across subjects.

  9. Active pixel sensor pixel having a photodetector whose output is coupled to an output transistor gate

    NASA Technical Reports Server (NTRS)

    Fossum, Eric R. (Inventor); Nakamura, Junichi (Inventor); Kemeny, Sabrina E. (Inventor)

    2005-01-01

    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. A Simple Floating Gate (SFG) pixel structure could also be employed in the imager to provide a non-destructive readout and smaller pixel sizes.

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

    NASA Astrophysics Data System (ADS)

    Kriss, Michael A.

    2011-01-01

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

  11. Visualization of dyed NAPL concentration in transparent porous media using color space components

    NASA Astrophysics Data System (ADS)

    Kashuk, Sina; Mercurio, Sophia R.; Iskander, Magued

    2014-07-01

    Finding a correlation between image pixel information and non-aqueous phase liquid (NAPL) saturation is an important issue in bench-scale geo-environmental model studies that employ optical imaging techniques. Another concern is determining the best dye color and its optimum concentration as a tracer for use in mapping NAPL zones. Most bench scale flow studies employ monochromatic gray-scale imaging to analyze the concentration of mostly red dyed NAPL tracers in porous media. However, the use of grayscale utilizes a third of the available information in color images, which typically contain three color-space components. In this study, eight color spaces consisting of 24 color-space components were calibrated against dye concentration for three color-dyes. Additionally, multiple color space components were combined to increase the correlation between color-space data and dyed NAPL concentration. This work is performed to support imaging of NAPL migration in transparent synthetic soils representing the macroscopic behavior of natural soils. The transparent soil used in this study consists of fused quartz and a matched refractive index mineral-oil solution that represents the natural aquifer. The objective is to determine the best color dye concentration and ideal color space components for rendering dyed sucrose-saturated fused quartz that represents contamination of the natural aquifer by a dense NAPL (DNAPL). Calibration was achieved for six NAPL zone lengths using 3456 images (24 color space components × 3 dyes × 48 NAPL combinations) of contaminants within a defined criteria expressed as peak signal to noise ratio. The effect of data filtering was also considered and a convolution average filter is recommended for image conditioning. The technology presented in this paper is fast, accurate, non-intrusive and inexpensive method for quantifying contamination zones using transparent soil models.

  12. Visualization of dyed NAPL concentration in transparent porous media using color space components.

    PubMed

    Kashuk, Sina; Mercurio, Sophia R; Iskander, Magued

    2014-07-01

    Finding a correlation between image pixel information and non-aqueous phase liquid (NAPL) saturation is an important issue in bench-scale geo-environmental model studies that employ optical imaging techniques. Another concern is determining the best dye color and its optimum concentration as a tracer for use in mapping NAPL zones. Most bench scale flow studies employ monochromatic gray-scale imaging to analyze the concentration of mostly red dyed NAPL tracers in porous media. However, the use of grayscale utilizes a third of the available information in color images, which typically contain three color-space components. In this study, eight color spaces consisting of 24 color-space components were calibrated against dye concentration for three color-dyes. Additionally, multiple color space components were combined to increase the correlation between color-space data and dyed NAPL concentration. This work is performed to support imaging of NAPL migration in transparent synthetic soils representing the macroscopic behavior of natural soils. The transparent soil used in this study consists of fused quartz and a matched refractive index mineral-oil solution that represents the natural aquifer. The objective is to determine the best color dye concentration and ideal color space components for rendering dyed sucrose-saturated fused quartz that represents contamination of the natural aquifer by a dense NAPL (DNAPL). Calibration was achieved for six NAPL zone lengths using 3456 images (24 color space components×3 dyes×48 NAPL combinations) of contaminants within a defined criteria expressed as peak signal to noise ratio. The effect of data filtering was also considered and a convolution average filter is recommended for image conditioning. The technology presented in this paper is fast, accurate, non-intrusive and inexpensive method for quantifying contamination zones using transparent soil models.

  13. Error control techniques for satellite and space communications

    NASA Technical Reports Server (NTRS)

    Costello, Daniel J., Jr.

    1992-01-01

    Worked performed during the reporting period is summarized. Construction of robustly good trellis codes for use with sequential decoding was developed. The robustly good trellis codes provide a much better trade off between free distance and distance profile. The unequal error protection capabilities of convolutional codes was studied. The problem of finding good large constraint length, low rate convolutional codes for deep space applications is investigated. A formula for computing the free distance of 1/n convolutional codes was discovered. Double memory (DM) codes, codes with two memory units per unit bit position, were studied; a search for optimal DM codes is being conducted. An algorithm for constructing convolutional codes from a given quasi-cyclic code was developed. Papers based on the above work are included in the appendix.

  14. Accounting for sub-pixel variability of clouds and/or unresolved spectral variability, as needed, with generalized radiative transfer theory

    DOE PAGES

    Davis, Anthony B.; Xu, Feng; Collins, William D.

    2015-03-01

    Atmospheric hyperspectral VNIR sensing struggles with sub-pixel variability of clouds and limited spectral resolution mixing molecular lines. Our generalized radiative transfer model addresses both issues with new propagation kernels characterized by power-law decay in space.

  15. Pixel-Level Simulation of Imaging Data

    NASA Astrophysics Data System (ADS)

    Stoughton, C.; Kuropatkin, N. P.; Neilsen, E., Jr.; Harms, D. C.

    2007-10-01

    We are preparing a set of Java packages to facilitate the design and operation of imaging surveys. The packages use shapelets to describe shapes of astronomical sources, optical distortions, and shear from weak gravitational lensing. We introduce noise, bad pixels, cosmic rays, the pupil image, saturation, and other observational effects. A set of utility classes handles I/O, plotting, and interfaces to existing packages: nom.tam.fits for FITS I/O; uk.ac.starlink.table for tables; and cern.colt for algorithms. The packages have been used to generate images for the Dark Energy Survey data challenges, and will be used by SNAP to continue evaluating its design.

  16. Small pixel uncooled imaging FPAs and applications

    NASA Astrophysics Data System (ADS)

    Blackwell, Richard; Franks, Glen; Lacroix, Daniel; Hyland, Sandra; Murphy, Robert

    2010-04-01

    BAE Systems continues to make dramatic progress in uncooled microbolometer sensors and applications. This paper will review the latest advancements in microbolometer technology at BAE Systems, including the development status of 17 micrometer pixel pitch detectors and imaging modules which are entering production and will be finding their way into BAE Systems products and applications. Benefits include increased die per wafer and potential benefits to SWAP for many applications. Applications include thermal weapons sights, thermal imaging modules for remote weapon stations, vehicle situational awareness sensors and mast/pole mounted sensors.

  17. Active pixel sensor array with electronic shuttering

    NASA Technical Reports Server (NTRS)

    Fossum, Eric R. (Inventor)

    2002-01-01

    An active pixel cell includes electronic shuttering capability. The cell can be shuttered to prevent additional charge accumulation. One mode transfers the current charge to a storage node that is blocked against accumulation of optical radiation. The charge is sampled from a floating node. Since the charge is stored, the node can be sampled at the beginning and the end of every cycle. Another aspect allows charge to spill out of the well whenever the charge amount gets higher than some amount, thereby providing anti blooming.

  18. A neighbor pixel communication filtering structure for Dynamic Vision Sensors

    NASA Astrophysics Data System (ADS)

    Xu, Yuan; Liu, Shiqi; Lu, Hehui; Zhang, Zilong

    2017-02-01

    For Dynamic Vision Sensors (DVS), thermal noise and junction leakage current induced Background Activity (BA) is the major cause of the deterioration of images quality. Inspired by the smoothing filtering principle of horizontal cells in vertebrate retina, A DVS pixel with Neighbor Pixel Communication (NPC) filtering structure is proposed to solve this issue. The NPC structure is designed to judge the validity of pixel's activity through the communication between its 4 adjacent pixels. The pixel's outputs will be suppressed if its activities are determined not real. The proposed pixel's area is 23.76×24.71μm2 and only 3ns output latency is introduced. In order to validate the effectiveness of the structure, a 5×5 pixel array has been implemented in SMIC 0.13μm CIS process. 3 test cases of array's behavioral model show that the NPC-DVS have an ability of filtering the BA.

  19. 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.

  20. The Phase1 CMS Pixel detector upgrade

    NASA Astrophysics Data System (ADS)

    Tavolaro, V. R.

    2016-12-01

    The pixel detector of the CMS experiment will be replaced in an extended end-of-year shutdown during winter 2016/2017 with an upgraded one able to cope with peak instantaneous luminosities beyond the nominal LHC instantaneous luminosity of 1 × 1034 cm-2 s-1. Under the conditions expected in the coming years, which will see an increase of a factor two in instantaneous luminosity, the present system would experience a dynamic inefficiency caused mainly by data losses due to buffer overflows. The Phase I upgrade of the CMS pixel detector, described in this paper, will operate at full efficiency at an instantaneous luminosity of 2 × 1034 cm-2 s-1 and beyond, thanks to a new readout chip. The new detector will feature one additional tracking point both in the barrel and in the forward regions, while reducing the material budget as a result of a new CO2 cooling system and optimised layout of the services. In this paper, the design and the technological choices of the Phase I detector will be reviewed and the status of the construction of the detector and the performance of its components will be discussed.

  1. Ultra large mode area pixelated Bragg fiber

    NASA Astrophysics Data System (ADS)

    Yehouessi, J.-P.; Bouwmans, G.; Vanvincq, O.; Cassez, A.; Habert, R.; Quiquempois, Y.; Bigot, L.

    2016-03-01

    We report on the design and the fabrication of a new design of an all-solid Bragg fiber based on the pixelization and heterostructuration of a cladding made of only two high index rings. The thickness of the low index ring as well as the geometry of the heterostructuration (its symmetry and the number of removed pixels) have been chosen to maximize the confinement losses of the Higher Order Modes (HOM) (above 10 dB/m) while keeping the Fundamental Mode (FM) losses low (below 0.1 dB/m). The proposed geometry allows having access to different Mode Field Diameter (MFD) from 54 μm to 60 μm at 1 μm wavelength by drawing the same stack to different fiber (and hence, core) diameters. As a result, a record MFD of 60 μm is reported for a Solid Core Photonic Bandgap Fiber (SC-PBGF) and single-mode behavior is obtained experimentally even for a short fiber length (few tens centimeters) maintained straight.

  2. Silicon pixel R&D for CLIC

    NASA Astrophysics Data System (ADS)

    Munker, M.

    2017-01-01

    Challenging detector requirements are imposed by the physics goals at the future multi-TeV e+ e‑ Compact Linear Collider (CLIC). A single point resolution of 3 μm for the vertex detector and 7 μm for the tracker is required. Moreover, the CLIC vertex detector and tracker need to be extremely light weighted with a material budget of 0.2% X0 per layer in the vertex detector and 1–2% X0 in the tracker. A fast time slicing of 10 ns is further required to suppress background from beam-beam interactions. A wide range of sensor and readout ASIC technologies are investigated within the CLIC silicon pixel R&D effort. Various hybrid planar sensor assemblies with a pixel size of 25×25 μm2 and 55×55 μm2 have been produced and characterised by laboratory measurements and during test-beam campaigns. Experimental and simulation results for thin (50 μm–500 μm) slim edge and active-edge planar, and High-Voltage CMOS sensors hybridised to various readout ASICs (Timepix, Timepix3, CLICpix) are presented.

  3. Further applications for mosaic pixel FPA technology

    NASA Astrophysics Data System (ADS)

    Liddiard, Kevin C.

    2011-06-01

    In previous papers to this SPIE forum the development of novel technology for next generation PIR security sensors has been described. This technology combines the mosaic pixel FPA concept with low cost optics and purpose-designed readout electronics to provide a higher performance and affordable alternative to current PIR sensor technology, including an imaging capability. Progressive development has resulted in increased performance and transition from conventional microbolometer fabrication to manufacture on 8 or 12 inch CMOS/MEMS fabrication lines. A number of spin-off applications have been identified. In this paper two specific applications are highlighted: high performance imaging IRFPA design and forest fire detection. The former involves optional design for small pixel high performance imaging. The latter involves cheap expendable sensors which can detect approaching fire fronts and send alarms with positional data via mobile phone or satellite link. We also introduce to this SPIE forum the application of microbolometer IR sensor technology to IoT, the Internet of Things.

  4. Convolution effect on TCR log response curve and the correction method for it

    NASA Astrophysics Data System (ADS)

    Chen, Q.; Liu, L. J.; Gao, J.

    2016-09-01

    Through-casing resistivity (TCR) logging has been successfully used in production wells for the dynamic monitoring of oil pools and the distribution of the residual oil, but its vertical resolution has limited its efficiency in identification of thin beds. The vertical resolution is limited by the distortion phenomenon of vertical response of TCR logging. The distortion phenomenon was studied in this work. It was found that the vertical response curve of TCR logging is the convolution of the true formation resistivity and the convolution function of TCR logging tool. Due to the effect of convolution, the measurement error at thin beds can reach 30% or even bigger. Thus the information of thin bed might be covered up very likely. The convolution function of TCR logging tool was obtained in both continuous and discrete way in this work. Through modified Lyle-Kalman deconvolution method, the true formation resistivity can be optimally estimated, so this inverse algorithm can correct the error caused by the convolution effect. Thus it can improve the vertical resolution of TCR logging tool for identification of thin beds.

  5. Three-dimensional cascaded system analysis of a 50 µm pixel pitch wafer-scale CMOS active pixel sensor x-ray detector for digital breast tomosynthesis

    NASA Astrophysics Data System (ADS)

    Zhao, C.; Vassiljev, N.; Konstantinidis, A. C.; Speller, R. D.; Kanicki, J.

    2017-03-01

    High-resolution, low-noise x-ray detectors based on the complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) technology have been developed and proposed for digital breast tomosynthesis (DBT). In this study, we evaluated the three-dimensional (3D) imaging performance of a 50 µm pixel pitch CMOS APS x-ray detector named DynAMITe (Dynamic Range Adjustable for Medical Imaging Technology). The two-dimensional (2D) angle-dependent modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE) were experimentally characterized and modeled using the cascaded system analysis at oblique incident angles up to 30°. The cascaded system model was extended to the 3D spatial frequency space in combination with the filtered back-projection (FBP) reconstruction method to calculate the 3D and in-plane MTF, NNPS and DQE parameters. The results demonstrate that the beam obliquity blurs the 2D MTF and DQE in the high spatial frequency range. However, this effect can be eliminated after FBP image reconstruction. In addition, impacts of the image acquisition geometry and detector parameters were evaluated using the 3D cascaded system analysis for DBT. The result shows that a wider projection angle range (e.g.  ±30°) improves the low spatial frequency (below 5 mm‑1) performance of the CMOS APS detector. In addition, to maintain a high spatial resolution for DBT, a focal spot size of smaller than 0.3 mm should be used. Theoretical analysis suggests that a pixelated scintillator in combination with the 50 µm pixel pitch CMOS APS detector could further improve the 3D image resolution. Finally, the 3D imaging performance of the CMOS APS and an indirect amorphous silicon (a-Si:H) thin-film transistor (TFT) passive pixel sensor (PPS) detector was simulated and compared.

  6. Three-dimensional cascaded system analysis of a 50 µm pixel pitch wafer-scale CMOS active pixel sensor x-ray detector for digital breast tomosynthesis.

    PubMed

    Zhao, C; Vassiljev, N; Konstantinidis, A C; Speller, R D; Kanicki, J

    2017-03-07

    High-resolution, low-noise x-ray detectors based on the complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) technology have been developed and proposed for digital breast tomosynthesis (DBT). In this study, we evaluated the three-dimensional (3D) imaging performance of a 50 µm pixel pitch CMOS APS x-ray detector named DynAMITe (Dynamic Range Adjustable for Medical Imaging Technology). The two-dimensional (2D) angle-dependent modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE) were experimentally characterized and modeled using the cascaded system analysis at oblique incident angles up to 30°. The cascaded system model was extended to the 3D spatial frequency space in combination with the filtered back-projection (FBP) reconstruction method to calculate the 3D and in-plane MTF, NNPS and DQE parameters. The results demonstrate that the beam obliquity blurs the 2D MTF and DQE in the high spatial frequency range. However, this effect can be eliminated after FBP image reconstruction. In addition, impacts of the image acquisition geometry and detector parameters were evaluated using the 3D cascaded system analysis for DBT. The result shows that a wider projection angle range (e.g.  ±30°) improves the low spatial frequency (below 5 mm(-1)) performance of the CMOS APS detector. In addition, to maintain a high spatial resolution for DBT, a focal spot size of smaller than 0.3 mm should be used. Theoretical analysis suggests that a pixelated scintillator in combination with the 50 µm pixel pitch CMOS APS detector could further improve the 3D image resolution. Finally, the 3D imaging performance of the CMOS APS and an indirect amorphous silicon (a-Si:H) thin-film transistor (TFT) passive pixel sensor (PPS) detector was simulated and compared.

  7. Moving from pixel to object scale when inverting radiative transfer models for quantitative estimation of biophysical variables in vegetation (Invited)

    NASA Astrophysics Data System (ADS)

    Atzberger, C.

    2013-12-01

    The robust and accurate retrieval of vegetation biophysical variables using RTM is seriously hampered by the ill-posedness of the inverse problem. The contribution presents our object-based inversion approach and evaluate it against measured data. The proposed method takes advantage of the fact that nearby pixels are generally more similar than those at a larger distance. For example, within a given vegetation patch, nearby pixels often share similar leaf angular distributions. This leads to spectral co-variations in the n-dimensional spectral features space, which can be used for regularization purposes. Using a set of leaf area index (LAI) measurements (n=26) acquired over alfalfa, sugar beet and garlic crops of the Barrax test site (Spain), it is demonstrated that the proposed regularization using neighbourhood information yields more accurate results compared to the traditional pixel-based inversion. Principle of the ill-posed inverse problem and the proposed solution illustrated in the red-nIR feature space using (PROSAIL). [A] spectral trajectory ('soil trajectory') obtained for one leaf angle (ALA) and one soil brightness (αsoil), when LAI varies between 0 and 10, [B] 'soil trajectories' for 5 soil brightness values and three leaf angles, [C] ill-posed inverse problem: different combinations of ALA × αsoil yield an identical crossing point, [D] object-based RTM inversion; only one 'soil trajectory' fits all nine pixelswithin a gliding (3×3) window. The black dots (plus the rectangle=central pixel) represent the hypothetical position of nine pixels within a 3×3 (gliding) window. Assuming that over short distances (× 1 pixel) variations in soil brightness can be neglected, the proposed object-based inversion searches for one common set of ALA × αsoil so that the resulting 'soil trajectory' best fits the nine measured pixels. Ground measured vs. retrieved LAI values for three crops. Left: proposed object-based approach. Right: pixel-based inversion

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  9. Illustrating Surface Shape in Volume Data via Principal Direction-Driven 3D Line Integral Convolution

    NASA Technical Reports Server (NTRS)

    Interrante, Victoria

    1997-01-01

    The three-dimensional shape and relative depth of a smoothly curving layered transparent surface may be communicated particularly effectively when the surface is artistically enhanced with sparsely distributed opaque detail. This paper describes how the set of principal directions and principal curvatures specified by local geometric operators can be understood to define a natural 'flow' over the surface of an object, and can be used to guide the placement of the lines of a stroke texture that seeks to represent 3D shape information in a perceptually intuitive way. The driving application for this work is the visualization of layered isovalue surfaces in volume data, where the particular identity of an individual surface is not generally known a priori and observers will typically wish to view a variety of different level surfaces from the same distribution, superimposed over underlying opaque structures. By advecting an evenly distributed set of tiny opaque particles, and the empty space between them, via 3D line integral convolution through the vector field defined by the principal directions and principal curvatures of the level surfaces passing through each gridpoint of a 3D volume, it is possible to generate a single scan-converted solid stroke texture that may intuitively represent the essential shape information of any level surface in the volume. To generate longer strokes over more highly curved areas, where the directional information is both most stable and most relevant, and to simultaneously downplay the visual impact of directional information in the flatter regions, one may dynamically redefine the length of the filter kernel according to the magnitude of the maximum principal curvature of the level surface at the point around which it is applied.

  10. Serial pixel analog-to-digital converter (ADC)

    NASA Astrophysics Data System (ADS)

    Larson, Eric D.

    2010-02-01

    This method reduces the data path from the counter to the pixel register of the analog-to-digital converter (ADC) from as many as 10 bits to a single bit. The reduction in data path width is accomplished by using a coded serial data stream similar to a pseudo random number (PRN) generator. The resulting encoded pixel data is then decoded into a standard hexadecimal format before storage. The high-speed serial pixel ADC concept is based on the single-slope integrating pixel ADC architecture. Previous work has described a massively parallel pixel readout of a similar architecture. The serial ADC connection is similar to the state-of-the art method with the exception that the pixel ADC register is a shift register and the data path is a single bit. A state-of-the-art individual-pixel ADC uses a single-slope charge integration converter architecture with integral registers and "one-hot" counters. This implies that parallel data bits are routed among the counter and the individual on-chip pixel ADC registers. The data path bit-width to the pixel is therefore equivalent to the pixel ADC bit resolution.

  11. Analysis of pixel circuits in CMOS image sensors

    NASA Astrophysics Data System (ADS)

    Mei, Zou; Chen, Nan; Yao, Li-bin

    2015-04-01

    CMOS image sensors (CIS) have lower power consumption, lower cost and smaller size than CCD image sensors. However, generally CCDs have higher performance than CIS mainly due to lower noise. The pixel circuit used in CIS is the first part of the signal processing circuit and connected to photodiode directly, so its performance will greatly affect the CIS or even the whole imaging system. To achieve high performance, CMOS image sensors need advanced pixel circuits. There are many pixel circuits used in CIS, such as passive pixel sensor (PPS), 3T and 4T active pixel sensor (APS), capacitive transimpedance amplifier (CTIA), and passive pixel sensor (PPS). At first, the main performance parameters of each pixel structure including the noise, injection efficiency, sensitivity, power consumption, and stability of bias voltage are analyzed. Through the theoretical analysis of those pixel circuits, it is concluded that CTIA pixel circuit has good noise performance, high injection efficiency, stable photodiode bias, and high sensitivity with small integrator capacitor. Furthermore, the APS and CTIA pixel circuits are simulated in a standard 0.18-μm CMOS process and using a n-well/p-sub photodiode by SPICE and the simulation result confirms the theoretical analysis result. It shows the possibility that CMOS image sensors can be extended to a wide range of applications requiring high performance.

  12. Edge effects in a small pixel CdTe for X-ray imaging

    NASA Astrophysics Data System (ADS)

    Duarte, D. D.; Bell, S. J.; Lipp, J.; Schneider, A.; Seller, P.; Veale, M. C.; Wilson, M. D.; Baker, M. A.; Sellin, P. J.; Kachkanov, V.; Sawhney, K. J. S.

    2013-10-01

    Large area detectors capable of operating with high detection efficiency at energies above 30 keV are required in many contemporary X-ray imaging applications. The properties of high Z compound semiconductors, such as CdTe, make them ideally suitable to these applications. The STFC Rutherford Appleton Laboratory has developed a small pixel CdTe detector with 80 × 80 pixels on a 250 μm pitch. Historically, these detectors have included a 200 μm wide guard band around the pixelated anode to reduce the effect of defects in the crystal edge. The latest version of the detector ASIC is capable of four-side butting that allows the tiling of N × N flat panel arrays. To limit the dead space between modules to the width of one pixel, edgeless detector geometries have been developed where the active volume of the detector extends to the physical edge of the crystal. The spectroscopic performance of an edgeless CdTe detector bump bonded to the HEXITEC ASIC was tested with sealed radiation sources and compared with a monochromatic X-ray micro-beam mapping measurements made at the Diamond Light Source, U.K. The average energy resolution at 59.54 keV of bulk and edge pixels was 1.23 keV and 1.58 keV, respectively. 87% of the edge pixels present fully spectroscopic performance demonstrating that edgeless CdTe detectors are a promising technology for the production of large panel radiation detectors for X-ray imaging.

  13. Research on Optical Observation for Space Debris

    NASA Astrophysics Data System (ADS)

    Sun, R. Y.

    2015-01-01

    Space debris has been recognized as a serious danger for operational spacecraft and manned spaceflights. Discussions are made in the methods of high order position precision and high detecting efficiency for space debris, including the design of surveying strategy, the extraction of object centroid, the precise measurement of object positions, the correlation and catalogue technique. To meet the needs of detecting space objects in the GEO (Geosynchronous Orbit), and prevent the saturation of CCD pixels with a long exposure time, a method of stacking a series of short exposure time images is presented. The results demonstrate that the saturation of pixels is eliminated effectively, and the SNR (Signal Noise Ratio) is increased by about 3.2 times, the detection ability is improved by about 2.5 magnitude when 10 seriate images are stacked, and the accuracy is reliable to satisfy the requirement by using the mean plate parameters for the astronomical orientation. A method combined with the geometrical morphology identification and linear correlation is adopted for the data calibration of IADC (Inter-Agency Space Debris Coordination Committee) AI23.4. After calibration, 139 tracklets are acquired, in which 116 tracklets are correlated with the catalogue. The distributions of magnitude, semi-major axis, inclination, and longitude of ascending node are obtained as well. A new method for detecting space debris in images is presented. The algorithm sets the gate around the image of objects, then several criterions are introduced for the object detection, at last the object position in the frame is obtained by the barycenter method and a simple linear transformation. The tests demonstrate that this technique is convenient for application, and the objects in image can be detected with a high centroid precision. In the observations of space objects, the shutter of camera is often removed, and the smear noise is ineluctable. Based on the differences of the geometry between the

  14. ON EPIMORPHICITY OF A CONVOLUTION OPERATOR IN CONVEX DOMAINS IN \\mathbf{C}^l

    NASA Astrophysics Data System (ADS)

    Morzhakov, V. V.

    1988-02-01

    Let D be a convex domain and K a convex compact set in \\mathbf{C}^l; let H(D) be the space of analytic functions in D, provided with the topology of uniform convergence on compact sets, and H(K) the space of germs of analytic functions on K with the natural inductive limit topology; and let H'(K) be the space dual to H(K). Each functional T\\in H'(K) generates a convolution operator (\\check{T}y)(z)=T_\\zeta(y(z+\\zeta)), y\\in H(D+K), z\\in D, which acts continuously from H(D+K) into H(D). Further let (\\mathscr{F}T)(z)=T_\\zeta(\\exp\\langle z,\\,\\zeta\\rangle) be the Fourier-Borel transform of the functional T\\in H'(K).In this paper the following theorem is proved:Theorem. Let D be a bounded convex domain in \\mathbf{C}^l with boundary of class C^1 or D=D_1\\times\\dots \\times D_l, where the D_j are bounded planar convex domains with boundaries of class C^1, and let T\\in H'(K). In order that \\check{T}(H(D+K))=H(D) it is necessary and sufficient that 1) \\mathscr{L}^*_{\\mathscr{F}T}(\\zeta)=h_K(\\zeta) for all \\zeta\\in\\mathbf{C}^l, and 2) (\\mathscr{F}T)(z) be a function of completely regular growth in \\mathbf{C}^l in the sense of weak convergence in D'(\\mathbf{C}^l).Here \\displaystyle \\mathscr{L}^*_{\\mathscr{F}T}(\\zeta)=\\varlimsup_{r\\to\\zeta}\\,\\varlimsup_{r\\to\\infty}\\frac{\\ln\\vert(\\mathscr{F}T)(rz)\\vert}{r}is the regularized radial indicator of the entire function (\\mathscr{F}T)(z), and h_K(\\zeta) is the support function of the compact set K.Bibliography: 29 titles.

  15. How big is an OMI pixel?

    NASA Astrophysics Data System (ADS)

    de Graaf, Martin; Sihler, Holger; Tilstra, Lieuwe G.; Stammes, Piet

    2016-08-01

    The Ozone Monitoring Instrument (OMI) is a push-broom imaging spectrometer, observing solar radiation backscattered by the Earth's atmosphere and surface. The incoming radiation is detected using a static imaging CCD (charge-coupled device) detector array with no moving parts, as opposed to most of the previous satellite spectrometers, which used a moving mirror to scan the Earth in the across-track direction. The field of view (FoV) of detector pixels is the solid angle from which radiation is observed, averaged over the integration time of a measurement. The OMI FoV is not quadrangular, which is common for scanning instruments, but rather super-Gaussian shaped and overlapping with the FoV of neighbouring pixels. This has consequences for pixel-area-dependent applications, like cloud fraction products, and visualisation.The shapes and sizes of OMI FoVs were determined pre-flight by theoretical and experimental tests but never verified after launch. In this paper the OMI FoV is characterised using collocated MODerate resolution Imaging Spectroradiometer (MODIS) reflectance measurements. MODIS measurements have a much higher spatial resolution than OMI measurements and spectrally overlap at 469 nm. The OMI FoV was verified by finding the highest correlation between MODIS and OMI reflectances in cloud-free scenes, assuming a 2-D super-Gaussian function with varying size and shape to represent the OMI FoV. Our results show that the OMPIXCOR product 75FoV corner coordinates are accurate as the full width at half maximum (FWHM) of a super-Gaussian FoV model when this function is assumed. The softness of the function edges, modelled by the super-Gaussian exponents, is different in both directions and is view angle dependent.The optimal overlap function between OMI and MODIS reflectances is scene dependent and highly dependent on time differences between overpasses, especially with clouds in the scene. For partially clouded scenes, the optimal overlap function was

  16. [Application of numerical convolution in in vivo/in vitro correlation research].

    PubMed

    Yue, Peng

    2009-01-01

    This paper introduced the conception and principle of in vivo/in vitro correlation (IVIVC) and convolution/deconvolution methods, and elucidated in details the convolution strategy and method for calculating the in vivo absorption performance of the pharmaceutics according to the their pharmacokinetic data in Excel, then put the results forward to IVIVC research. Firstly, the pharmacokinetic data ware fitted by mathematical software to make up the lost points. Secondly, the parameters of the optimal fitted input function were defined by trail-and-error method according to the convolution principle in Excel under the hypothesis that all the input functions fit the Weibull functions. Finally, the IVIVC between in vivo input function and the in vitro dissolution was studied. In the examples, not only the application of this method was demonstrated in details but also its simplicity and effectiveness were proved by comparing with the compartment model method and deconvolution method. It showed to be a powerful tool for IVIVC research.

  17. Micro-pixel Displacement Estimation for the Heterogeneous and Asymmetric PSFs of STEP

    NASA Astrophysics Data System (ADS)

    Zhou, Jianfeng

    2015-08-01

    Search for Terrestrial Exo-Planest (STEP) is a Chinese space mission aims at the detection of nearby earth-alike planets, comprehensive research on the planetary system with 1uas astrometry precision in the space, which will be the highest precision detection mission in the world. Micro-pixel accuracy centroid displacement estimation and the relevant detector calibration are the key techniques in this mission. Due to the instability of the spacecraft, there will be a rotation displacement between two epochs of observations. In such situation, the heterogeneous and asymmetric Point Spread Functions (PSF) of the STEP will greatly reduce the accuracy of the centroid displacement estimation. To solve this problem, we present a new algorithm in which both displacement and rotation are considered, therefore micro-pixel accuracy displacement estimation is maintained.

  18. The Brain's Representations May Be Compatible With Convolution-Based Memory Models.

    PubMed

    Kato, Kenichi; Caplan, Jeremy B

    2017-02-13

    Convolution is a mathematical operation used in vector-models of memory that have been successful in explaining a broad range of behaviour, including memory for associations between pairs of items, an important primitive of memory upon which a broad range of everyday memory behaviour depends. However, convolution models have trouble with naturalistic item representations, which are highly auto-correlated (as one finds, e.g., with photographs), and this has cast doubt on their neural plausibility. Consequently, modellers working with convolution have used item representations composed of randomly drawn values, but introducing so-called noise-like representation raises the question how those random-like values might relate to actual item properties. We propose that a compromise solution to this problem may already exist. It has also long been known that the brain tends to reduce auto-correlations in its inputs. For example, centre-surround cells in the retina approximate a Difference-of-Gaussians (DoG) transform. This enhances edges, but also turns natural images into images that are closer to being statistically like white noise. We show the DoG-transformed images, although not optimal compared to noise-like representations, survive the convolution model better than naturalistic images. This is a proof-of-principle that the pervasive tendency of the brain to reduce auto-correlations may result in representations of information that are already adequately compatible with convolution, supporting the neural plausibility of convolution-based association-memory. (PsycINFO Database Record

  19. Punctured Parallel and Serial Concatenated Convolutional Codes for BPSK/QPSK Channels

    NASA Technical Reports Server (NTRS)

    Acikel, Omer Fatih

    1999-01-01

    As available bandwidth for communication applications becomes scarce, bandwidth-efficient modulation and coding schemes become ever important. Since their discovery in 1993, turbo codes (parallel concatenated convolutional codes) have been the center of the attention in the coding community because of their bit error rate performance near the Shannon limit. Serial concatenated convolutional codes have also been shown to be as powerful as turbo codes. In this dissertation, we introduce algorithms for designing bandwidth-efficient rate r = k/(k + 1),k = 2, 3,..., 16, parallel and rate 3/4, 7/8, and 15/16 serial concatenated convolutional codes via puncturing for BPSK/QPSK (Binary Phase Shift Keying/Quadrature Phase Shift Keying) channels. Both parallel and serial concatenated convolutional codes have initially, steep bit error rate versus signal-to-noise ratio slope (called the -"cliff region"). However, this steep slope changes to a moderate slope with increasing signal-to-noise ratio, where the slope is characterized by the weight spectrum of the code. The region after the cliff region is called the "error rate floor" which dominates the behavior of these codes in moderate to high signal-to-noise ratios. Our goal is to design high rate parallel and serial concatenated convolutional codes while minimizing the error rate floor effect. The design algorithm includes an interleaver enhancement procedure and finds the polynomial sets (only for parallel concatenated convolutional codes) and the puncturing schemes that achieve the lowest bit error rate performance around the floor for the code rates of interest.

  20. Pixel-level plasmonic microcavity infrared photodetector

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  1. Pixel-level plasmonic microcavity infrared photodetector

    PubMed Central

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

    2016-01-01

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

  2. Silicon buried channels for pixel detector cooling

    NASA Astrophysics Data System (ADS)

    Boscardin, M.; Conci, P.; Crivellari, M.; Ronchin, S.; Bettarini, S.; Bosi, F.

    2013-08-01

    The support and cooling structures add important contributions to the thickness, in radiation length, of vertex detectors. In order to minimize the material budget of pixel sensors, we developed a new approach to integrate the cooling into the silicon devices. The microchannels are formed in silicon using isotropic SF6 plasma etching in a DRIE (deep reactive ion etcher) equipment. Due to their peculiar profiles, the channels can be sealed by a layer of a PECVD silicon oxide. We have realized on a silicon wafer microchannels with different geometries and hydraulic diameters. We describe the main fabrication steps of microchannels with focus on the channel definition. The experimental results are reported on the thermal characterization of several prototypes, using a mixture of glycol and water as a liquid coolant. The prototypes have shown high cooling efficiency and high-pressure breaking strength.

  3. Operational experience with the ALICE pixel detector

    NASA Astrophysics Data System (ADS)

    Mastroserio, A.

    2017-01-01

    The Silicon Pixel Detector (SPD) constitutes the two innermost layers of the Inner Tracking System of the ALICE experiment and it is the closest detector to the interaction point. As a vertex detector, it has the unique feature of generating a trigger signal that contributes to the L0 trigger of the ALICE experiment. The SPD started collecting data since the very first pp collisions at LHC in 2009 and since then it has taken part in all pp, Pb-Pb and p-Pb data taking campaigns. This contribution will present the main features of the SPD, the detector performance and the operational experience, including calibration and optimization activities from Run 1 to Run 2.

  4. Research of IRFPAs' reliability evaluation by bad pixel

    NASA Astrophysics Data System (ADS)

    Hao, Lichao; Huang, Aibo; Lai, Canxiong; Chen, Xing; Hao, Mingming; Chen, Honglei; Lu, Guoguang; Huang, Yun; En, Yunfei

    2015-10-01

    Reliability is an important index to ensure the application of infrared focal plane arrays (IRFPAs) in complex environment, and it becomes a major bottleneck problem of IRFPAs' development. Because of the characteristics such as type, nature, quantity, location and distribution et al, bad pixel which contains initial bad pixel and used bad pixel has outstanding advantage for failure analysis and reliability evaluation of IRFPAs. In this paper, the structure of IRPFAs has been introduced in detail, and the damage mechanisms of used bad pixel also have been analyzed deeply. At the same time, the feasibility to study IRPFAs' damage stress, failure position, damage mechanism has been discussed all around. The research of bad pixel can be used to optimize the structure and process, meanwhile it also can improve the accuracy of bad pixel identification and replacements.

  5. Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

    NASA Astrophysics Data System (ADS)

    Acciarri, R.; Adams, C.; An, R.; Asaadi, J.; Auger, M.; Bagby, L.; Baller, B.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Bugel, L.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; James, C.; de Vries, J. Jan; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Jones, B. J. P.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; von Rohr, C. Rudolf; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van de Water, R. G.; Viren, B.; Weber, M.; Weston, J.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Zeller, G. P.; Zennamo, J.; Zhang, C.

    2017-03-01

    We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.

  6. Patient-specific dosimetry based on quantitative SPECT imaging and 3D-DFT convolution

    SciTech Connect

    Akabani, G.; Hawkins, W.G.; Eckblade, M.B.; Leichner, P.K.

    1999-01-01

    The objective of this study was to validate the use of a 3-D discrete Fourier Transform (3D-DFT) convolution method to carry out the dosimetry for I-131 for soft tissues in radioimmunotherapy procedures. To validate this convolution method, mathematical and physical phantoms were used as a basis of comparison with Monte Carlo transport (MCT) calculations which were carried out using the EGS4 system code. The mathematical phantom consisted of a sphere containing uniform and nonuniform activity distributions. The physical phantom consisted of a cylinder containing uniform and nonuniform activity distributions. Quantitative SPECT reconstruction was carried out using the Circular Harmonic Transform (CHT) algorithm.

  7. Blind separation of convolutive sEMG mixtures based on independent vector analysis

    NASA Astrophysics Data System (ADS)

    Wang, Xiaomei; Guo, Yina; Tian, Wenyan

    2015-12-01

    An independent vector analysis (IVA) method base on variable-step gradient algorithm is proposed in this paper. According to the sEMG physiological properties, the IVA model is applied to the frequency-domain separation of convolutive sEMG mixtures to extract motor unit action potentials information of sEMG signals. The decomposition capability of proposed method is compared to the one of independent component analysis (ICA), and experimental results show the variable-step gradient IVA method outperforms ICA in blind separation of convolutive sEMG mixtures.

  8. Implementation of large kernel 2-D convolution in limited FPGA resource

    NASA Astrophysics Data System (ADS)

    Zhong, Sheng; Li, Yang; Yan, Luxin; Zhang, Tianxu; Cao, Zhiguo

    2007-12-01

    2-D Convolution is a simple mathematical operation which is fundamental to many common image processing operators. Using FPGA to implement the convolver can greatly reduce the DSP's heavy burden in signal processing. But with the limit resource the FPGA can implement a convolver with small 2-D kernel. In this paper, An FIFO type line delayer is presented to serve as the data buffer for convolution to reduce the data fetching operation. A finite state machine is applied to control the reuse of multipliers and adders arrays. With these two techniques, a resource limited FPGA can be used to implement a larger kernel convolver which is commonly used in image process systems.

  9. Discrete singular convolution mapping methods for solving singular boundary value and boundary layer problems

    NASA Astrophysics Data System (ADS)

    Pindza, Edson; Maré, Eben

    2017-03-01

    A modified discrete singular convolution method is proposed. The method is based on the single (SE) and double (DE) exponential transformation to speed up the convergence of the existing methods. Numerical computations are performed on a wide variety of singular boundary value and singular perturbed problems in one and two dimensions. The obtained results from discrete singular convolution methods based on single and double exponential transformations are compared with each other, and with the existing methods too. Numerical results confirm that these methods are considerably efficient and accurate in solving singular and regular problems. Moreover, the method can be applied to a wide class of nonlinear partial differential equations.

  10. High-rate systematic recursive convolutional encoders: minimal trellis and code search

    NASA Astrophysics Data System (ADS)

    Benchimol, Isaac; Pimentel, Cecilio; Souza, Richard Demo; Uchôa-Filho, Bartolomeu F.

    2012-12-01

    We consider high-rate systematic recursive convolutional encoders to be adopted as constituent encoders in turbo schemes. Douillard and Berrou showed that, despite its complexity, the construction of high-rate turbo codes by means of high-rate constituent encoders is advantageous over the construction based on puncturing rate-1/2 constituent encoders. To reduce the decoding complexity of high-rate codes, we introduce the construction of the minimal trellis for a systematic recursive convolutional encoding matrix. A code search is conducted and examples are provided which indicate that a more finely grained decoding complexity-error performance trade-off is obtained.

  11. Fast computation algorithm for the Rayleigh-Sommerfeld diffraction formula using a type of scaled convolution.

    PubMed

    Nascov, Victor; Logofătu, Petre Cătălin

    2009-08-01

    We describe a fast computational algorithm able to evaluate the Rayleigh-Sommerfeld diffraction formula, based on a special formulation of the convolution theorem and the fast Fourier transform. What is new in our approach compared to other algorithms is the use of a more general type of convolution with a scale parameter, which allows for independent sampling intervals in the input and output computation windows. Comparison between the calculations made using our algorithm and direct numeric integration show a very good agreement, while the computation speed is increased by orders of magnitude.

  12. Fast Pixel Buffer For Processing With Lookup Tables

    NASA Technical Reports Server (NTRS)

    Fisher, Timothy E.

    1992-01-01

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

  13. Mapping Capacitive Coupling Among Pixels in a Sensor Array

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  14. Steganography on quantum pixel images using Shannon entropy

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  15. CMOS monolithic pixel sensors research and development at LBNL

    NASA Astrophysics Data System (ADS)

    Contarato, D.; Bussat, J.-M.; Denes, P.; Greiner, L.; Kim, T.; Stezelberger, T.; Wieman, H.; Battaglia, M.; Hooberman, B.; Tompkins, L.

    2007-12-01

    This paper summarizes the recent progress in the design and characterization of CMOS pixel sensors at LBNL. Results of lab tests, beam tests and radiation hardness tests carried out at LBNL on a test structure with pixels of various sizes are reported. The first results of the characterization of back-thinned CMOS pixel sensors are also reported, and future plans and activities are discussed.

  16. Hit efficiency study of CMS prototype forward pixel detectors

    SciTech Connect

    Kim, Dongwook; /Johns Hopkins U.

    2006-01-01

    In this paper the author describes the measurement of the hit efficiency of a prototype pixel device for the CMS forward pixel detector. These pixel detectors were FM type sensors with PSI46V1 chip readout. The data were taken with the 120 GeV proton beam at Fermilab during the period of December 2004 to February 2005. The detectors proved to be highly efficient (99.27 {+-} 0.02%). The inefficiency was primarily located near the corners of the individual pixels.

  17. A Fast Numerical Method for Max-Convolution and the Application to Efficient Max-Product Inference in Bayesian Networks.

    PubMed

    Serang, Oliver

    2015-08-01

    Observations depending on sums of random variables are common throughout many fields; however, no efficient solution is currently known for performing max-product inference on these sums of general discrete distributions (max-product inference can be used to obtain maximum a posteriori estimates). The limiting step to max-product inference is the max-convolution problem (sometimes presented in log-transformed form and denoted as "infimal convolution," "min-convolution," or "convolution on the tropical semiring"), for which no O(k log(k)) method is currently known. Presented here is an O(k log(k)) numerical method for estimating the max-convolution of two nonnegative vectors (e.g., two probability mass functions), where k is the length of the larger vector. This numerical max-convolution method is then demonstrated by performing fast max-product inference on a convolution tree, a data structure for performing fast inference given information on the sum of n discrete random variables in O(nk log(nk)log(n)) steps (where each random variable has an arbitrary prior distribution on k contiguous possible states). The numerical max-convolution method can be applied to specialized classes of hidden Markov models to reduce the runtime of computing the Viterbi path from nk(2) to nk log(k), and has potential application to the all-pairs shortest paths problem.

  18. Ultra-low power high-dynamic range color pixel embedding RGB to r-g chromaticity transformation

    NASA Astrophysics Data System (ADS)

    Lecca, Michela; Gasparini, Leonardo; Gottardi, Massimo

    2014-05-01

    This work describes a novel color pixel topology that converts the three chromatic components from the standard RGB space into the normalized r-g chromaticity space. This conversion is implemented with high-dynamic range and with no dc power consumption, and the auto-exposure capability of the sensor ensures to capture a high quality chromatic signal, even in presence of very bright illuminants or in the darkness. The pixel is intended to become the basic building block of a CMOS color vision sensor, targeted to ultra-low power applications for mobile devices, such as human machine interfaces, gesture recognition, face detection. The experiments show that significant improvements of the proposed pixel with respect to standard cameras in terms of energy saving and accuracy on data acquisition. An application to skin color-based description is presented.

  19. Module production for the Phase 1 upgrade of the CMS forward pixel detector

    NASA Astrophysics Data System (ADS)

    Siado Castaneda, Joaquin

    2017-01-01

    For Run 2 the Large Hadron Collider will run at a much higher instantaneous luminosity, which requires an upgrade of the CMS pixel detector. The detector consists of rectangular silicon sensors, segmented into 100 μm by 150 μm pixels, bonded to readout chips, with one sensor and a 8x2 array of readout chips forming a module. Due to its high granularity and good spatial resolution, about 10 μm for a single hit, the pixel detector is used for track reconstruction, pileup mitigation, and b-quark tagging in many physics analyses. Being the innermost sub-detector of CMS it receives the most radiation damage, and therefore needs to be replaced most often. For the phase 1 upgrade an additional disk in the forward region and increased buffer space in the readout chip will improve the pixel performance by increasing efficiency and reducing fake rates. The University of Nebraska-Lincoln is one of the two sites where modules are being assembled. This talk features the steps of the assembly process as well as challenges encountered and overcome during production of over 500 modules. The CMS Collaboration.

  20. A Triple-GEM Detector with Pixel Readout for High-Rate Beam Tracking in COMPASS

    NASA Astrophysics Data System (ADS)

    Nagel, T.; Austregesilo, A.; Haas, F.; Ketzer, B.; Konorov, I.; Krämer, M.; Mann, A.; Paul, S.

    2008-06-01

    For its physics program with a high-intensity hadron beam of 2 · 107 particles/s, the COMPASS experiment at CERN requires tracking of charged particles scattered by very small angles with respect to the incident beam direction. While good resolution in time and space is mandatory, the challenge is imposed by the high beam intensity, requiring radiation-hard detectors which add very little material to the beam path in order to minimise secondary interactions. To this end, a set of triple-GEM detectors with pixel readout in the beam region and 2-D strip readout in the periphery is currently being built. The pixel size has been chosen to be 1×1 mm2, which constitutes a compromise between the spatial resolution achievable and the number of readout channels. Surrounding the pixel area, a 2-D strip readout with a pitch of 400 μm has been realised on the same printed circuit foil. In total an active area of 10 × 10 cm2 is covered using 2048 readout channels. Analogue readout by the APV25 ASIC has been chosen in order to profit from amplitude measurements which help to improve the spatial resolution by clustering neighbouring hit strips or pixels. A detector prototype has been tested successfully in the 5 · 107 particles/s COMPASS muon beam, as well as in a focused hadron beam. The design of the detector and first results concerning its performance as a beam tracker will be presented.

  1. Evaluation of a single-pixel one-transistor active pixel sensor for fingerprint imaging

    NASA Astrophysics Data System (ADS)

    Xu, Man; Ou, Hai; Chen, Jun; Wang, Kai

    2015-08-01

    Since it first appeared in iPhone 5S in 2013, fingerprint identification (ID) has rapidly gained popularity among consumers. Current fingerprint-enabled smartphones unanimously consists of a discrete sensor to perform fingerprint ID. This architecture not only incurs higher material and manufacturing cost, but also provides only static identification and limited authentication. Hence as the demand for a thinner, lighter, and more secure handset grows, we propose a novel pixel architecture that is a photosensitive device embedded in a display pixel and detects the reflected light from the finger touch for high resolution, high fidelity and dynamic biometrics. To this purpose, an amorphous silicon (a-Si:H) dual-gate photo TFT working in both fingerprint-imaging mode and display-driving mode will be developed.

  2. Dimensional regularization in configuration space

    SciTech Connect

    Bollini, C.G. |; Giambiagi, J.J.

    1996-05-01

    Dimensional regularization is introduced in configuration space by Fourier transforming in {nu} dimensions the perturbative momentum space Green functions. For this transformation, the Bochner theorem is used; no extra parameters, such as those of Feynman or Bogoliubov and Shirkov, are needed for convolutions. The regularized causal functions in {ital x} space have {nu}-dependent moderated singularities at the origin. They can be multiplied together and Fourier transformed (Bochner) without divergence problems. The usual ultraviolet divergences appear as poles of the resultant analytic functions of {nu}. Several examples are discussed. {copyright} {ital 1996 The American Physical Society.}

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

    NASA Astrophysics Data System (ADS)

    Kriss, Michael A.

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

  4. Design and characterization of high precision in-pixel discriminators for rolling shutter CMOS pixel sensors with full CMOS capability

    NASA Astrophysics Data System (ADS)

    Fu, Y.; Hu-Guo, C.; Dorokhov, A.; Pham, H.; Hu, Y.

    2013-07-01

    In order to exploit the ability to integrate a charge collecting electrode with analog and digital processing circuitry down to the pixel level, a new type of CMOS pixel sensors with full CMOS capability is presented in this paper. The pixel array is read out based on a column-parallel read-out architecture, where each pixel incorporates a diode, a preamplifier with a double sampling circuitry and a discriminator to completely eliminate analog read-out bottlenecks. The sensor featuring a pixel array of 8 rows and 32 columns with a pixel pitch of 80 μm×16 μm was fabricated in a 0.18 μm CMOS process. The behavior of each pixel-level discriminator isolated from the diode and the preamplifier was studied. The experimental results indicate that all in-pixel discriminators which are fully operational can provide significant improvements in the read-out speed and the power consumption of CMOS pixel sensors.

  5. High-dynamic-range pixel architectures for diagnostic medical imaging

    NASA Astrophysics Data System (ADS)

    Karim, Karim S.; Yin, Sherman; Nathan, Arokia; Rowlands, John A.

    2004-05-01

    One approach to increase pixel signal-to-noise ratio (SNR) in low noise digital fluoroscopy is to employ in-situ pixel amplification via current-mediated active pixel sensors (C-APS). Experiments reveal a reduction in readout noise and indicate that an a-Si C-APS, coupled together with an established X-ray detection technology such as amorphous selenium (a-Se), can meet the stringent requirements (of < 1000 noise electrons) for digital X-ray fluoroscopy. A challenge with the C-APS circuit is the presence of a small-signal input linearity constraint. While using such a pixel amplifier for real-time fluoroscopy (where the exposure level is small) is feasible, the voltage change at the amplifier input is much higher in chest radiography or mammography due to the larger X-ray exposure levels. The larger input voltage causes the C-APS output to be non-linear thus reducing the pixel dynamic range. In addition, the resulting larger pixel output current causes the external column amplifier to saturate further reducing the pixel dynamic range. In this research, we investigate two alternate amplified pixel architectures that exhibit higher dynamic range. The test pixels are designed and simulated using an a-Si TFT model implemented in Verilog-A and results indicate a linear performance, high dynamic range, and a programmable circuit gain via choice of supply voltage and sampling time. These high dynamic range pixel architectures have the potential to enable a large area, active matrix flat panel imager (AMFPI) to switch instantly between low exposure, fluoroscopic imaging and higher exposure radiographic imaging modes. Lastly, the high dynamic range pixel circuits are suitable for integration with on-panel multiplexers for both gate and data lines, which can further reduce circuit complexity.

  6. Two projects in theoretical neuroscience: A convolution-based metric for neural membrane potentials and a combinatorial connectionist semantic network method

    NASA Astrophysics Data System (ADS)

    Evans, Garrett Nolan

    In this work, I present two projects that both contribute to the aim of discovering how intelligence manifests in the brain. The first project is a method for analyzing recorded neural signals, which takes the form of a convolution-based metric on neural membrane potential recordings. Relying only on integral and algebraic operations, the metric compares the timing and number of spikes within recordings as well as the recordings' subthreshold features: summarizing differences in these with a single "distance" between the recordings. Like van Rossum's (2001) metric for spike trains, the metric is based on a convolution operation that it performs on the input data. The kernel used for the convolution is carefully chosen such that it produces a desirable frequency space response and, unlike van Rossum's kernel, causes the metric to be first order both in differences between nearby spike times and in differences between same-time membrane potential values: an important trait. The second project is a combinatorial syntax method for connectionist semantic network encoding. Combinatorial syntax has been a point on which those who support a symbol-processing view of intelligent processing and those who favor a connectionist view have had difficulty seeing eye-to-eye. Symbol-processing theorists have persuasively argued that combinatorial syntax is necessary for certain intelligent mental operations, such as reasoning by analogy. Connectionists have focused on the versatility and adaptability offered by self-organizing networks of simple processing units. With this project, I show that there is a way to reconcile the two perspectives and to ascribe a combinatorial syntax to a connectionist network. The critical principle is to interpret nodes, or units, in the connectionist network as bound integrations of the interpretations for nodes that they share links with. Nodes need not correspond exactly to neurons and may correspond instead to distributed sets, or assemblies, of

  7. Accelerating Convolutional Sparse Coding for Curvilinear Structures Segmentation by Refining SCIRD-TS Filter Banks.

    PubMed

    Annunziata, Roberto; Trucco, Emanuele

    2016-11-01

    Deep learning has shown great potential for curvilinear structure (e.g., retinal blood vessels and neurites) segmentation as demonstrated by a recent auto-context regression architecture based on filter banks learned by convolutional sparse coding. However, learning such filter banks is very time-consuming, thus limiting the amount of filters employed and the adaptation to other data sets (i.e., slow re-training). We address this limitation by proposing a novel acceleration strategy to speed-up convolutional sparse coding filter learning for curvilinear structure segmentation. Our approach is based on a novel initialisation strategy (warm start), and therefore it is different from recent methods improving the optimisation itself. Our warm-start strategy is based on carefully designed hand-crafted filters (SCIRD-TS), modelling appearance properties of curvilinear structures which are then refined by convolutional sparse coding. Experiments on four diverse data sets, including retinal blood vessels and neurites, suggest that the proposed method reduces significantly the time taken to learn convolutional filter banks (i.e., up to -82%) compared to conventional initialisation strategies. Remarkably, this speed-up does not worsen performance; in fact, filters learned with the proposed strategy often achieve a much lower reconstruction error and match or exceed the segmentation performance of random and DCT-based initialisation, when used as input to a random forest classifier.

  8. The venom apparatus in stenogastrine wasps: subcellular features of the convoluted gland.

    PubMed

    Petrocelli, Iacopo; Turillazzi, Stefano; Delfino, Giovanni

    2014-09-01

    In the wasp venom apparatus, the convoluted gland is the tract of the thin secretory unit, i.e. filament, contained in the muscular reservoir. Previous transmission electron microscope investigation on Stenogastrinae disclosed that the free filaments consist of distal and proximal tracts, from/to the venom reservoir, characterized by class 3 and 2 gland patterns, respectively. This study aims to extend the ultrastructural analysis to the convoluted tract, in order to provide a thorough, subcellular representation of the venom gland in these Asian wasps. Our findings showed that the convoluted gland is a continuation of the proximal tract, with secretory cells provided with a peculiar apical invagination, the extracellular cavity, collecting their products. This compartment holds a simple end-apparatus lined by large and ramified microvilli that contribute to the processing of the secretory product. A comparison between previous and present findings reveals a noticeable regionalization of the stenogastrine venom filaments and suggests that the secretory product acquires its ultimate composition in the convoluted tract.

  9. Digital Tomosynthesis System Geometry Analysis Using Convolution-Based Blur-and-Add (BAA) Model.

    PubMed

    Wu, Meng; Yoon, Sungwon; Solomon, Edward G; Star-Lack, Josh; Pelc, Norbert; Fahrig, Rebecca

    2016-01-01

    Digital tomosynthesis is a three-dimensional imaging technique with a lower radiation dose than computed tomography (CT). Due to the missing data in tomosynthesis systems, out-of-plane structures in the depth direction cannot be completely removed by the reconstruction algorithms. In this work, we analyzed the impulse responses of common tomosynthesis systems on a plane-to-plane basis and proposed a fast and accurate convolution-based blur-and-add (BAA) model to simulate the backprojected images. In addition, the analysis formalism describing the impulse response of out-of-plane structures can be generalized to both rotating and parallel gantries. We implemented a ray tracing forward projection and backprojection (ray-based model) algorithm and the convolution-based BAA model to simulate the shift-and-add (backproject) tomosynthesis reconstructions. The convolution-based BAA model with proper geometry distortion correction provides reasonably accurate estimates of the tomosynthesis reconstruction. A numerical comparison indicates that the simulated images using the two models differ by less than 6% in terms of the root-mean-squared error. This convolution-based BAA model can be used in efficient system geometry analysis, reconstruction algorithm design, out-of-plane artifacts suppression, and CT-tomosynthesis registration.

  10. The VLSI design of error-trellis syndrome decoding for convolutional codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Jensen, J. M.; Truong, T. K.; Hsu, I. S.

    1985-01-01

    A recursive algorithm using the error-trellis decoding technique is developed to decode convolutional codes (CCs). An example, illustrating the very large scale integration (VLSI) architecture of such a decode, is given for a dual-K CC. It is demonstrated that such a decoder can be realized readily on a single chip with metal-nitride-oxide-semiconductor technology.

  11. The VLSI design of an error-trellis syndrome decoder for certain convolutional codes

    NASA Technical Reports Server (NTRS)

    Reed, I. S.; Jensen, J. M.; Hsu, I.-S.; Truong, T. K.

    1986-01-01

    A recursive algorithm using the error-trellis decoding technique is developed to decode convolutional codes (CCs). An example, illustrating the very large scale integration (VLSI) architecture of such a decode, is given for a dual-K CC. It is demonstrated that such a decoder can be realized readily on a single chip with metal-nitride-oxide-semiconductor technology.

  12. Linear diffusion-wave channel routing using a discrete Hayami convolution method

    NASA Astrophysics Data System (ADS)

    Wang, Li; Wu, Joan Q.; Elliot, William J.; Fiedler, Fritz R.; Lapin, Sergey

    2014-02-01

    The convolution of an input with a response function has been widely used in hydrology as a means to solve various problems analytically. Due to the high computation demand in solving the functions using numerical integration, it is often advantageous to use the discrete convolution instead of the integration of the continuous functions. This approach greatly reduces the amount of the computational work; however, it increases the possibility for mass balance errors. In this study, we analyzed the characteristics of the kernel function for the Hayami convolution solution to the linear diffusion-wave channel routing with distributed lateral inflow. We propose two ways of selection of the discrete kernel function values: using the exact point values or using the center-averaged values. Through a hypothetical example and the applications to Asotin Creek, WA and the Clearwater River, ID, we showed that when the point kernel function values were used in the discrete Hayami convolution (DHC) solution, the mass balance error of channel routing is dependent on the number of time steps on the rising limb of the Hayami kernel function. The mass balance error is negligible when there are more than 1.8 time steps on the rising limb of the kernel function. The fewer time steps on the rising limb, the greater risk of high mass balance errors. When the average kernel function values are used for the DHC solution, however, the mass balance is always maintained, since the integration of the discrete kernel function is always unity.

  13. Convolutional FEC design considerations for data transmission over PSK satellite channels

    NASA Astrophysics Data System (ADS)

    Garrison, G. J.; Wong, V. C.

    Simulation results are provided for rate R = 1/2 convolutional error correcting codes suited to data transmission over BPSK, gray coded QPSK, and OQPSK channels. The burst generation mechanism resulting from differential encoding/decoding is analyzed in terms of the impairment to code performance and offsetting internal/external interleaving techniques are described.

  14. Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction.

    PubMed

    Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

    2017-04-10

    This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.

  15. 3D reconstructions with pixel-based images are made possible by digitally clearing plant and animal tissue

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Reconstruction of 3D images from a series of 2D images has been restricted by the limited capacity to decrease the opacity of surrounding tissue. Commercial software that allows color-keying and manipulation of 2D images in true 3D space allowed us to produce 3D reconstructions from pixel based imag...

  16. Novel integrated CMOS pixel structures for vertex detectors

    SciTech Connect

    Kleinfelder, Stuart; Bieser, Fred; Chen, Yandong; Gareus, Robin; Matis, Howard S.; Oldenburg, Markus; Retiere, Fabrice; Ritter, Hans Georg; Wieman, Howard H.; Yamamoto, Eugene

    2003-10-29

    Novel CMOS active pixel structures for vertex detector applications have been designed and tested. The overriding goal of this work is to increase the signal to noise ratio of the sensors and readout circuits. A large-area native epitaxial silicon photogate was designed with the aim of increasing the charge collected per struck pixel and to reduce charge diffusion to neighboring pixels. The photogate then transfers the charge to a low capacitance readout node to maintain a high charge to voltage conversion gain. Two techniques for noise reduction are also presented. The first is a per-pixel kT/C noise reduction circuit that produces results similar to traditional correlated double sampling (CDS). It has the advantage of requiring only one read, as compared to two for CDS, and no external storage or subtraction is needed. The technique reduced input-referred temporal noise by a factor of 2.5, to 12.8 e{sup -}. Finally, a column-level active reset technique is explored that suppresses kT/C noise during pixel reset. In tests, noise was reduced by a factor of 7.6 times, to an estimated 5.1 e{sup -} input-referred noise. The technique also dramatically reduces fixed pattern (pedestal) noise, by up to a factor of 21 in our tests. The latter feature may possibly reduce pixel-by-pixel pedestal differences to levels low enough to permit sparse data scan without per-pixel offset corrections.

  17. Method for hyperspectral imagery exploitation and pixel spectral unmixing

    NASA Technical Reports Server (NTRS)

    Lin, Ching-Fang (Inventor)

    2003-01-01

    An efficiently hybrid approach to exploit hyperspectral imagery and unmix spectral pixels. This hybrid approach uses a genetic algorithm to solve the abundance vector for the first pixel of a hyperspectral image cube. This abundance vector is used as initial state in a robust filter to derive the abundance estimate for the next pixel. By using Kalman filter, the abundance estimate for a pixel can be obtained in one iteration procedure which is much fast than genetic algorithm. The output of the robust filter is fed to genetic algorithm again to derive accurate abundance estimate for the current pixel. The using of robust filter solution as starting point of the genetic algorithm speeds up the evolution of the genetic algorithm. After obtaining the accurate abundance estimate, the procedure goes to next pixel, and uses the output of genetic algorithm as the previous state estimate to derive abundance estimate for this pixel using robust filter. And again use the genetic algorithm to derive accurate abundance estimate efficiently based on the robust filter solution. This iteration continues until pixels in a hyperspectral image cube end.

  18. Hybrid Pixel Detectors for gamma/X-ray imaging

    NASA Astrophysics Data System (ADS)

    Hatzistratis, D.; Theodoratos, G.; Zografos, V.; Kazas, I.; Loukas, D.; Lambropoulos, C. P.

    2015-09-01

    Hybrid pixel detectors are made by direct converting high-Z semi-insulating single crystalline material coupled to complementary-metal-oxide semiconductor (CMOS) readout electronics. They are attractive because direct conversion exterminates all the problems of spatial localization related to light diffusion, energy resolution, is far superior from the combination of scintillation crystals and photomultipliers and lithography can be used to pattern electrodes with very fine pitch. We are developing 2-D pixel CMOS ASICs, connect them to pixilated CdTe crystals with the flip chip and bump bonding method and characterize the hybrids. We have designed a series of circuits, whose latest member consists of a 50×25 pixel array with 400um pitch and an embedded controller. In every pixel a full spectroscopic channel with time tagging information has been implemented. The detectors are targeting Compton scatter imaging and they can be used for coded aperture imaging too. Hybridization using CMOS can overcome the limit put on pixel circuit complexity by the use of thin film transistors (TFT) in large flat panels. Hybrid active pixel sensors are used in dental imaging and other applications (e.g. industrial CT etc.). Thus X-ray imaging can benefit from the work done on dynamic range enhancement methods developed initially for visible and infrared CMOS pixel sensors. A 2-D CMOS ASIC with 100um pixel pitch to demonstrate the feasibility of such methods in the context of X-ray imaging has been designed.

  19. CMOS Active-Pixel Image Sensor With Simple Floating Gates

    NASA Technical Reports Server (NTRS)

    Fossum, Eric R.; Nakamura, Junichi; Kemeny, Sabrina E.

    1996-01-01

    Experimental complementary metal-oxide/semiconductor (CMOS) active-pixel image sensor integrated circuit features simple floating-gate structure, with metal-oxide/semiconductor field-effect transistor (MOSFET) as active circuit element in each pixel. Provides flexibility of readout modes, no kTC noise, and relatively simple structure suitable for high-density arrays. Features desirable for "smart sensor" applications.

  20. Singlet mega-pixel resolution lens

    NASA Astrophysics Data System (ADS)

    Lin, Chen-Hung; Lin, Hoang Yan; Chang, Horng

    2008-03-01

    There always exist some new challenges for lens designers to keep their old-line technology update. To minimize lens volume is one of the most notified examples. In this paper we designed a single thick lens, constructed by using one oblique (reflective) surface, apart from two conventional refractive surfaces, to bend the optical path of the optical system to achieve this goal. Detail design procedure, including system layout and lens performance diagrams, will be presented. Following the first order layout, we applied aspherical form to the two refractive surfaces in order to correct the spherical aberration up to an acceptable condition. Then, the reduced aberrations such as coma, astigmatism, field curvature and distortion can easily be corrected with some calculations related to spherical aberration as shown in the publication of H. H. Hopkins (1950). Plastic material is used in the design, because the aspherical surfaces can then be manufactured in a more cost effective way. The final specification of the design is: EFL is 4.6 mm, the F number is 2.8, the over all thickness of lens is 3.6 mm, its MTF is 0.3 at 227 lp/mm in center field and chief ray angle is less than 15 degrees. Lens data as well as optical performance curves are also presented in the paper. In conclusion we have successfully finished a mega-pixel resolution lens design and its overall thickness is compatible with the state of the art.

  1. Hyperspectral Anomaly Detection by Graph Pixel Selection.

    PubMed

    Yuan, Yuan; Ma, Dandan; Wang, Qi

    2016-12-01

    Hyperspectral anomaly detection (AD) is an important problem in remote sensing field. It can make full use of the spectral differences to discover certain potential interesting regions without any target priors. Traditional Mahalanobis-distance-based anomaly detectors assume the background spectrum distribution conforms to a Gaussian distribution. However, this and other similar distributions may not be satisfied for the real hyperspectral images. Moreover, the background statistics are susceptible to contamination of anomaly targets which will lead to a high false-positive rate. To address these intrinsic problems, this paper proposes a novel AD method based on the graph theory. We first construct a vertex- and edge-weighted graph and then utilize a pixel selection process to locate the anomaly targets. Two contributions are claimed in this paper: 1) no background distributions are required which makes the method more adaptive and 2) both the vertex and edge weights are considered which enables a more accurate detection performance and better robustness to noise. Intensive experiments on the simulated and real hyperspectral images demonstrate that the proposed method outperforms other benchmark competitors. In addition, the robustness of the proposed method has been validated by using various window sizes. This experimental result also demonstrates the valuable characteristic of less computational complexity and less parameter tuning for real applications.

  2. Detector apparatus having a hybrid pixel-waveform readout system

    DOEpatents

    Meng, Ling-Jian

    2014-10-21

    A gamma ray detector apparatus comprises a solid state detector that includes a plurality of anode pixels and at least one cathode. The solid state detector is configured for receiving gamma rays during an interaction and inducing a signal in an anode pixel and in a cathode. An anode pixel readout circuit is coupled to the plurality of anode pixels and is configured to read out and process the induced signal in the anode pixel and provide triggering and addressing information. A waveform sampling circuit is coupled to the at least one cathode and configured to read out and process the induced signal in the cathode and determine energy of the interaction, timing of the interaction, and depth of interaction.

  3. Readout of TPC Tracking Chambers with GEMs and Pixel Chip

    SciTech Connect

    Kadyk, John; Kim, T.; Freytsis, M.; Button-Shafer, J.; Kadyk, J.; Vahsen, S.E.; Wenzel, W.A.

    2007-12-21

    Two layers of GEMs and the ATLAS Pixel Chip, FEI3, have been combined and tested as a prototype for Time Projection Chamber (TPC) readout at the International Linear Collider (ILC). The double-layer GEM system amplifies charge with gain sufficient to detect all track ionization. The suitability of three gas mixtures for this application was investigated, and gain measurements are presented. A large sample of cosmic ray tracks was reconstructed in 3D by using the simultaneous timing and 2D spatial information from the pixel chip. The chip provides pixel charge measurement as well as timing. These results demonstrate that a double GEM and pixel combination, with a suitably modified pixel ASIC, could meet the stringent readout requirements of the ILC.

  4. Status of the CMS Phase I pixel detector upgrade

    NASA Astrophysics Data System (ADS)

    Spannagel, S.

    2016-09-01

    A new pixel detector for the CMS experiment is being built, owing to the instantaneous luminosities anticipated for the Phase I Upgrade of the LHC. The new CMS pixel detector provides four-hit tracking while featuring a significantly reduced material budget as well as new cooling and powering schemes. A new front-end readout chip mitigates buffering and bandwidth limitations, and comprises a low-threshold comparator. These improvements allow the new pixel detector to sustain and improve the efficiency of the current pixel tracker at the increased requirements imposed by high luminosities and pile-up. This contribution gives an overview of the design of the upgraded pixel detector and the status of the upgrade project, and presents test beam performance measurements of the production read-out chip.

  5. Attenuating Stereo Pixel-Locking via Affine Window Adaptation

    NASA Technical Reports Server (NTRS)

    Stein, Andrew N.; Huertas, Andres; Matthies, Larry H.

    2006-01-01

    For real-time stereo vision systems, the standard method for estimating sub-pixel stereo disparity given an initial integer disparity map involves fitting parabolas to a matching cost function aggregated over rectangular windows. This results in a phenomenon known as 'pixel-locking,' which produces artificially-peaked histograms of sub-pixel disparity. These peaks correspond to the introduction of erroneous ripples or waves in the 3D reconstruction of truly Rat surfaces. Since stereo vision is a common input modality for autonomous vehicles, these inaccuracies can pose a problem for safe, reliable navigation. This paper proposes a new method for sub-pixel stereo disparity estimation, based on ideas from Lucas-Kanade tracking and optical flow, which substantially reduces the pixel-locking effect. In addition, it has the ability to correct much larger initial disparity errors than previous approaches and is more general as it applies not only to the ground plane.

  6. Using an Active Pixel Sensor In A Vertex Detector

    SciTech Connect

    Matis, Howard S.; Bieser, Fred; Chen, Yandong; Gareus, Robin; Kleinfelder, Stuart; Oldenburg, Markus; Retiere, Fabrice; Ritter, HansGeorg; Wieman, Howard H.; Wurzel, Samuel E.; Yamamoto, Eugene

    2004-04-22

    Research has shown that Active Pixel CMOS sensors can detect charged particles. We have been studying whether this process can be used in a collider environment. In particular, we studied the effect of radiation with 55 MeV protons. These results show that a fluence of about 2 x 10{sup 12} protons/cm{sup 2} reduces the signal by a factor of two while the noise increases by 25%. A measurement 6 months after exposure shows that the silicon lattice naturally repairs itself. Heating the silicon to 100 C reduced the shot noise and increased the collected charge. CMOS sensors have a reduced signal to noise ratio per pixel because charge diffuses to neighboring pixels. We have constructed a photogate to see if this structure can collect more charge per pixel. Results show that a photogate does collect charge in fewer pixels, but it takes about 15 ms to collect all of the electrons produced by a pulse of light.

  7. Research on ionospheric tomography based on variable pixel height

    NASA Astrophysics Data System (ADS)

    Zheng, Dunyong; Li, Peiqing; He, Jie; Hu, Wusheng; Li, Chaokui

    2016-05-01

    A novel ionospheric tomography technique based on variable pixel height was developed for the tomographic reconstruction of the ionospheric electron density distribution. The method considers the height of each pixel as an unknown variable, which is retrieved during the inversion process together with the electron density values. In contrast to conventional computerized ionospheric tomography (CIT), which parameterizes the model with a fixed pixel height, the variable-pixel-height computerized ionospheric tomography (VHCIT) model applies a disturbance to the height of each pixel. In comparison with conventional CIT models, the VHCIT technique achieved superior results in a numerical simulation. A careful validation of the reliability and superiority of VHCIT was performed. According to the results of the statistical analysis of the average root mean square errors, the proposed model offers an improvement by 15% compared with conventional CIT models.

  8. Field-portable pixel super-resolution colour microscope.

    PubMed

    Greenbaum, Alon; Akbari, Najva; Feizi, Alborz; Luo, Wei; Ozcan, Aydogan

    2013-01-01

    Based on partially-coherent digital in-line holography, we report a field-portable microscope that can render lensfree colour images over a wide field-of-view of e.g., >20 mm(2). This computational holographic microscope weighs less than 145 grams with dimensions smaller than 17×6×5 cm, making it especially suitable for field settings and point-of-care use. In this lensfree imaging design, we merged a colorization algorithm with a source shifting based multi-height pixel super-resolution technique to mitigate 'rainbow' like colour artefacts that are typical in holographic imaging. This image processing scheme is based on transforming the colour components of an RGB image into YUV colour space, which separates colour information from brightness component of an image. The resolution of our super-resolution colour microscope was characterized using a USAF test chart to confirm sub-micron spatial resolution, even for reconstructions that employ multi-height phase recovery to handle dense and connected objects. To further demonstrate the performance of this colour microscope Papanicolaou (Pap) smears were also successfully imaged. This field-portable and wide-field computational colour microscope could be useful for tele-medicine applications in resource poor settings.

  9. Field-Portable Pixel Super-Resolution Colour Microscope

    PubMed Central

    Greenbaum, Alon; Akbari, Najva; Feizi, Alborz; Luo, Wei; Ozcan, Aydogan

    2013-01-01

    Based on partially-coherent digital in-line holography, we report a field-portable microscope that can render lensfree colour images over a wide field-of-view of e.g., >20 mm2. This computational holographic microscope weighs less than 145 grams with dimensions smaller than 17×6×5 cm, making it especially suitable for field settings and point-of-care use. In this lensfree imaging design, we merged a colorization algorithm with a source shifting based multi-height pixel super-resolution technique to mitigate ‘rainbow’ like colour artefacts that are typical in holographic imaging. This image processing scheme is based on transforming the colour components of an RGB image into YUV colour space, which separates colour information from brightness component of an image. The resolution of our super-resolution colour microscope was characterized using a USAF test chart to confirm sub-micron spatial resolution, even for reconstructions that employ multi-height phase recovery to handle dense and connected objects. To further demonstrate the performance of this colour microscope Papanicolaou (Pap) smears were also successfully imaged. This field-portable and wide-field computational colour microscope could be useful for tele-medicine applications in resource poor settings. PMID:24086742

  10. A 400 KHz line rate 2048-pixel stitched SWIR linear array

    NASA Astrophysics Data System (ADS)

    Anchlia, Ankur; Vinella, Rosa M.; Gielen, Daphne; Wouters, Kristof; Vervenne, Vincent; Hooylaerts, Peter; Deroo, Pieter; Ruythooren, Wouter; De Gaspari, Danny; Das, Jo; Merken, Patrick

    2016-05-01

    Xenics has developed a family of stitched SWIR long linear arrays that operate up to 400 KHz of line rate. These arrays serve medical and industrial applications that require high line rates as well as space applications that require long linear arrays. The arrays are based on a modular ROIC design concept: modules of 512 pixels are stitched during fabrication to achieve 512, 1024 and 2048 pixel arrays. Each 512-pixel module has its own on-chip digital sequencer, analog readout chain and 4 output buffers. This modular concept enables a long array to run at a high line rates irrespective of the array length, which limits the line rate in a traditional linear array. The ROIC is flip-chipped with InGaAs detector arrays. The FPA has a pixel pitch of 12.5μm and has two pixel flavors: square (12.5μm) and rectangular (250μm). The frontend circuit is based on Capacitive Trans-impedance Amplifier (CTIA) to attain stable detector bias, and good linearity and signal integrity, especially at high speeds. The CTIA has an input auto-zero mechanism that allows to have low detector bias (<20mV). An on-chip Correlated Double Sample (CDS) facilitates removal of CTIA KTC and 1/f noise, and other offsets, achieving low noise performance. There are five gain modes in the FPA giving the full well range from 85Ke- to 40Me-. The measured input referred noise is 35e-rms in the highest gain mode. The FPA operates in Integrate While Read mode and, at a master clock rate of 60MHz and a minimum integration time of 1.4μs, achieves the highest line rate of 400 KHz. In this paper, design details and measurements results are presented in order to demonstrate the array performance.

  11. The Gaussian streaming model and convolution Lagrangian effective field theory

    NASA Astrophysics Data System (ADS)

    Vlah, Zvonimir; Castorina, Emanuele; White, Martin

    2016-12-01

    We update the ingredients of the Gaussian streaming model (GSM) for the redshift-space clustering of biased tracers using the techniques of Lagrangian perturbation theory, effective field theory (EFT) and a generalized Lagrangian bias expansion. After relating the GSM to the cumulant expansion, we present new results for the real-space correlation function, mean pairwise velocity and pairwise velocity dispersion including counter terms from EFT and bias terms through third order in the linear density, its leading derivatives and its shear up to second order. We discuss the connection to the Gaussian peaks formalism. We compare the ingredients of the GSM to a suite of large N-body simulations, and show the performance of the theory on the low order multipoles of the redshift-space correlation function and power spectrum. We highlight the importance of a general biasing scheme, which we find to be as important as higher-order corrections due to non-linear evolution for the halos we consider on the scales of interest to us.

  12. Filling schemes of silver dots inkjet-printed on pixelated nanostructured surfaces.

    PubMed

    Alan, Sheida; Jiang, Hao; Shahbazbegian, Haleh; Patel, Jasbir N; Kaminska, Bozena

    2017-03-01

    Recently, our group demonstrated an inkjet-based technique to enable high-throughput, versatile and full-colour printing of structural colours on generic pixelated nanostructures, termed as molded ink on nanostructured surfaces. The printed colours are controlled by the area of printed silver on the pixelated red, green and blue polymer nanostructure arrays. This paper investigates the behaviour of jetted silver ink droplets on nanostructured surfaces and the microscale dot patterns implemented during printing process, for achieving accurate and consistent colours in the printed images. The surface wettability and the schemes of filling silver dots inside the subpixels are crucial to the quality of printed images. Several related concepts and definitions are introduced, such as filling ratio, full dots per subpixel (DPSP), number of printable colours, colour leaking and dot merging. In our experiments, we first chemically modified the surface to control the wettability and dot size. From each type of modified surface, various filling schemes were experimented and the printed results were evaluated with comprehensive considerations on the number of printable colours and the negative effects of colour leaking and dot merging. Rational selection of the best filling scheme resulted in a 2-line filling scheme using 20 μm dot spacing and line spacing capable of printing 9261 different colours with 121 pixel per inch display resolution, on low-wettability surface. This study is of vital importance for scaling up the printing technique in industrial applications and provides meaningful insights for inkjet-printing on nanostructures.

  13. Filling schemes of silver dots inkjet-printed on pixelated nanostructured surfaces

    NASA Astrophysics Data System (ADS)

    Alan, Sheida; Jiang, Hao; Shahbazbegian, Haleh; Patel, Jasbir N.; Kaminska, Bozena

    2017-03-01

    Recently, our group demonstrated an inkjet-based technique to enable high-throughput, versatile and full-colour printing of structural colours on generic pixelated nanostructures, termed as molded ink on nanostructured surfaces. The printed colours are controlled by the area of printed silver on the pixelated red, green and blue polymer nanostructure arrays. This paper investigates the behaviour of jetted silver ink droplets on nanostructured surfaces and the microscale dot patterns implemented during printing process, for achieving accurate and consistent colours in the printed images. The surface wettability and the schemes of filling silver dots inside the subpixels are crucial to the quality of printed images. Several related concepts and definitions are introduced, such as filling ratio, full dots per subpixel (DPSP), number of printable colours, colour leaking and dot merging. In our experiments, we first chemically modified the surface to control the wettability and dot size. From each type of modified surface, various filling schemes were experimented and the printed results were evaluated with comprehensive considerations on the number of printable colours and the negative effects of colour leaking and dot merging. Rational selection of the best filling scheme resulted in a 2-line filling scheme using 20 μm dot spacing and line spacing capable of printing 9261 different colours with 121 pixel per inch display resolution, on low-wettability surface. This study is of vital importance for scaling up the printing technique in industrial applications and provides meaningful insights for inkjet-printing on nanostructures.

  14. Generalized approach to inverse problems in tomography: Image reconstruction for spatially variant systems using natural pixels

    SciTech Connect

    Baker, J.R.; Budinger, T.F.; Huesman, R.H.

    1992-10-01

    A major limitation in tomographic inverse problems is inadequate computation speed, which frequently impedes the application of engineering ideas and principles in medical science more than in the physical and engineering sciences. Medical problems are computationally taxing because a minimum description of the system often involves 5 dimensions (3 space, 1 energy, 1 time), with the range of each space coordinate requiring up to 512 samples. The computational tasks for this problem can be simply expressed by posing the problem as one in which the tomograph system response function is spatially invariant, and the noise is additive and Gaussian. Under these assumptions, a number of reconstruction methods have been implemented with generally satisfactory results for general medical imaging purposes. However, if the system response function of the tomograph is assumed more realistically to be spatially variant and the noise to be Poisson, the computational problem becomes much more difficult. Some of the algorithms being studied to compensate for position dependent resolution and statistical fluctuations in the data acquisition process, when expressed in canonical form, are not practical for clinical applications because the number of computations necessary exceeds the capabilities of high performance computer systems currently available. Reconstruction methods based on natural pixels, specifically orthonormal natural pixels, preserve symmetries in the data acquisition process. Fast implementations of orthonormal natural pixel algorithms can achieve orders of magnitude speedup relative to general implementations. Thus, specialized thought in algorithm development can lead to more significant increases in performance than can be achieved through hardware improvements alone.

  15. Recent results of the ATLAS upgrade planar pixel sensors R&D project

    NASA Astrophysics Data System (ADS)

    Weigell, Philipp

    2013-12-01

    To extend the physics reach of the LHC experiments, several upgrades to the accelerator complex are planned, culminating in the HL-LHC, which eventually leads to an increase of the peak luminosity by a factor of five to ten compared to the LHC design value. To cope with the higher occupancy and radiation damage also the LHC experiments will be upgraded. The ATLAS Planar Pixel Sensor R&D Project is an international collaboration of 17 institutions and more than 80 scientists, exploring the feasibility of employing planar pixel sensors for this scenario. Depending on the radius, different pixel concepts are investigated using laboratory and beam test measurements. At small radii the extreme radiation environment and strong space constraints are addressed with very thin pixel sensors active thickness in the range of (75-150) μm, and the development of slim as well as active edges. At larger radii the main challenge is the cost reduction to allow for instrumenting the large area of (7-10) m2. To reach this goal the pixel productions are being transferred to 6 in production lines and more cost-efficient and industrialised interconnection techniques are investigated. Additionally, the n-in-p technology is employed, which requires less production steps since it relies on a single-sided process. An overview of the recent accomplishments obtained within the ATLAS Planar Pixel Sensor R&D Project is given. The performance in terms of charge collection and tracking efficiency, obtained with radioactive sources in the laboratory and at beam tests, is presented for devices built from sensors of different vendors connected to either the present ATLAS read-out chip FE-I3 or the new Insertable B-Layer read-out chip FE-I4. The devices, with a thickness varying between 75 μm and 300 μm, were irradiated to several fluences up to 2×1016 neq/cm2. Finally, the different approaches followed inside the collaboration to achieve slim or active edges for planar pixel sensors are presented.

  16. Pixellated Cd(Zn)Te high-energy X-ray instrument

    NASA Astrophysics Data System (ADS)

    Seller, P.; Bell, S.; Cernik, R. J.; Christodoulou, C.; Egan, C. K.; Gaskin, J. A.; Jacques, S.; Pani, S.; Ramsey, B. D.; Reid, C.; Sellin, P. J.; Scuffham, J. W.; Speller, R. D.; Wilson, M. D.; Veale, M. C.

    2011-12-01

    We have developed a pixellated high energy X-ray detector instrument to be used in a variety of imaging applications. The instrument consists of either a Cadmium Zinc Telluride or Cadmium Telluride (Cd(Zn)Te) detector bump-bonded to a large area ASIC and packaged with a high performance data acquisition system. The 80 by 80 pixels each of 250 μm by 250 μm give better than 1 keV FWHM energy resolution at 59.5 keV and 1.5 keV FWHM at 141 keV, at the same time providing a high speed imaging performance. This system uses a relatively simple wire-bonded interconnection scheme but this is being upgraded to allow multiple modules to be used with very small dead space. The readout system and the novel interconnect technology is described and how the system is performing in several target applications.

  17. Methods of editing cloud and atmospheric layer affected pixels from satellite data

    NASA Technical Reports Server (NTRS)

    Nixon, P. R. (Principal Investigator); Wiegand, C. L.; Richardson, A. J.; Johnson, M. P.

    1982-01-01

    Practical methods of computer screening cloud-contaminated pixels from data of various satellite systems are proposed. Examples are given of the location of clouds and representative landscape features in HCMM spectral space of reflectance (VIS) vs emission (IR). Methods of screening out cloud affected HCMM are discussed. The character of subvisible absorbing-emitting atmospheric layers (subvisible cirrus or SCi) in HCMM data is considered and radiosonde soundings are examined in relation to the presence of SCi. The statistical characteristics of multispectral meteorological satellite data in clear and SCi affected areas are discussed. Examples in TIROS-N and NOAA-7 data from several states and Mexico are presented. The VIS-IR cluster screening method for removing clouds is applied to a 262, 144 pixel HCMM scene from south Texas and northeast Mexico. The SCi that remain after cluster screening are sited out by applying a statistically determined IR limit.

  18. Robust Matching of Wavelet Features for Sub-Pixel Registration of Landsat Data

    NASA Technical Reports Server (NTRS)

    LeMoigne, Jacqueline; Netanyahu, Nathan S.; Masek, Jeffrey G.; Mount, David M.; Goward, Samuel; Zukor, Dorothy (Technical Monitor)

    2001-01-01

    For many Earth and Space Science applications, automatic geo-registration at sub-pixel accuracy has become a necessity. In this work, we are focusing on building an operational system, which will provide a sub-pixel accuracy registration of Landsat-5 and Landsat-7 data. The input to our registration method consists of scenes that have been geometrically and radiometrically corrected. Such pre-processed scenes are then geo-registered relative to a database of Landsat chips. The method assumes a transformation composed of a rotation and a translation, and utilizes rotation- and translation-invariant wavelets to extract image features that are matched using statistically robust feature matching and a generalized Hausdorff distance metric. The registration process is described and results on four Landsat input scenes of the Washington, D.C. area are presented.

  19. Getting small: new 10μm pixel pitch cooled infrared products

    NASA Astrophysics Data System (ADS)

    Reibel, Y.; Pere-Laperne, N.; Augey, T.; Rubaldo, L.; Decaens, G.; Bourqui, M.-L.; Manissadjian, A.; Billon-Lanfrey, D.; Bisotto, S.; Gravrand, O.; Destefanis, G.; Druart, G.; Guerineau, N.

    2014-06-01

    Recent advances in miniaturization of IR imaging technology have led to a burgeoning market for mini thermalimaging sensors. Seen in this context our development on smaller pixel pitch has opened the door to very compact products. When this competitive advantage is mixed with smaller coolers, thanks to HOT technology, we achieve valuable reductions in size, weight and power of the overall package. In the same time, we are moving towards a global offer based on digital interfaces that provides our customers lower power consumption and simplification on the IR system design process while freeing up more space. Additionally, we are also investigating new wafer level camera solution taking advantage of the progress in micro-optics. This paper discusses recent developments on hot and small pixel pitch technologies as well as efforts made on compact packaging solution developed by SOFRADIR in collaboration with CEA-LETI and ONERA.

  20. Pixellated Cd(Zn)Te high-energy X-ray instrument

    PubMed Central

    Seller, P.; Bell, S.; Cernik, R.J.; Christodoulou, C.; Egan, C.K.; Gaskin, J.A.; Jacques, S.; Pani, S.; Ramsey, B.D.; Reid, C.; Sellin, P.J.; Scuffham, J.W.; Speller, R.D.; Wilson, M.D.; Veale, M.C.

    2012-01-01

    We have developed a pixellated high energy X-ray detector instrument to be used in a variety of imaging applications. The instrument consists of either a Cadmium Zinc Telluride or Cadmium Telluride (Cd(Zn)Te) detector bump-bonded to a large area ASIC and packaged with a high performance data acquisition system. The 80 by 80 pixels each of 250 μm by 250 μm give better than 1 keV FWHM energy resolution at 59.5 keV and 1.5 keV FWHM at 141 keV, at the same time providing a high speed imaging performance. This system uses a relatively simple wire-bonded interconnection scheme but this is being upgraded to allow multiple modules to be used with very small dead space. The readout system and the novel interconnect technology is described and how the system is performing in several target applications. PMID:22737179

  1. Analysis of Multipath Pixels in SAR Images

    NASA Astrophysics Data System (ADS)

    Zhao, J. W.; Wu, J. C.; Ding, X. L.; Zhang, L.; Hu, F. M.

    2016-06-01

    As the received radar signal is the sum of signal contributions overlaid in one single pixel regardless of the travel path, the multipath effect should be seriously tackled as the multiple bounce returns are added to direct scatter echoes which leads to ghost scatters. Most of the existing solution towards the multipath is to recover the signal propagation path. To facilitate the signal propagation simulation process, plenty of aspects such as sensor parameters, the geometry of the objects (shape, location, orientation, mutual position between adjacent buildings) and the physical parameters of the surface (roughness, correlation length, permittivity)which determine the strength of radar signal backscattered to the SAR sensor should be given in previous. However, it's not practical to obtain the highly detailed object model in unfamiliar area by field survey as it's a laborious work and time-consuming. In this paper, SAR imaging simulation based on RaySAR is conducted at first aiming at basic understanding of multipath effects and for further comparison. Besides of the pre-imaging simulation, the product of the after-imaging, which refers to radar images is also taken into consideration. Both Cosmo-SkyMed ascending and descending SAR images of Lupu Bridge in Shanghai are used for the experiment. As a result, the reflectivity map and signal distribution map of different bounce level are simulated and validated by 3D real model. The statistic indexes such as the phase stability, mean amplitude, amplitude dispersion, coherence and mean-sigma ratio in case of layover are analyzed with combination of the RaySAR output.

  2. Monolithic pixels on moderate resistivity substrate and sparsifying readout architecture

    NASA Astrophysics Data System (ADS)

    Giubilato, P.; Battaglia, M.; Bisello, D.; Caselle, M.; Chalmet, P.; Demaria, L.; Ikemoto, Y.; Kloukinas, K.; Mansuy, S. C.; Mattiazzo, S.; Marchioro, A.; Mugnier, H.; Pantano, D.; Potenza, A.; Rivetti, A.; Rousset, J.; Silvestrin, L.; Snoeys, W.

    2013-12-01

    The LePix projects aim realizing a new generation monolithic pixel detectors with improved performances at lesser cost with respect to both current state of the art monolithic and hybrid pixel sensors. The detector is built in a 90 nm CMOS process on a substrate of moderate resistivity. This allows charge collection by drift while maintaining the other advantages usually offered by MAPS, like having a single piece detector and using a standard CMOS production line. The collection by drift mechanism, coupled to the low capacitance design of the collecting node made possible by the monolithic approach, provides an excellent signal to noise ratio straight at the pixel cell together with a radiation tolerance far superior to conventional un-depleted MAPS. The excellent signal-to-noise performance is demonstrated by the device ability to separate the 6 keV 55Fe double peak at room temperature. To achieve high granularity (10-20 μm pitch pixels) over large detector areas maintaining high readout speed, a completely new compressing architecture has been devised. This architecture departs from the mainstream hybrid pixel sparsification approach, which uses in-pixel logic to reduce data, by using topological compression to minimize pixel area and power consumption.

  3. Performance limits of a single photon counting pixel system

    NASA Astrophysics Data System (ADS)

    Chmeissani, M.; Mikulec, B.

    2001-03-01

    X-ray imaging using hybrid pixel detectors in single photon counting mode is a relatively recent and exciting development. The photon counting mode implies that each pixel has a threshold in energy above which a hit is recorded. Sharing of charge between adjacent pixels would therefore lead to a loss of registered hits and for medical imaging applications to a higher patient dose. This explains why the demand for high spatial resolution and consequently small pixel sizes (<100 μm) motivates the Medipix2 collaboration to study the effects of charge sharing between pixels on system performance. Two different simulation codes are used to simulate the energy loss inside the detector and the charge transport towards the pixel electrodes. The largest contribution to the lateral spreading of charge comes from diffusion and can result in a considerable loss of detection efficiency in photon counting systems for small pixel sizes. The Medipix2 collaboration consists of groups from Barcelona, Cagliari, CEA/Leti DEIN, CERN, Freiburg, Glasgow, Mitthögskolan, Napoli, NIKHEF, MRC lab Cambridge, Pisa, Prague and Sassari.

  4. A low light level sensor with dark current compensating pixels

    NASA Astrophysics Data System (ADS)

    Perley, Mitchell; Baxter, Patrick; Raynor, Jeffrey M.; Renshaw, David

    2008-09-01

    In ultra-low light conditions the presence of dark current becomes a major source of noise for a CMOS sensor. Standard dark current compensation techniques, such as using a dark reference frame, bring significant improvements to dark noise in typical applications. However, applications requiring long integration times mean that such techniques cannot always be used. This paper presents a differential dark current compensating pixel. The pixel is made up of a differential amplifier and two photodiodes: one light shielded photodiode connected to the non-inverting input of the opamp and a light detecting photodiode connected to the inverting input of the opamp. An integrating capacitor is used in the feedback loop to convert photocurrent to voltage, and a switched capacitor network is present in parallel with the light shielded pixel, which is used to satisfy the output equation to compensate the dark current. The pixel uses 150 μm x 150 μm photodiodes and is fabricated in a standard 0.18 μm, 6M1P, CMOS process. The results show that the pixel is light sensitive and has a linear output as expected. However, the dark current is not predictably controlled. Further work will be carried out on the pixel design, and particularly the switched capacitor circuit, to determine the cause of the non-predictability of the pixel output.

  5. Pixel Analysis and Plasma Dynamics Characterized by Photospheric Spectral Data

    NASA Astrophysics Data System (ADS)

    Rasca, A.; Chen, J.; Pevtsov, A. A.

    2015-12-01

    Continued advances in solar observations have led to higher-resolution magnetograms and surface (photospheric) images, revealing bipolar magnetic features operating near the resolution limit during emerging flux events and other phenomena used to predict solar eruptions responsible for geomagnetic plasma disturbances. However, line of sight (LOS) magnetogram pixels only contain the net uncanceled magnetic flux, which is expected to increase for fixed regions as resolution limits improve. A pixel dynamics model utilizing Stokes I spectral profiles was previously-used to quantify changes in the Doppler shift, width, asymmetry, and tail flatness of Fe I lines at 6301.5 and 6302.5 Å and used pixel-by-pixel line profile fluctuations to characterize quiet and active regions on the Sun. We use this pixel dynamics model with circularly polarized photospheric data (e.g., SOLIS data) to estimate plasma dynamic properties at a sub-pixel level. The analysis can be extended to include the full Stokes parameters and study signatures of magnetic fields and coupled plasma properties on sub-pixel scales.

  6. Monolithic pixel detectors with 0.2 μm FD-SOI pixel process technology

    NASA Astrophysics Data System (ADS)

    Miyoshi, Toshinobu; Arai, Yasuo; Chiba, Tadashi; Fujita, Yowichi; Hara, Kazuhiko; Honda, Shunsuke; Igarashi, Yasushi; Ikegami, Yoichi; Ikemoto, Yukiko; Kohriki, Takashi; Ohno, Morifumi; Ono, Yoshimasa; Shinoda, Naoyuki; Takeda, Ayaki; Tauchi, Kazuya; Tsuboyama, Toru; Tadokoro, Hirofumi; Unno, Yoshinobu; Yanagihara, Masashi

    2013-12-01

    Truly monolithic pixel detectors were fabricated with 0.2 μm SOI pixel process technology by collaborating with LAPIS Semiconductor Co., Ltd. for particle tracking experiment, X-ray imaging and medical applications. CMOS circuits were fabricated on a thin SOI layer and connected to diodes formed in the silicon handle wafer through the buried oxide layer. We can choose the handle wafer and therefore high-resistivity silicon is also available. Double SOI (D-SOI) wafers fabricated from Czochralski (CZ)-SOI wafers were newly obtained and successfully processed in 2012. The top SOI layers are used as electric circuits and the middle SOI layers used as a shield layer against the back-gate effect and cross-talk between sensors and CMOS circuits, and as an electrode to compensate for the total ionizing dose (TID) effect. In 2012, we developed two SOI detectors, INTPIX5 and INTPIX3g. A spatial resolution study was done with INTPIX5 and it showed excellent performance. The TID effect study with D-SOI INTPIX3g detectors was done and we confirmed improvement of TID tolerance in D-SOI sensors.

  7. Pixel detectors in 3D technologies for high energy physics

    SciTech Connect

    Deptuch, G.; Demarteau, M.; Hoff, J.; Lipton, R.; Shenai, A.; Yarema, R.; Zimmerman, T.; /Fermilab

    2010-10-01

    This paper reports on the current status of the development of International Linear Collider vertex detector pixel readout chips based on multi-tier vertically integrated electronics. Initial testing results of the VIP2a prototype are presented. The chip is the second embodiment of the prototype data-pushed readout concept developed at Fermilab. The device was fabricated in the MIT-LL 0.15 {micro}m fully depleted SOI process. The prototype is a three-tier design, featuring 30 x 30 {micro}m{sup 2} pixels, laid out in an array of 48 x 48 pixels.

  8. Status and Construction of the Belle II DEPFET pixel system

    NASA Astrophysics Data System (ADS)

    Lütticke, Florian

    2014-06-01

    DEpleted P-channel Field Effect Transistor (DEPFET) active pixel detectors combine detection with a first amplification stage in a fully depleted detector, resulting in an superb signal-to-noise ratio even for thin sensors. Two layers of thin (75 micron) silicon DEPFET pixels will be used as the innermost vertex system, very close to the beam pipe in the Belle II detector at the SuperKEKB facility. The status of the 8 million DEPFET pixels detector, latest developments and current system tests will be discussed.

  9. Matching faces and expressions in pixelated and blurred photos.

    PubMed

    White, Murray; Li, Judy

    2006-01-01

    Matching the emotional expressions of pairs of face photos was slower with pixelated and blurred photos than with original, untransformed photos. Matching the identities of the same face pairs was unaffected by pixelation and blurring. Because pixelation and blurring degrade higher spatial frequencies carrying edge-based information that define feature shape more than lower frequencies carrying configural properties, these findings converge with findings for line drawings and negative photos in showing that expression and face recognition processes differ in their reliance on edge-based and configural information.

  10. Vertically integrated pixel readout chip for high energy physics

    SciTech Connect

    Deptuch, Grzegorz; Demarteau, Marcel; Hoff, James; Khalid, Farah; Lipton, Ronald; Shenai, Alpana; Trimpl, Marcel; Yarema, Raymond; Zimmerman, Tom; /Fermilab

    2011-01-01

    We report on the development of the vertex detector pixel readout chips based on multi-tier vertically integrated electronics for the International Linear Collider. Some testing results of the VIP2a prototype are presented. The chip is the second iteration of the silicon implementation of the prototype, data-pushed concept of the readout developed at Fermilab. The device was fabricated in the 3D MIT-LL 0.15 {micro}m fully depleted SOI process. The prototype is a three-tier design, featuring 30 x 30 {micro}m{sup 2} pixels, laid out in an array of 48 x 48 pixels.

  11. Monolithic pixel detectors in silicon on insulator technology

    NASA Astrophysics Data System (ADS)

    Bisello, Dario

    2013-05-01

    Silicon On Insulator (SOI) is becoming an attractive technology to fabricate monolithic pixel detectors. The possibility of using the depleted resistive substrate as a drift collection volume and to connect it by means of vias through the buried oxide to the pixel electronic makes this kind of approach interesting both for particle and photon detection. In this paper I report the results obtained in the development of monolithic pixel detectors in an SOI technology by a collaboration between groups from the University and INFN of Padova (Italy) and the LBNL and the SCIPP at UCSC (USA).

  12. Pixel CdTe semiconductor module to implement a sub-MeV imaging detector for astrophysics

    NASA Astrophysics Data System (ADS)

    Gálvez, J.-L.; Hernanz, M.; Álvarez, L.; Artigues, B.; Álvarez, J.-M.; Ullán, M.; Pellegrini, G.; Lozano, M.; Cabruja, E.; Martínez, R.; Chmeissani, M.; Puigdengoles, C.

    2017-03-01

    Stellar explosions are relevant and interesting astrophysical phenomena. Since long ago we have been working on the characterization of nova and supernova explosions in X and gamma rays, with the use of space missions such as INTEGRAL, XMM-Newton and Swift. We have been also involved in feasibility studies of future instruments in the energy range from several keV up to a few MeV, in collaboration with other research institutes, such as GRI, DUAL and e-ASTROGAM. High sensitivities are essential to perform detailed studies of cosmic explosions and cosmic accelerators, e.g., Supernovae, Classical Novae, Supernova Remnants (SNRs), Gamma-Ray Bursts (GRBs). In order to fulfil the combined requirement of high detection efficiency with good spatial and energy resolution, an initial module prototype based on CdTe pixel detectors is being developed. The detector dimensions are 12.5mm x 12.5mm x 2mm, with a pixel pitch of 1mm x 1mm. Each pixel is bump bonded to a fanout board made of Sapphire substrate and routed to the corresponding input channel of the readout ASIC, to measure pixel position and pulse height for each incident gamma-ray photon. An ohmic CdTe pixel detector has been characterised by means of 57Co, 133Ba and 22Na sources. Based on this, its spectroscopic performance and the influence of charge sharing is reported here. The pixel study is complemented by the simulation of the CdTe module performance using the GEANT 4 and MEGALIB tools, which will help us to optimise the pixel size selection.

  13. A germanium hybrid pixel detector with 55μm pixel size and 65,000 channels

    NASA Astrophysics Data System (ADS)

    Pennicard, D.; Struth, B.; Hirsemann, H.; Sarajlic, M.; Smoljanin, S.; Zuvic, M.; Lampert, M. O.; Fritzsch, T.; Rothermund, M.; Graafsma, H.

    2014-12-01

    Hybrid pixel semiconductor detectors provide high performance through a combination of direct detection, a relatively small pixel size, fast readout and sophisticated signal processing circuitry in each pixel. For X-ray detection above 20 keV, high-Z sensor layers rather than silicon are needed to achieve high quantum efficiency, but many high-Z materials such as GaAs and CdTe often suffer from poor material properties or nonuniformities. Germanium is available in large wafers of extremely high quality, making it an appealing option for high-performance hybrid pixel X-ray detectors, but suitable technologies for finely pixelating and bump-bonding germanium have not previously been available. A finely-pixelated germanium photodiode sensor with a 256 by 256 array of 55μm pixels has been produced. The sensor has an n-on-p structure, with 700μm thickness. Using a low-temperature indium bump process, this sensor has been bonded to the Medipix3RX photoncounting readout chip. Tests with the LAMBDA readout system have shown that the detector works successfully, with a high bond yield and higher image uniformity than comparable high-Z systems. During cooling, the system is functional around -80°C (with warmer temperatures resulting in excessive leakage current), with -100°C sufficient for good performance.

  14. Development of a Cost-Effective Modular Pixelated NaI(Tl) Detector for Clinical SPECT Applications

    PubMed Central

    Rozler, Mike; Liang, Haoning; Chang, Wei

    2013-01-01

    A new pixelated detector for high-resolution clinical SPECT applications was designed and tested. The modular detector is based on a scintillator block comprised of 2.75×2.75×10 mm3 NaI(Tl) pixels and decoded by an array of 51 mm diameter single-anode PMTs. Several configurations, utilizing two types of PMTs, were evaluated using a collimated beam source to measure positioning accuracy directly. Good pixel separation was observed, with correct pixel identification ranging from 60 to 72% averaged over the entire area of the modules, depending on the PMT type and configuration. This translates to a significant improvement in positioning accuracy compared to continuous slab detectors of the same thickness, along with effective reduction of “dead” space at the edges. The observed 10% average energy resolution compares well to continuous slab detectors. The combined performance demonstrates the suitability of pixelated detectors decoded with a relatively small number of medium-sized PMTs as a cost-effective approach for high resolution clinical SPECT applications, in particular those involving curved detector geometries. PMID:24146436

  15. Brain tumor grading based on Neural Networks and Convolutional Neural Networks.

    PubMed

    Yuehao Pan; Weimin Huang; Zhiping Lin; Wanzheng Zhu; Jiayin Zhou; Wong, Jocelyn; Zhongxiang Ding

    2015-08-01

    This paper studies brain tumor grading using multiphase MRI images and compares the results with various configurations of deep learning structure and baseline Neural Networks. The MRI images are used directly into the learning machine, with some combination operations between multiphase MRIs. Compared to other researches, which involve additional effort to design and choose feature sets, the approach used in this paper leverages the learning capability of deep learning machine. We present the grading performance on the testing data measured by the sensitivity and specificity. The results show a maximum improvement of 18% on grading performance of Convolutional Neural Networks based on sensitivity and specificity compared to Neural Networks. We also visualize the kernels trained in different layers and display some self-learned features obtained from Convolutional Neural Networks.

  16. Pulmonary Nodule Classification with Deep Convolutional Neural Networks on Computed Tomography Images.

    PubMed

    Li, Wei; Cao, Peng; Zhao, Dazhe; Wang, Junbo

    2016-01-01

    Computer aided detection (CAD) systems can assist radiologists by offering a second opinion on early diagnosis of lung cancer. Classification and feature representation play critical roles in false-positive reduction (FPR) in lung nodule CAD. We design a deep convolutional neural networks method for nodule classification, which has an advantage of autolearning representation and strong generalization ability. A specified network structure for nodule images is proposed to solve the recognition of three types of nodules, that is, solid, semisolid, and ground glass opacity (GGO). Deep convolutional neural networks are trained by 62,492 regions-of-interest (ROIs) samples including 40,772 nodules and 21,720 nonnodules from the Lung Image Database Consortium (LIDC) database. Experimental results demonstrate the effectiveness of the proposed method in terms of sensitivity and overall accuracy and that it consistently outperforms the competing methods.

  17. Video-based convolutional neural networks for activity recognition from robot-centric videos

    NASA Astrophysics Data System (ADS)

    Ryoo, M. S.; Matthies, Larry

    2016-05-01

    In this evaluation paper, we discuss convolutional neural network (CNN)-based approaches for human activity recognition. In particular, we investigate CNN architectures designed to capture temporal information in videos and their applications to the human activity recognition problem. There have been multiple previous works to use CNN-features for videos. These include CNNs using 3-D XYT convolutional filters, CNNs using pooling operations on top of per-frame image-based CNN descriptors, and recurrent neural networks to learn temporal changes in per-frame CNN descriptors. We experimentally compare some of these different representatives CNNs while using first-person human activity videos. We especially focus on videos from a robots viewpoint, captured during its operations and human-robot interactions.

  18. Pulmonary Nodule Classification with Deep Convolutional Neural Networks on Computed Tomography Images

    PubMed Central

    Li, Wei; Zhao, Dazhe; Wang, Junbo

    2016-01-01

    Computer aided detection (CAD) systems can assist radiologists by offering a second opinion on early diagnosis of lung cancer. Classification and feature representation play critical roles in false-positive reduction (FPR) in lung nodule CAD. We design a deep convolutional neural networks method for nodule classification, which has an advantage of autolearning representation and strong generalization ability. A specified network structure for nodule images is proposed to solve the recognition of three types of nodules, that is, solid, semisolid, and ground glass opacity (GGO). Deep convolutional neural networks are trained by 62,492 regions-of-interest (ROIs) samples including 40,772 nodules and 21,720 nonnodules from the Lung Image Database Consortium (LIDC) database. Experimental results demonstrate the effectiveness of the proposed method in terms of sensitivity and overall accuracy and that it consistently outperforms the competing methods. PMID:28070212

  19. Improvement of Event Synchronization in the ATLAS Pixel Readout Development

    NASA Astrophysics Data System (ADS)

    Adams, Logan; Atlas Collaboration

    2017-01-01

    As the LHC continues in Run2, the B-Layer still uses the Atlas-SiROD Pixel readout system initially developed for Run 1. The higher luminosity occurring during Run 2 results in higher occupancy causing increased desynchronization errors in the Pixel Readout. In order to ensure lasting operation of the B-Layer until it is replaced after Run 3, changes were made to the firmware and software to add debug capabilities to identify when the errors are crossing certain thresholds and change the internal control logic accordingly. These features also allow for better debugging of the Event Counter Reset addition to the firmware. This talk will focus on the features implemented and measurements to demonstrate the positive impact on the Pixel DAQ system. A Pixel front-end chip emulator which can be used for readout system development beyond Run 3 will also be discussed. Presenter is Logan Adams, University of Washington.

  20. Pixel-by-pixel VIS/NIR and LIR sensor fusion system

    NASA Astrophysics Data System (ADS)

    Zhang, Evan; Zhang, James S.; Song, Vivian W.; Chin, Ken P.; Hu, Gelbert

    2003-01-01

    Visible (VIS) camera (such as CCD) or Near Infrared (NIR) camera (such as low light level CCD or image intensifier) has high resolution and is easy to distinguish enemy and foe, but it cannot see through thin fog/cloud, heavy smoke/dust, foliage, camouflage, and darkness. The Long Infrared (LIR) imager can overcome above problems, but the resolution is too low and it cannot see the NIR aiming light from enemy. The best solution is to fuse the VIS/NIR and LIR sensors to overcome their shortcomings and take advantages of both sensors. In order to see the same target without parallax, the fusio system must have a common optical aperature. In this paper, three common optical apertures are designed: common reflective objective lens, common beam splitter, and common transmissive objective lens. The first one has very small field of view and the second one needs two heads, so the best choice is the third one, but we must find suitable optical materials and correct the color aberrations from 0.6 to 12 μ. It is a tough job. By choosing ZnSe as the first common piece of the objective lens and using glass for NIR and Ge (or IR glass) for LIR as rest pieces, we only need to and are able to correct the aberrations from 0.6 to 1.0 μ for NIR and from 8 to 12 μ for LIR. Finally, a common reflective objective lens and the common beam splitter are also successfully designed. Five application examples are given. In the digital signal processing, we use only one Altera chip. After inserting data, scaling the image size, and adjusting the signal level, the LIR will have the same format and same pixel number of the VIS/NIR, so real-time pixel-by-pixel sensor fusion is realized. The digital output can be used for further image processing and automatic target recognition, such as if we overlap the LIR image on the VIS/NIR image for missile guidance or rifle sight we don't need to worry about the time and the environment again. A gum-size wireless transmitter is also designed that is

  1. Fuzzy Logic Module of Convolutional Neural Network for Handwritten Digits Recognition

    NASA Astrophysics Data System (ADS)

    Popko, E. A.; Weinstein, I. A.

    2016-08-01

    Optical character recognition is one of the important issues in the field of pattern recognition. This paper presents a method for recognizing handwritten digits based on the modeling of convolutional neural network. The integrated fuzzy logic module based on a structural approach was developed. Used system architecture adjusted the output of the neural network to improve quality of symbol identification. It was shown that proposed algorithm was flexible and high recognition rate of 99.23% was achieved.

  2. Transient electromagnetic modeling of the ZR accelerator water convolute and stack.

    SciTech Connect

    Lehr, Jane Marie; Elizondo-Decanini, Juan Manuel; Turner, C. David; Coats, Rebecca Sue; Bohnhoff, William J.; Pointon, Timothy David; Pasik, Michael Francis; Johnson, William Arthur; Savage, Mark Edward

    2005-06-01

    The ZR accelerator is a refurbishment of Sandia National Laboratories Z accelerator [1]. The ZR accelerator components were designed using electrostatic and circuit modeling tools. Transient electromagnetic modeling has played a complementary role in the analysis of ZR components [2]. In this paper we describe a 3D transient electromagnetic analysis of the ZR water convolute and stack using edge-based finite element techniques.

  3. Proteomic analysis of brush-border membrane vesicles isolated from purified proximal convoluted tubules

    PubMed Central

    Walmsley, Scott J.; Broeckling, Corey; Hess, Ann; Prenni, Jessica

    2010-01-01

    The renal proximal convoluted tubule is the primary site of water, electrolyte and nutrient reabsorption and of active secretion of selected molecules. Proteins in the apical brush-border membrane facilitate these functions and initiate some of the cellular responses to altered renal physiology. The current study uses two-dimensional liquid chromatography/mass spectrometry to compare brush border membrane vesicles isolated from rat renal cortex (BBMVCTX) and from purified proximal convoluted tubules (BBMVPCT). Both proteomic data and Western blot analysis indicate that the BBMVCTX contain apical membrane proteins from cortical cells other than the proximal tubule. This heterogeneity was greatly reduced in the BBMVPCT. Proteomic analysis identified 193 proteins common to both samples, 21 proteins unique to BBMVCTX, and 57 proteins unique to BBMVPCT. Spectral counts were used to quantify relative differences in protein abundance. This analysis identified 42 and 50 proteins that are significantly enriched (p values ≤0.001) in the BBMVCTX and BBMVPCT, respectively. These data were validated by measurement of γ-glutamyltranspeptidase activity and by Western blot analysis. The combined results establish that BBMVPCT are primarily derived from the proximal convoluted tubule (S1 and S2 segments), whereas BBMVCTX include proteins from the proximal straight tubule (S3 segment). Analysis of functional annotations indicated that BBMVPCT are enriched in mitochondrial proteins and enzymes involved in glucose and organic acid metabolism. Thus the current study reports a detailed proteomic analysis of the brush-border membrane of the rat renal proximal convoluted tubule and provides a database for future hypothesis-driven research. PMID:20219825

  4. Convolution-based estimation of organ dose in tube current modulated CT

    NASA Astrophysics Data System (ADS)

    Tian, Xiaoyu; Segars, W. P.; Dixon, R. L.; Samei, Ehsan

    2015-03-01

    Among the various metrics that quantify radiation dose in computed tomography (CT), organ dose is one of the most representative quantities reflecting patient-specific radiation burden.1 Accurate estimation of organ dose requires one to effectively model the patient anatomy and the irradiation field. As illustrated in previous studies, the patient anatomy factor can be modeled using a library of computational phantoms with representative body habitus.2 However, the modeling of irradiation field can be practically challenging, especially for CT exams performed with tube current modulation. The central challenge is to effectively quantify the scatter irradiation field created by the dynamic change of tube current. In this study, we present a convolution-based technique to effectively quantify the primary and scatter irradiation field for TCM examinations. The organ dose for a given clinical patient can then be rapidly determined using the convolution-based method, a patient-matching technique, and a library of computational phantoms. 58 adult patients were included in this study (age range: 18-70 y.o., weight range: 60-180 kg). One computational phantom was created based on the clinical images of each patient. Each patient was optimally matched against one of the remaining 57 computational phantoms using a leave-one-out strategy. For each computational phantom, the organ dose coefficients (CTDIvol-normalized organ dose) under fixed tube current were simulated using a validated Monte Carlo simulation program. Such organ dose coefficients were multiplied by a scaling factor, (CTDIvol )organ, convolution that quantifies the regional irradiation field. The convolution-based organ dose was compared with the organ dose simulated from Monte Carlo program with TCM profiles explicitly modeled on the original phantom created based on patient images. The estimation error was within 10% across all organs and modulation profiles for abdominopelvic examination. This strategy

  5. Transfer Learning with Convolutional Neural Networks for Classification of Abdominal Ultrasound Images.

    PubMed

    Cheng, Phillip M; Malhi, Harshawn S

    2017-04-01

    The purpose of this study is to evaluate transfer learning with deep convolutional neural networks for the classification of abdominal ultrasound images. Grayscale images from 185 consecutive clinical abdominal ultrasound studies were categorized into 11 categories based on the text annotation specified by the technologist for the image. Cropped images were rescaled to 256 × 256 resolution and randomized, with 4094 images from 136 studies constituting the training set, and 1423 images from 49 studies constituting the test set. The fully connected layers of two convolutional neural networks based on CaffeNet and VGGNet, previously trained on the 2012 Large Scale Visual Recognition Challenge data set, were retrained on the training set. Weights in the convolutional layers of each network were frozen to serve as fixed feature extractors. Accuracy on the test set was evaluated for each network. A radiologist experienced in abdominal ultrasound also independently classified the images in the test set into the same 11 categories. The CaffeNet network classified 77.3% of the test set images accurately (1100/1423 images), with a top-2 accuracy of 90.4% (1287/1423 images). The larger VGGNet network classified 77.9% of the test set accurately (1109/1423 images), with a top-2 accuracy of VGGNet was 89.7% (1276/1423 images). The radiologist classified 71.7% of the test set images correctly (1020/1423 images). The differences in classification accuracies between both neural networks and the radiologist were statistically significant (p < 0.001). The results demonstrate that transfer learning with convolutional neural networks may be used to construct effective classifiers for abdominal ultrasound images.

  6. A filtering approach based on Gaussian-powerlaw convolutions for local PET verification of proton radiotherapy.

    PubMed

    Parodi, Katia; Bortfeld, Thomas

    2006-04-21

    Because proton beams activate positron emitters in patients, positron emission tomography (PET) has the potential to play a unique role in the in vivo verification of proton radiotherapy. Unfortunately, the PET image is not directly proportional to the delivered radiation dose distribution. Current treatment verification strategies using PET therefore compare the actual PET image with full-blown Monte Carlo simulations of the PET signal. In this paper, we describe a simpler and more direct way to reconstruct the expected PET signal from the local radiation dose distribution near the distal fall-off region, which is calculated by the treatment planning programme. Under reasonable assumptions, the PET image can be described as a convolution of the dose distribution with a filter function. We develop a formalism to derive the filter function analytically. The main concept is the introduction of 'Q' functions defined as the convolution of a Gaussian with a powerlaw function. Special Q functions are the Gaussian itself and the error function. The convolution of two Q functions is another Q function. By fitting elementary dose distributions and their corresponding PET signals with Q functions, we derive the Q function approximation of the filter. The new filtering method has been validated through comparisons with Monte Carlo calculations and, in one case, with measured data. While the basic concept is developed under idealized conditions assuming that the absorbing medium is homogeneous near the distal fall-off region, a generalization to inhomogeneous situations is also described. As a result, the method can determine the distal fall-off region of the PET signal, and consequently the range of the proton beam, with millimetre accuracy. Quantification of the produced activity is possible. In conclusion, the PET activity resulting from a proton beam treatment can be determined by locally filtering the dose distribution as obtained from the treatment planning system. The

  7. Quantum Fields Obtained from Convoluted Generalized White Noise Never Have Positive Metric

    NASA Astrophysics Data System (ADS)

    Albeverio, Sergio; Gottschalk, Hanno

    2016-05-01

    It is proven that the relativistic quantum fields obtained from analytic continuation of convoluted generalized (Lévy type) noise fields have positive metric, if and only if the noise is Gaussian. This follows as an easy observation from a criterion by Baumann, based on the Dell'Antonio-Robinson-Greenberg theorem, for a relativistic quantum field in positive metric to be a free field.

  8. Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields.

    PubMed

    Liu, Fayao; Shen, Chunhua; Lin, Guosheng; Reid, Ian

    2016-10-01

    In this article, we tackle the problem of depth estimation from single monocular images. Compared with depth estimation using multiple images such as stereo depth perception, depth from monocular images is much more challenging. Prior work typically focuses on exploiting geometric priors or additional sources of information, most using hand-crafted features. Recently, there is mounting evidence that features from deep convolutional neural networks (CNN) set new records for various vision applications. On the other hand, considering the continuous characteristic of the depth values, depth estimation can be naturally formulated as a continuous conditional random field (CRF) learning problem. Therefore, here we present a deep convolutional neural field model for estimating depths from single monocular images, aiming to jointly explore the capacity of deep CNN and continuous CRF. In particular, we propose a deep structured learning scheme which learns the unary and pairwise potentials of continuous CRF in a unified deep CNN framework. We then further propose an equally effective model based on fully convolutional networks and a novel superpixel pooling method, which is about 10 times faster, to speedup the patch-wise convolutions in the deep model. With this more efficient model, we are able to design deeper networks to pursue better performance. Our proposed method can be used for depth estimation of general scenes with no geometric priors nor any extra information injected. In our case, the integral of the partition function can be calculated in a closed form such that we can exactly solve the log-likelihood maximization. Moreover, solving the inference problem for predicting depths of a test image is highly efficient as closed-form solutions exist. Experiments on both indoor and outdoor scene datasets demonstrate that the proposed method outperforms state-of-the-art depth estimation approaches.

  9. FPIX2, the BTeV pixel readout chip

    SciTech Connect

    David C. Christian et al.

    2003-12-10

    A radiation tolerant pixel readout chip, FPIX2, has been developed at Fermilab for use by BTeV. Some of the requirements of the BTeV pixel readout chip are reviewed and contrasted with requirements for similar devices in LHC experiments. A description of the FPIX2 is given, and results of initial tests of its performance are presented, as is a summary of measurements planned for the coming year.

  10. A Chip and Pixel Qualification Methodology on Imaging Sensors

    NASA Technical Reports Server (NTRS)

    Chen, Yuan; Guertin, Steven M.; Petkov, Mihail; Nguyen, Duc N.; Novak, Frank

    2004-01-01

    This paper presents a qualification methodology on imaging sensors. In addition to overall chip reliability characterization based on sensor s overall figure of merit, such as Dark Rate, Linearity, Dark Current Non-Uniformity, Fixed Pattern Noise and Photon Response Non-Uniformity, a simulation technique is proposed and used to project pixel reliability. The projected pixel reliability is directly related to imaging quality and provides additional sensor reliability information and performance control.

  11. Small pixel CZT detector for hard X-ray spectroscopy

    NASA Astrophysics Data System (ADS)

    Wilson, Matthew David; Cernik, Robert; Chen, Henry; Hansson, Conny; Iniewski, Kris; Jones, Lawrence L.; Seller, Paul; Veale, Matthew C.

    2011-10-01

    A new small pixel cadmium zinc telluride (CZT) detector has been developed for hard X-ray spectroscopy. The X-ray performance of four detectors is presented and the detectors are analysed in terms of the energy resolution of each pixel. The detectors were made from CZT crystals grown by the travelling heater method (THM) bonded to a 20×20 application specific integrated circuit (ASIC) and data acquisition (DAQ) system. The detectors had an array of 20×20 pixels on a 250 μm pitch, with each pixel gold-stud bonded to an energy resolving circuit in the ASIC. The DAQ system digitised the ASIC output with 14 bit resolution, performing offset corrections and data storage to disc in real time at up to 40,000 frames per second. The detector geometry and ASIC design was optimised for X-ray spectroscopy up to 150 keV and made use of the small pixel effect to preferentially measure the electron signal. A 241Am source was used to measure the spectroscopic performance and uniformity of the detectors. The average energy resolution (FWHM at 59.54 keV) of each pixel ranged from 1.09±0.46 to 1.50±0.57 keV across the four detectors. The detectors showed good spectral performance and uniform response over almost all pixels in the 20×20 array. A large area 80×80 pixel detector will be built that will utilise the scalable design of the ASIC and the large areas of monolithic spectroscopic grade THM grown CZT that are now available. The large area detector will have the same performance as that demonstrated here.

  12. Vehicle detection based on visual saliency and deep sparse convolution hierarchical model

    NASA Astrophysics Data System (ADS)

    Cai, Yingfeng; Wang, Hai; Chen, Xiaobo; Gao, Li; Chen, Long

    2016-07-01

    Traditional vehicle detection algorithms use traverse search based vehicle candidate generation and hand crafted based classifier training for vehicle candidate verification. These types of methods generally have high processing times and low vehicle detection performance. To address this issue, a visual saliency and deep sparse convolution hierarchical model based vehicle detection algorithm is proposed. A visual saliency calculation is firstly used to generate a small vehicle candidate area. The vehicle candidate sub images are then loaded into a sparse deep convolution hierarchical model with an SVM-based classifier to perform the final detection. The experimental results demonstrate that the proposed method is with 94.81% correct rate and 0.78% false detection rate on the existing datasets and the real road pictures captured by our group, which outperforms the existing state-of-the-art algorithms. More importantly, high discriminative multi-scale features are generated by deep sparse convolution network which has broad application prospects in target recognition in the field of intelligent vehicle.

  13. Joint multiple fully connected convolutional neural network with extreme learning machine for hepatocellular carcinoma nuclei grading.

    PubMed

    Li, Siqi; Jiang, Huiyan; Pang, Wenbo

    2017-03-22

    Accurate cell grading of cancerous tissue pathological image is of great importance in medical diagnosis and treatment. This paper proposes a joint multiple fully connected convolutional neural network with extreme learning machine (MFC-CNN-ELM) architecture for hepatocellular carcinoma (HCC) nuclei grading. First, in preprocessing stage, each grayscale image patch with the fixed size is obtained using center-proliferation segmentation (CPS) method and the corresponding labels are marked under the guidance of three pathologists. Next, a multiple fully connected convolutional neural network (MFC-CNN) is designed to extract the multi-form feature vectors of each input image automatically, which considers multi-scale contextual information of deep layer maps sufficiently. After that, a convolutional neural network extreme learning machine (CNN-ELM) model is proposed to grade HCC nuclei. Finally, a back propagation (BP) algorithm, which contains a new up-sample method, is utilized to train MFC-CNN-ELM architecture. The experiment comparison results demonstrate that our proposed MFC-CNN-ELM has superior performance compared with related works for HCC nuclei grading. Meanwhile, external validation using ICPR 2014 HEp-2 cell dataset shows the good generalization of our MFC-CNN-ELM architecture.

  14. Convolutional neural network approach for buried target recognition in FL-LWIR imagery

    NASA Astrophysics Data System (ADS)

    Stone, K.; Keller, J. M.

    2014-05-01

    A convolutional neural network (CNN) approach to recognition of buried explosive hazards in forward-looking long-wave infrared (FL-LWIR) imagery is presented. The convolutional filters in the first layer of the network are learned in the frequency domain, making enforcement of zero-phase and zero-dc response characteristics much easier. The spatial domain representations of the filters are forced to have unit l2 norm, and penalty terms are added to the online gradient descent update to encourage orthonormality among the convolutional filters, as well smooth first and second order derivatives in the spatial domain. The impact of these modifications on the generalization performance of the CNN model is investigated. The CNN approach is compared to a second recognition algorithm utilizing shearlet and log-gabor decomposition of the image coupled with cell-structured feature extraction and support vector machine classification. Results are presented for multiple FL-LWIR data sets recently collected from US Army test sites. These data sets include vehicle position information allowing accurate transformation between image and world coordinates and realistic evaluation of detection and false alarm rates.

  15. Deep Convolutional Extreme Learning Machine and Its Application in Handwritten Digit Classification

    PubMed Central

    Yang, Xinyi

    2016-01-01

    In recent years, some deep learning methods have been developed and applied to image classification applications, such as convolutional neuron network (CNN) and deep belief network (DBN). However they are suffering from some problems like local minima, slow convergence rate, and intensive human intervention. In this paper, we propose a rapid learning method, namely, deep convolutional extreme learning machine (DC-ELM), which combines the power of CNN and fast training of ELM. It uses multiple alternate convolution layers and pooling layers to effectively abstract high level features from input images. Then the abstracted features are fed to an ELM classifier, which leads to better generalization performance with faster learning speed. DC-ELM also introduces stochastic pooling in the last hidden layer to reduce dimensionality of features greatly, thus saving much training time and computation resources. We systematically evaluated the performance of DC-ELM on two handwritten digit data sets: MNIST and USPS. Experimental results show that our method achieved better testing accuracy with significantly shorter training time in comparison with deep learning methods and other ELM methods. PMID:27610128

  16. Hardware efficient implementation of DFT using an improved first-order moments based cyclic convolution structure

    NASA Astrophysics Data System (ADS)

    Xiong, Jun; Liu, J. G.; Cao, Li

    2015-12-01

    This paper presents hardware efficient designs for implementing the one-dimensional (1D) discrete Fourier transform (DFT). Once DFT is formulated as the cyclic convolution form, the improved first-order moments-based cyclic convolution structure can be used as the basic computing unit for the DFT computation, which only contains a control module, a barrel shifter and (N-1)/2 accumulation units. After decomposing and reordering the twiddle factors, all that remains to do is shifting the input data sequence and accumulating them under the control of the statistical results on the twiddle factors. The whole calculation process only contains shift operations and additions with no need for multipliers and large memory. Compared with the previous first-order moments-based structure for DFT, the proposed designs have the advantages of less hardware consumption, lower power consumption and the flexibility to achieve better performance in certain cases. A series of experiments have proven the high performance of the proposed designs in terms of the area time product and power consumption. Similar efficient designs can be obtained for other computations, such as DCT/IDCT, DST/IDST, digital filter and correlation by transforming them into the forms of the first-order moments based cyclic convolution.

  17. Deep Convolutional Extreme Learning Machine and Its Application in Handwritten Digit Classification.

    PubMed

    Pang, Shan; Yang, Xinyi

    2016-01-01

    In recent years, some deep learning methods have been developed and applied to image classification applications, such as convolutional neuron network (CNN) and deep belief network (DBN). However they are suffering from some problems like local minima, slow convergence rate, and intensive human intervention. In this paper, we propose a rapid learning method, namely, deep convolutional extreme learning machine (DC-ELM), which combines the power of CNN and fast training of ELM. It uses multiple alternate convolution layers and pooling layers to effectively abstract high level features from input images. Then the abstracted features are fed to an ELM classifier, which leads to better generalization performance with faster learning speed. DC-ELM also introduces stochastic pooling in the last hidden layer to reduce dimensionality of features greatly, thus saving much training time and computation resources. We systematically evaluated the performance of DC-ELM on two handwritten digit data sets: MNIST and USPS. Experimental results show that our method achieved better testing accuracy with significantly shorter training time in comparison with deep learning methods and other ELM methods.

  18. High-voltage pixel sensors for ATLAS upgrade

    NASA Astrophysics Data System (ADS)

    Perić, I.; Kreidl, C.; Fischer, P.; Bompard, F.; Breugnon, P.; Clemens, J.-C.; Fougeron, D.; Liu, J.; Pangaud, P.; Rozanov, A.; Barbero, M.; Feigl, S.; Capeans, M.; Ferrere, D.; Pernegger, H.; Ristic, B.; Muenstermann, D.; Gonzalez Sevilla, S.; La Rosa, A.; Miucci, A.; Nessi, M.; Iacobucci, G.; Backhaus, M.; Hügging, Fabian; Krüger, H.; Hemperek, T.; Obermann, T.; Wermes, N.; Garcia-Sciveres, M.; Quadt, A.; Weingarten, J.; George, M.; Grosse-Knetter, J.; Rieger, J.; Bates, R.; Blue, A.; Buttar, C.; Hynds, D.

    2014-11-01

    The high-voltage (HV-) CMOS pixel sensors offer several good properties: a fast charge collection by drift, the possibility to implement relatively complex CMOS in-pixel electronics and the compatibility with commercial processes. The sensor element is a deep n-well diode in a p-type substrate. The n-well contains CMOS pixel electronics. The main charge collection mechanism is drift in a shallow, high field region, which leads to a fast charge collection and a high radiation tolerance. We are currently evaluating the use of the high-voltage detectors implemented in 180 nm HV-CMOS technology for the high-luminosity ATLAS upgrade. Our approach is replacing the existing pixel and strip sensors with the CMOS sensors while keeping the presently used readout ASICs. By intelligence we mean the ability of the sensor to recognize a particle hit and generate the address information. In this way we could benefit from the advantages of the HV sensor technology such as lower cost, lower mass, lower operating voltage, smaller pitch, smaller clusters at high incidence angles. Additionally we expect to achieve a radiation hardness necessary for ATLAS upgrade. In order to test the concept, we have designed two HV-CMOS prototypes that can be readout in two ways: using pixel and strip readout chips. In the case of the pixel readout, the connection between HV-CMOS sensor and the readout ASIC can be established capacitively.

  19. Error-free demodulation of pixelated carrier frequency interferograms.

    PubMed

    Servin, M; Estrada, J C

    2010-08-16

    Recently, pixelated spatial carrier interferograms have been used in optical metrology and are an industry standard nowadays. The main feature of these interferometers is that each pixel over the video camera may be phase-modulated by any (however fixed) desired angle within [0,2pi] radians. The phase at each pixel is shifted without cross-talking from their immediate neighborhoods. This has opened new possibilities for experimental spatial wavefront modulation not dreamed before, because we are no longer constrained to introduce a spatial-carrier using a tilted plane. Any useful mathematical model to phase-modulate the testing wavefront in a pixel-wise basis can be used. However we are nowadays faced with the problem that these pixelated interferograms have not been correctly demodulated to obtain an error-free (exact) wavefront estimation. The purpose of this paper is to offer the general theory that allows one to demodulate, in an exact way, pixelated spatial-carrier interferograms modulated by any thinkable two-dimensional phase carrier.

  20. Techniques for precise energy calibration of particle pixel detectors

    NASA Astrophysics Data System (ADS)

    Kroupa, M.; Campbell-Ricketts, T.; Bahadori, A.; Empl, A.

    2017-03-01

    We demonstrate techniques to improve the accuracy of the energy calibration of Timepix pixel detectors, used for the measurement of energetic particles. The typical signal from such particles spreads among many pixels due to charge sharing effects. As a consequence, the deposited energy in each pixel cannot be reconstructed unless the detector is calibrated, limiting the usability of such signals for calibration. To avoid this shortcoming, we calibrate using low energy X-rays. However, charge sharing effects still occur, resulting in part of the energy being deposited in adjacent pixels and possibly lost. This systematic error in the calibration process results in an error of about 5% in the energy measurements of calibrated devices. We use FLUKA simulations to assess the magnitude of charge sharing effects, allowing a corrected energy calibration to be performed on several Timepix pixel detectors and resulting in substantial improvement in energy deposition measurements. Next, we address shortcomings in calibration associated with the huge range (from kiloelectron-volts to megaelectron-volts) of energy deposited per pixel which result in a nonlinear energy response over the full range. We introduce a new method to characterize the non-linear response of the Timepix detectors at high input energies. We demonstrate improvement using a broad range of particle types and energies, showing that the new method reduces the energy measurement errors, in some cases by more than 90%.

  1. Challenges of small-pixel infrared detectors: a review

    NASA Astrophysics Data System (ADS)

    Rogalski, A.; Martyniuk, P.; Kopytko, M.

    2016-04-01

    In the last two decades, several new concepts for improving the performance of infrared detectors have been proposed. These new concepts particularly address the drive towards the so-called high operating temperature focal plane arrays (FPAs), aiming to increase detector operating temperatures, and as a consequence reduce the cost of infrared systems. In imaging systems with the above megapixel formats, pixel dimension plays a crucial role in determining critical system attributes such as system size, weight and power consumption (SWaP). The advent of smaller pixels has also resulted in the superior spatial and temperature resolution of these systems. Optimum pixel dimensions are limited by diffraction effects from the aperture, and are in turn wavelength-dependent. In this paper, the key challenges in realizing optimum pixel dimensions in FPA design including dark current, pixel hybridization, pixel delineation, and unit cell readout capacity are outlined to achieve a sufficiently adequate modulation transfer function for the ultra-small pitches involved. Both photon and thermal detectors have been considered. Concerning infrared photon detectors, the trade-offs between two types of competing technology—HgCdTe material systems and III-V materials (mainly barrier detectors)—have been investigated.

  2. Fault tolerant photodiode and photogate active pixel sensors

    NASA Astrophysics Data System (ADS)

    Jung, Cory; Chapman, Glenn H.; La Haye, Michelle L.; Djaja, Sunjaya; Cheung, Desmond Y. H.; Lin, Henry; Loo, Edward; Audet, Yves R.

    2005-03-01

    As the pixel counts of digital imagers increase, the challenge of maintaining high yields and ensuring reliability over an imager"s lifetime increases. A fault tolerant active pixel sensor (APS) has been designed to meet this need by splitting an APS in half and operating both halves in parallel. The fault tolerant APS will perform normally in the no defect case and will produce approximately half the output for single defects. Thus, the entire signal can be recovered by multiplying the output by two. Since pixels containing multiple defects are rare, this design can correct for most defects allowing for higher production yields. Fault tolerant photodiode and photogate APS" were fabricated in 0.18-micron technology. Testing showed that the photodiode APS could correct for optically induced and electrically induced faults, within experimental error. The photogate APS was only tested for optically induced defects and also corrects for defects within experimental error. Further testing showed that the sensitivity of fault tolerant pixels was approximately 2-3 times more sensitive than the normal pixels. HSpice simulations of the fault tolerant APS circuit did not show increased sensitivity, however an equivalent normal APS circuit with twice width readout and row transistors was 1.90 times more sensitive than a normal pixel.

  3. Frequency distribution signatures and classification of within-object pixels

    PubMed Central

    Stow, Douglas A.; Toure, Sory I.; Lippitt, Christopher D.; Lippitt, Caitlin L.; Lee, Chung-rui

    2011-01-01

    The premise of geographic object-based image analysis (GEOBIA) is that image objects are composed of aggregates of pixels that correspond to earth surface features of interest. Most commonly, image-derived objects (segments) or objects associated with predefined land units (e.g., agricultural fields) are classified using parametric statistical characteristics (e.g., mean and standard deviation) of the within-object pixels. The objective of this exploratory study was to examine the between- and within-class variability of frequency distributions of multispectral pixel values, and to evaluate a quantitative measure and classification rule that exploits the full pixel frequency distribution of within object pixels (i.e., histogram signatures) compared to simple parametric statistical characteristics. High spatial resolution Quickbird satellite multispectral data of Accra, Ghana were evaluated in the context of mapping land cover and land use and socioeconomic status. Results show that image objects associated with land cover and land use types can have characteristic, non-normal frequency distributions (histograms). Signatures of most image objects tended to match closely the training signature of a single class or sub-class. Curve matching approaches to classifying multi-pixel frequency distributions were found to be slightly more effective than standard statistical classifiers based on a nearest neighbor classifier. PMID:22408575

  4. Active pixel sensor having intra-pixel charge transfer with analog-to-digital converter

    NASA Technical Reports Server (NTRS)

    Fossum, Eric R. (Inventor); Mendis, Sunetra K. (Inventor); Pain, Bedabrata (Inventor); Nixon, Robert H. (Inventor); Zhou, Zhimin (Inventor)

    2003-01-01

    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, a readout circuit including at least an output field effect transistor formed in the substrate, and a charge coupled device section formed on the substrate adjacent the photogate having a sensing node connected to the output transistor and at least one charge coupled device stage for transferring charge from the underlying portion of the substrate to the sensing node and an analog-to-digital converter formed in the substrate connected to the output of the readout circuit.

  5. Active pixel sensor having intra-pixel charge transfer with analog-to-digital converter

    NASA Technical Reports Server (NTRS)

    Fossum, Eric R. (Inventor); Mendis, Sunetra K. (Inventor); Pain, Bedabrata (Inventor); Nixon, Robert H. (Inventor); Zhou, Zhimin (Inventor)

    2000-01-01

    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, a readout circuit including at least an output field effect transistor formed in the substrate, and a charge coupled device section formed on the substrate adjacent the photogate having a sensing node connected to the output transistor and at least one charge coupled device stage for transferring charge from the underlying portion of the substrate to the sensing node and an analog-to-digital converter formed in the substrate connected to the output of the readout circuit.

  6. Pixelized Device Control Actuators for Large Adaptive Optics

    NASA Technical Reports Server (NTRS)

    Knowles, Gareth J.; Bird, Ross W.; Shea, Brian; Chen, Peter

    2009-01-01

    A fully integrated, compact, adaptive space optic mirror assembly has been developed, incorporating new advances in ultralight, high-performance composite mirrors. The composite mirrors use Q-switch matrix architecture-based pixelized control (PMN-PT) actuators, which achieve high-performance, large adaptive optic capability, while reducing the weight of present adaptive optic systems. The self-contained, fully assembled, 11x11x4-in. (approx.= 28x28x10-cm) unit integrates a very-high-performance 8-in. (approx.=20-cm) optic, and has 8-kHz true bandwidth. The assembled unit weighs less than 15 pounds (=6.8 kg), including all mechanical assemblies, power electronics, control electronics, drive electronics, face sheet, wiring, and cabling. It requires just three wires to be attached (power, ground, and signal) for full-function systems integration, and uses a steel-frame and epoxied electronics. The three main innovations are: 1. Ultralightweight composite optics: A new replication method for fabrication of very thin composite 20-cm-diameter laminate face sheets with good as-fabricated optical figure was developed. The approach is a new mandrel resin surface deposition onto previously fabricated thin composite laminates. 2. Matrix (regenerative) power topology: Waveform correction can be achieved across an entire face sheet at 6 kHz, even for large actuator counts. In practice, it was found to be better to develop a quadrant drive, that is, four quadrants of 169 actuators behind the face sheet. Each quadrant has a single, small, regenerative power supply driving all 169 actuators at 8 kHz in effective parallel. 3. Q-switch drive architecture: The Q-switch innovation is at the heart of the matrix architecture, and allows for a very fast current draw into a desired actuator element in 120 counts of a MHz clock without any actuator coupling.

  7. Characteristics of Monolithically Integrated InGaAs Active Pixel Imager Array

    NASA Technical Reports Server (NTRS)

    Kim, Q.; Cunningham, T. J.; Pain, B.; Lange, M. J.; Olsen, G. H.

    2000-01-01

    Switching and amplifying characteristics of a newly developed monolithic InGaAs Active Pixel Imager Array are presented. The sensor array is fabricated from InGaAs material epitaxially deposited on an InP substrate. It consists of an InGaAs photodiode connected to InP depletion-mode junction field effect transistors (JFETs) for low leakage, low power, and fast control of circuit signal amplifying, buffering, selection, and reset. This monolithically integrated active pixel sensor configuration eliminates the need for hybridization with silicon multiplexer. In addition, the configuration allows the sensor to be front illuminated, making it sensitive to visible as well as near infrared signal radiation. Adapting the existing 1.55 micrometer fiber optical communication technology, this integration will be an ideal system of optoelectronic integration for dual band (Visible/IR) applications near room temperature, for use in atmospheric gas sensing in space, and for target identification on earth. In this paper, two different types of small 4 x 1 test arrays will be described. The effectiveness of switching and amplifying circuits will be discussed in terms of circuit effectiveness (leakage, operating frequency, and temperature) in preparation for the second phase demonstration of integrated, two-dimensional monolithic InGaAs active pixel sensor arrays for applications in transportable shipboard surveillance, night vision, and emission spectroscopy.

  8. The NA62 Gigatracker pixel detector system

    NASA Astrophysics Data System (ADS)

    Mazza, G.; Ceccucci, A.; Cortina, E.; Cotta Ramusino, A.; Dellacasa, G.; Fiorini, M.; Garbolino, S.; Jarron, P.; Kaplon, J.; Kluge, A.; Marchetto, F.; Martin, E.; Martoiu, S.; Noy, M.; Petrucci, F.; Riedler, P.; Rivetti, A.; Tiuraniemi, S.

    2010-05-01

    The silicon tracker for the NA62 experiment has to provide both a time resolution of 150 ps rms and a space resolution of about 100 μm rms. These challenging specifications require the development of a new readout electronics in order to address the problem of measuring the tracks arrival time with such a high channel density. Moreover, the high particle density (up to 1.5 MHz/mm2 in the center and 0.8-1 GHz in total) requires a high speed measurement and data transmission in order to keep the dead time below 1%.

  9. Convolution-based estimation of organ dose in tube current modulated CT

    PubMed Central

    Tian, Xiaoyu; Segars, W Paul; Dixon, Robert L; Samei, Ehsan

    2016-01-01

    Estimating organ dose for clinical patients requires accurate modeling of the patient anatomy and the dose field of the CT exam. The modeling of patient anatomy can be achieved using a library of representative computational phantoms (Samei et al 2014 Pediatr. Radiol. 44 460–7). The modeling of the dose field can be challenging for CT exams performed with a tube current modulation (TCM) technique. The purpose of this work was to effectively model the dose field for TCM exams using a convolution-based method. A framework was further proposed for prospective and retrospective organ dose estimation in clinical practice. The study included 60 adult patients (age range: 18–70 years, weight range: 60–180 kg). Patient-specific computational phantoms were generated based on patient CT image datasets. A previously validated Monte Carlo simulation program was used to model a clinical CT scanner (SOMATOM Definition Flash, Siemens Healthcare, Forchheim, Germany). A practical strategy was developed to achieve real-time organ dose estimation for a given clinical patient. CTDIvol-normalized organ dose coefficients (hOrgan) under constant tube current were estimated and modeled as a function of patient size. Each clinical patient in the library was optimally matched to another computational phantom to obtain a representation of organ location/distribution. The patient organ distribution was convolved with a dose distribution profile to generate (CTDIvol)organ, convolution values that quantified the regional dose field for each organ. The organ dose was estimated by multiplying (CTDIvol)organ, convolution with the organ dose coefficients (hOrgan). To validate the accuracy of this dose estimation technique, the organ dose of the original clinical patient was estimated using Monte Carlo program with TCM profiles explicitly modeled. The discrepancy between the estimated organ dose and dose simulated using TCM Monte Carlo program was quantified. We further compared the

  10. Convolution-based estimation of organ dose in tube current modulated CT

    NASA Astrophysics Data System (ADS)

    Tian, Xiaoyu; Segars, W. Paul; Dixon, Robert L.; Samei, Ehsan

    2016-05-01

    Estimating organ dose for clinical patients requires accurate modeling of the patient anatomy and the dose field of the CT exam. The modeling of patient anatomy can be achieved using a library of representative computational phantoms (Samei et al 2014 Pediatr. Radiol. 44 460-7). The modeling of the dose field can be challenging for CT exams performed with a tube current modulation (TCM) technique. The purpose of this work was to effectively model the dose field for TCM exams using a convolution-based method. A framework was further proposed for prospective and retrospective organ dose estimation in clinical practice. The study included 60 adult patients (age range: 18-70 years, weight range: 60-180 kg). Patient-specific computational phantoms were generated based on patient CT image datasets. A previously validated Monte Carlo simulation program was used to model a clinical CT scanner (SOMATOM Definition Flash, Siemens Healthcare, Forchheim, Germany). A practical strategy was developed to achieve real-time organ dose estimation for a given clinical patient. CTDIvol-normalized organ dose coefficients ({{h}\\text{Organ}} ) under constant tube current were estimated and modeled as a function of patient size. Each clinical patient in the library was optimally matched to another computational phantom to obtain a representation of organ location/distribution. The patient organ distribution was convolved with a dose distribution profile to generate {{≤ft(\\text{CTD}{{\\text{I}}\\text{vol}}\\right)}\\text{organ, \\text{convolution}}} values that quantified the regional dose field for each organ. The organ dose was estimated by multiplying {{≤ft(\\text{CTD}{{\\text{I}}\\text{vol}}\\right)}\\text{organ, \\text{convolution}}} with the organ dose coefficients ({{h}\\text{Organ}} ). To validate the accuracy of this dose estimation technique, the organ dose of the original clinical patient was estimated using Monte Carlo program with TCM profiles explicitly modeled. The

  11. Hard x-ray response of pixellated CdZnTe detectors

    NASA Astrophysics Data System (ADS)

    Abbene, L.; Del Sordo, S.; Caroli, E.; Gerardi, G.; Raso, G.; Caccia, S.; Bertuccio, G.

    2009-06-01

    In recent years, the development of cadmium zinc telluride (CdZnTe) detectors for x-ray and gamma ray spectrometry has grown rapidly. The good room temperature performance and the high spatial resolution of pixellated CdZnTe detectors make them very attractive in space-borne x-ray astronomy, mainly as focal plane detectors for the new generation of hard x-ray focusing telescopes. In this work, we investigated on the spectroscopic performance of two pixellated CdZnTe detectors coupled with a custom low noise and low power readout application specific integrated circuit (ASIC). The detectors (10×10×1 and 10×10×2 mm3 single crystals) have an anode layout based on an array of 256 pixels with a geometric pitch of 0.5 mm. The ASIC, fabricated in 0.8 μm BiCMOS technology, is equipped with eight independent channels (preamplifier and shaper) and characterized by low power consumption (0.5 mW/channel) and low noise (150-500 electrons rms). The spectroscopic results point out the good energy resolution of both detectors at room temperature [5.8% full width at half maximum (FWHM) at 59.5 keV for the 1 mm thick detector; 5.5% FWHM at 59.5 keV for the 2 mm thick detector) and low tailing in the measured spectra, confirming the single charge carrier sensing properties of the CdZnTe detectors equipped with a pixellated anode layout. Temperature measurements show optimum performance of the system (detector and electronics) at T =10 °C and performance degradation at lower temperatures. The detectors and the ASIC were developed by our collaboration as two small focal plane detector prototypes for hard x-ray multilayer telescopes operating in the 20-70 keV energy range.

  12. Optical multi-token-ring networking using smart pixels with field programmable gate arrays (FPGAs)

    NASA Astrophysics Data System (ADS)

    Zhang, Liping; Hong, Sunkwang; Min, Changki; Alpaslan, Zahir Y.; Sawchuk, Alexander A.

    2001-12-01

    This research explores architectures and design principles for monolithic optoelectronic integrated circuits (OEICs) through the implementation of an optical multi-token-ring network testbed system. Monolithic smart pixel CMOS OEICs are of paramount importance to high performance networks, communication switches, computer interfaces, and parallel signal processing for demanding future multimedia applications. The general testbed system is called Reconfigurable Translucent Smart Pixel Array (R-Transpar) and includes a field programmable gate array (FPGA), a transimpedance receiver array, and an optoelectronic very large-scale integrated (OE-VLSI) smart pixel array. The FPGA is an Altera FLEX10K100E chip that performs logic functions and receives inputs from the transimpedance receiver array. A monolithic (OE-VLSI) smart pixel device containing an array of 4 X 4 vertical-cavity surface-emitting lasers (VCSELs) spatially interlaced with an array of 4 X 4 metal- semiconductor-metal (MSM) detectors connects to these devices and performs optical input-output functions. These components are mounted on a printed circuit board for testing and evaluation of integrated monolithic OEIC designs and various optical interconnection techniques. The system moves information between nodes by transferring 3-D optical packets in free space or through fiber image guides. The R-Transpar system is reconfigurable to test different network protocols and signal processing functions. In its operation as a 3-D multi-token-ring network, we use a specific version of the system called Transpar-Token-Ring (Transpar-TR) that uses novel time-division multiplexed (TDM) network node addressing to enhance channel utilization and throughput. Host computers interface with the system via a high-speed digital I/O board that sends commands for networking and application algorithm operations. We describe the system operation and experimental results in detail.

  13. Hard x-ray response of pixellated CdZnTe detectors

    SciTech Connect

    Abbene, L.; Caccia, S.; Bertuccio, G.

    2009-06-15

    In recent years, the development of cadmium zinc telluride (CdZnTe) detectors for x-ray and gamma ray spectrometry has grown rapidly. The good room temperature performance and the high spatial resolution of pixellated CdZnTe detectors make them very attractive in space-borne x-ray astronomy, mainly as focal plane detectors for the new generation of hard x-ray focusing telescopes. In this work, we investigated on the spectroscopic performance of two pixellated CdZnTe detectors coupled with a custom low noise and low power readout application specific integrated circuit (ASIC). The detectors (10x10x1 and 10x10x2 mm{sup 3} single crystals) have an anode layout based on an array of 256 pixels with a geometric pitch of 0.5 mm. The ASIC, fabricated in 0.8 mum BiCMOS technology, is equipped with eight independent channels (preamplifier and shaper) and characterized by low power consumption (0.5 mW/channel) and low noise (150-500 electrons rms). The spectroscopic results point out the good energy resolution of both detectors at room temperature [5.8% full width at half maximum (FWHM) at 59.5 keV for the 1 mm thick detector; 5.5% FWHM at 59.5 keV for the 2 mm thick detector) and low tailing in the measured spectra, confirming the single charge carrier sensing properties of the CdZnTe detectors equipped with a pixellated anode layout. Temperature measurements show optimum performance of the system (detector and electronics) at T=10 deg.C and performance degradation at lower temperatures. The detectors and the ASIC were developed by our collaboration as two small focal plane detector prototypes for hard x-ray multilayer telescopes operating in the 20-70 keV energy range.

  14. MOEMS for prospective space applications

    NASA Astrophysics Data System (ADS)

    Viard, Thierry; Buisset, Christophe; Zamkotsian, Frederic; Costes, Vincent; Venancio, Luis

    2011-02-01

    We are involved with ESA and CNES since several years, in the analysis of space applications using MOEMS components. A first concept using a Programmable Micro Diffracting Device (PMDG) has been proposed for an astronomical spectrometer with a small field of view. In this application the introduction of a MOEMS component has allowed to reduce the focal plane complexity (one mono detector) and to increase the mission adaptability to the target (programmable mission). An opto mechanical concept has been proposed and first performance assessed. A second concept has been studied and deals with the use of a MOEMS component to realize an innovative spectrometer, so-called convolution spectrometer. In the proposed solution, a MOEMS is used to realize a shifting spectral window (large spectral width) associated to a slight spectral increment. The signal given by the detector being the convolution between the target spectral density and the spectral window, it is then possible to recover the target spectral signal by a deconvolution. A breadboard has been developed, and the concept of the convolution spectrometer has been successfully demonstrated. Finally, some results of analysis will be also given concerning the use of a DMD for Earth observation associated to a push broom detection mode and a large field of view.

  15. CMOS in-pixel optical pulse frequency modulator

    NASA Astrophysics Data System (ADS)

    Nel, Nicolaas E.; du Plessis, M.; Joubert, T.-H.

    2016-02-01

    This paper covers the design of a complementary metal oxide semiconductor (CMOS) pixel readout circuit with a built-in frequency conversion feature. The pixel contains a CMOS photo sensor along with all signal-to-frequency conversion circuitry. An 8×8 array of these pixels is also designed. Current imaging arrays often use analog-to-digital conversion (ADC) and digital signal processing (DSP) techniques that are off-chip1. The frequency modulation technique investigated in this paper is preferred over other ADC techniques due to its smaller size, and the possibility of a higher dynamic range. Careful considerations are made regarding the size of the components of the pixel, as various characteristics of CMOS devices are limited by decreasing the scale of the components2. The methodology used was the CMOS design cycle for integrated circuit design. All components of the pixel were designed from first principles to meet necessary requirements of a small pixel size (30×30 μm2) and an output resolution greater than that of an 8-bit ADC. For the photodetector, an n+-p+/p-substrate diode was designed with a parasitic capacitance of 3 fF. The analog front-end stage was designed around a Schmitt trigger circuit. The photo current is integrated on an integration capacitor of 200 fF, which is reset when the Schmitt trigger output voltage exceeds a preset threshold. The circuit schematic and layout were designed using Cadence Virtuoso and the process used was the AMS CMOS 350 nm process using a power supply of 5V. The simulation results were confirmed to comply with specifications, and the layout passed all verification checks. The dynamic range achieved is 58.828 dB per pixel, with the output frequencies ranging from 12.341kHz to 10.783 MHz. It is also confirmed that the output frequency has a linear relationship to the photocurrent generated by the photodiode.

  16. VeloPix: the pixel ASIC for the LHCb upgrade

    NASA Astrophysics Data System (ADS)

    Poikela, T.; De Gaspari, M.; Plosila, J.; Westerlund, T.; Ballabriga, R.; Buytaert, J.; Campbell, M.; Llopart, X.; Wyllie, K.; Gromov, V.; van Beuzekom, M.; Zivkovic, V.

    2015-01-01

    The LHCb Vertex Detector (VELO) will be upgraded in 2018 along with the other subsystems of LHCb in order to enable full readout at 40 MHz, with the data fed directly to the software triggering algorithms. The upgraded VELO is a lightweight hybrid pixel detector operating in vacuum in close proximity to the LHC beams. The readout will be provided by a dedicated front-end ASIC, dubbed VeloPix, matched to the LHCb readout requirements and the 55 × 55 μm VELO pixel dimensions. The chip is closely related to the Timepix3, from the Medipix family of ASICs. The principal challenge that the chip has to meet is a hit rate of up to 900 Mhits/s, resulting in a required output bandwidth of more than 16 Gbit/s. The occupancy across the chip is also very non-uniform, and the radiation levels reach an integrated 400 Mrad over the lifetime of the detector.VeloPix is a binary pixel readout chip with a data driven readout, designed in 130 nm CMOS technology. The pixels are combined into groups of 2 × 4 super pixels, enabling a shared logic and a reduction of bandwidth due to combined address and time stamp information. The pixel hits are combined with other simultaneous hits in the same super pixel, time stamped, and immediately driven off-chip. The analog front-end must be sufficiently fast to accurately time stamp the data, with a small enough dead time to minimize data loss in the most occupied regions of the chip. The data is driven off chip with a custom designed high speed serialiser. The current status of the ASIC design, the chip architecture and the simulations will be described.

  17. Pixel Analysis of Photospheric Spectral Data. I. Plasma Dynamics

    NASA Astrophysics Data System (ADS)

    Rasca, Anthony P.; Chen, James; Pevtsov, Alexei A.

    2016-11-01

    Recent observations of the photosphere using high spatial and temporal resolution show small dynamic features at or below the current resolving limits. A new pixel dynamics method has been developed to analyze spectral profiles and quantify changes in line displacement, width, asymmetry, and peakedness of photospheric absorption lines. The algorithm evaluates variations of line profile properties in each pixel and determines the statistics of such fluctuations averaged over all pixels in a given region. The method has been used to derive statistical characteristics of pixel fluctuations in observed quiet-Sun regions, an active region with no eruption, and an active region with an ongoing eruption. Using Stokes I images from the Vector Spectromagnetograph (VSM) of the Synoptic Optical Long-term Investigations of the Sun (SOLIS) telescope on 2012 March 13, variations in line width and peakedness of Fe i 6301.5 Å are shown to have a distinct spatial and temporal relationship with an M7.9 X-ray flare in NOAA 11429. This relationship is observed as stationary and contiguous patches of pixels adjacent to a sunspot exhibiting intense flattening in the line profile and line-center displacement as the X-ray flare approaches peak intensity, which is not present in area scans of the non-eruptive active region. The analysis of pixel dynamics allows one to extract quantitative information on differences in plasma dynamics on sub-pixel scales in these photospheric regions. The analysis can be extended to include the Stokes parameters and study signatures of vector components of magnetic fields and coupled plasma properties.

  18. Position and Orientation Distributions for Non-Reversal Random Walks using Space-Group Fourier Transforms

    PubMed Central

    Skliros, Aris; Park, Wooram; Chirikjian, Gregory S.

    2010-01-01

    This paper presents an efficient group-theoretic approach for computing the statistics of non-reversal random walks (NRRW) on lattices. These framed walks evolve on proper crystallographic space groups. In a previous paper we introduced a convolution method for computing the statistics of NRRWs in which the convolution product is defined relative to the space-group operation. Here we use the corresponding concept of the fast Fourier transform for functions on crystallographic space groups together with a non-Abelian version of the convolution theorem. We develop the theory behind this technique and present numerical results for two-dimensional and three-dimensional lattices (square, cubic and diamond). In order to verify our results, the statistics of the end-to-end distance and the probability of ring closure are calculated and compared with results obtained in the literature for the random walks for which closed-form expressions exist. PMID:21037950

  19. Visual mining business service using pixel bar charts

    NASA Astrophysics Data System (ADS)

    Hao, Ming C.; Dayal, Umeshwar; Casati, Fabio

    2004-06-01

    Basic bar charts have been commonly available, but they only show highly aggregated data. Finding the valuable information hidden in the data is essential to the success of business. We describe a new visualization technique called pixel bar charts, which are derived from regular bar charts. The basic idea of a pixel bar chart is to present all data values directly instead of aggregating them into a few data values. Pixel bar charts provide data distribution and exceptions besides aggregated data. The approach is to represent each data item (e.g. a business transaction) by a single pixel in the bar chart. The attribute of each data item is encoded into the pixel color and can be accessed and drilled down to the detail information as needed. Different color mappings are used to represent multiple attributes. This technique has been prototyped in three business service applications-Business Operation Analysis, Sales Analysis, and Service Level Agreement Analysis at Hewlett Packard Laboratories. Our applications show the wide applicability and usefulness of this new idea.

  20. The pixel tracking telescope at the Fermilab Test Beam Facility

    SciTech Connect

    Kwan, Simon; Lei, CM; Menasce, Dario; Moroni, Luigi; Ngadiuba, Jennifer; Prosser, Alan; Rivera, Ryan; Terzo, Stefano; Turqueti, Marcos; Uplegger, Lorenzo; Vigani, Luigi; Dinardo, Mauro E.

    2016-03-01

    An all silicon pixel telescope has been assembled and used at the Fermilab Test Beam Facility (FTBF) since 2009 to provide precise tracking information for different test beam experiments with a wide range of Detectors Under Test (DUTs) requiring high resolution measurement of the track impact point. The telescope is based on CMS pixel modules left over from the CMS forward pixel production. Eight planes are arranged to achieve a resolution of less than 8 μm on the 120 GeV proton beam transverse coordinate at the DUT position. In order to achieve such resolution with 100 × 150 μm2 pixel cells, the planes were tilted to 25 degrees to maximize charge sharing between pixels. Crucial for obtaining this performance is the alignment software, called Monicelli, specifically designed and optimized for this system. This paper will describe the telescope hardware, the data acquisition system and the alignment software constituting this particle tracking system for test beam users.

  1. Super pixel density based clustering automatic image classification method

    NASA Astrophysics Data System (ADS)

    Xu, Mingxing; Zhang, Chuan; Zhang, Tianxu

    2015-12-01

    The image classification is an important means of image segmentation and data mining, how to achieve rapid automated image classification has been the focus of research. In this paper, based on the super pixel density of cluster centers algorithm for automatic image classification and identify outlier. The use of the image pixel location coordinates and gray value computing density and distance, to achieve automatic image classification and outlier extraction. Due to the increased pixel dramatically increase the computational complexity, consider the method of ultra-pixel image preprocessing, divided into a small number of super-pixel sub-blocks after the density and distance calculations, while the design of a normalized density and distance discrimination law, to achieve automatic classification and clustering center selection, whereby the image automatically classify and identify outlier. After a lot of experiments, our method does not require human intervention, can automatically categorize images computing speed than the density clustering algorithm, the image can be effectively automated classification and outlier extraction.

  2. Pixel-feature hybrid fusion for PET/CT images.

    PubMed

    Zhu, Yang-Ming; Nortmann, Charles A

    2011-02-01

    Color blending is a popular display method for functional and anatomic image fusion. The underlay image is typically displayed in grayscale, and the overlay image is displayed in pseudo colors. This pixel-level fusion provides too much information for reviewers to analyze quickly and effectively and clutters the display. To improve the fusion image reviewing speed and reduce the information clutter, a pixel-feature hybrid fusion method is proposed and tested for PET/CT images. Segments of the colormap are selectively masked to have a few discrete colors, and pixels displayed in the masked colors are made transparent. The colormap thus creates a false contouring effect on overlay images and allows the underlay to show through to give contours an anatomic context. The PET standardized uptake value (SUV) is used to control where colormap segments are masked. Examples show that SUV features can be extracted and blended with CT image instantaneously for viewing and diagnosis, and the non-feature part of the PET image is transparent. The proposed pixel-feature hybrid fusion highlights PET SUV features on CT images and reduces display clutters. It is easy to implement and can be used as complementarily to existing pixel-level fusion methods.

  3. Pixel classification based color image segmentation using quaternion exponent moments.

    PubMed

    Wang, Xiang-Yang; Wu, Zhi-Fang; Chen, Liang; Zheng, Hong-Liang; Yang, Hong-Ying

    2016-02-01

    Image segmentation remains an important, but hard-to-solve, problem since it appears to be application dependent with usually no a priori information available regarding the image structure. In recent years, many image segmentation algorithms have been developed, but they are often very complex and some undesired results occur frequently. In this paper, we propose a pixel classification based color image segmentation using quaternion exponent moments. Firstly, the pixel-level image feature is extracted based on quaternion exponent moments (QEMs), which can capture effectively the image pixel content by considering the correlation between different color channels. Then, the pixel-level image feature is used as input of twin support vector machines (TSVM) classifier, and the TSVM model is trained by selecting the training samples with Arimoto entropy thresholding. Finally, the color image is segmented with the trained TSVM model. The proposed scheme has the following advantages: (1) the effective QEMs is introduced to describe color image pixel content, which considers the correlation between different color channels, (2) the excellent TSVM classifier is utilized, which has lower computation time and higher classification accuracy. Experimental results show that our proposed method has very promising segmentation performance compared with the state-of-the-art segmentation approaches recently proposed in the literature.

  4. Multiport solid-state imager characterization at variable pixel rates

    SciTech Connect

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

    1993-08-01

    The imaging performance of an 8-port Full Frame Transfer Charge Coupled Device (FFT CCD) as a function of several parameters including pixel clock rate is presented. The device, model CCD- 13, manufactured by English Electric Valve (EEV) is a 512 {times} 512 pixel array designed with four individual programmable bidirectional serial registers and eight output amplifiers permitting simultaneous readout of eight segments (128 horizontal {times} 256 vertical pixels) of the array. The imager was evaluated in Los Alamos National Laboratory`s High-Speed Solid-State Imager Test Station at true pixel rates as high as 50 MHz for effective imager pixel rates approaching 400 MHz from multiporting. Key response characteristics measured include absolute responsivity, Charge-Transfer-Efficiency (CTE), dynamic range, resolution, signal-to-noise ratio, and electronic and optical crosstalk among the eight video channels. Preliminary test results and data obtained from the CCD-13 will be presented and the versatility/capabilities of the test station will be reviewed.

  5. Fabrication and performance of mercuric iodide pixellated detectors

    NASA Astrophysics Data System (ADS)

    van den Berg, Lodewijk; Bastian, Lloyd F.; Zhang, Feng; Lenos, Howard; Capote, M. Albert

    2007-09-01

    The radiation detection efficiency and spectral resolution of mercuric iodide detectors can be improved significantly by increasing the volume of the detectors and by using a pixellated anode structure. Detector bodies with a thickness of nominally 10 mm and an active area of approximately 14 mm x 14 mm have been used for these experiments. The detectors were cut from single crystals grown by the physical vapor transport method. The cut surfaces were polished and etched using a string saw and potassium iodide solutions. The Palladium contacts were deposited by magnetron sputtering through stainless steel masks. The cathode contact is continuous; the anode contacts consist of an array of 11 x 11 pixels surrounded by a guard ring. The resistance between a pixel and its surrounding contacts should be larger than 0.25 Gohm. The detector is mounted on a substrate that makes it possible to connect the anode pixels to an ASIC, and is conditioned so that it is stable for all pixels at a bias of -3000 Volts. Under these conditions the spectral resolution for Cs-137 gamma rays (662 keV) is approximately 5% FWHM. When depth sensing correction methods are applied, the resolution improves to about 2% FWHM or better. It is expected that the performance of the devices can be improved by the careful selection of crystal parts that are free of structural defects. Details of the fabrication technologies will be described. The effects of material inhomogeneities and transport properties of the charge carriers will be discussed.

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  7. The HEXITEC hard x-ray pixelated CdTe imager for fast solar observations

    NASA Astrophysics Data System (ADS)

    Baumgartner, Wayne H.; Christe, Steven D.; Ryan, Daniel F.; Inglis, Andrew R.; Shih, Albert Y.; Gregory, Kyle; Wilson, Matt; Seller, Paul; Gaskin, Jessica; Wilson-Hodge, Colleen

    2016-08-01

    There is an increasing demand in solar and astrophysics for high resolution X-ray spectroscopic imaging. Such observations would present ground breaking opportunities to study the poorly understood high energy processes in our solar system and beyond, such as solar flares, X-ray binaries, and active galactic nuclei. However, such observations require a new breed of solid state detectors sensitive to high energy X-rays with fine independent pixels to sub-sample the point spread function (PSF) of the X-ray optics. For solar observations in particular, they must also be capable of handling very high count rates as photon fluxes from solar flares often cause pile up and saturation in present generation detectors. The Rutherford Appleton Laboratory (RAL) has recently developed a new cadmium telluride (CdTe) detector system, called HEXITEC (High Energy X-ray Imaging Technology). It is an 8080 array of 250 μm independent pixels sensitive in the 2-200 keV band and capable of a high full frame read out rate of 10 kHz. HEXITEC provides the smallest independently read out CdTe pixels currently available, and are well matched to the few arcsecond PSF produced by current and next generation hard X-ray focusing optics. NASA's Goddard and Marshall Space Flight Centers are collaborating with RAL to develop these detectors for use on future space borne hard X-ray focusing telescopes. We show the latest results on HEXITEC's imaging capability, energy resolution, high read out rate, and reveal it to be ideal for such future instruments.

  8. Planar pixel sensors for the ATLAS upgrade: beam tests results

    NASA Astrophysics Data System (ADS)

    Weingarten, J.; Altenheiner, S.; Beimforde, M.; Benoit, M.; Bomben, M.; Calderini, G.; Gallrapp, C.; George, M.; Gibson, S.; Grinstein, S.; Janoska, Z.; Jentzsch, J.; Jinnouchi, O.; Kishida, T.; La Rosa, A.; Libov, V.; Macchiolo, A.; Marchiori, G.; Muenstermann, D.; Nagai, R.; Piacquadio, G.; Ristic, B.; Rubinskiy, I.; Rummler, A.; Takubo, Y.; Troska, G.; Tsiskaridtze, S.; Tsurin, I.; Unno, Y.; Weigell, P.; Wittig, T.

    2012-10-01

    The performance of planar silicon pixel sensors, in development for the ATLAS Insertable B-Layer and High Luminosity LHC (HL-LHC) upgrades, has been examined in a series of beam tests at the CERN SPS facilities since 2009. Salient results are reported on the key parameters, including the spatial resolution, the charge collection and the charge sharing between adjacent cells, for different bulk materials and sensor geometries. Measurements are presented for n+-in-n pixel sensors irradiated with a range of fluences and for p-type silicon sensors with various layouts from different vendors. All tested sensors were connected via bump-bonding to the ATLAS Pixel read-out chip. The tests reveal that both n-type and p-type planar sensors are able to collect significant charge even after the lifetime fluence expected at the HL-LHC.

  9. The Phase-1 upgrade of the CMS pixel detector

    NASA Astrophysics Data System (ADS)

    Klein, Katja

    2017-02-01

    The CMS experiment features a pixel detector with three barrel layers and two discs per side, corresponding to an active silicon area of 1 m2. The detector delivered high-quality data during LHC Run 1. However, the CMS pixel detector was designed for the nominal instantaneous LHC luminosity of 1 ·1034cm-2s-1 . It is expected that the instantaneous luminosity will increase and reach twice the design value before Long Shutdown 3, scheduled for 2023. Under such conditions, the present readout chip would suffer from data loss due to buffer overflow, leading to significant inefficiencies of up to 16%. The CMS collaboration is presently constructing a new pixel detector to replace the present device during the winter shutdown 2016/2017. The design of this new detector will be outlined, the construction status summarized and the performance described.

  10. Visual mining geo-related data using pixel bar charts

    NASA Astrophysics Data System (ADS)

    Hao, Ming C.; Keim, Daniel A.; Dayal, Umeshwar; Wright, Peter; Schneidewind, Joern

    2005-03-01

    A common approach to analyze geo-related data is using bar charts or x-y plots. They are intuitive and easy to use. But important information often gets lost. In this paper, we introduce a new interactive visualization technique called Geo Pixel Bar Charts, which combines the advantages of Pixel Bar Charts and interactive maps. This technique allows analysts to visualize large amounts of spatial data without aggregation and shows the geographical regions corresponding to the spatial data attribute at the same time. In this paper, we apply Geo Pixel Bar Charts to visually mining sales transactions and Internet usage from different locations. Our experimental results show the effectiveness of this technique for providing data distribution and exceptions from the map.

  11. Virus based Full Colour Pixels using a Microheater

    PubMed Central

    Kim, Won-Geun; Kim, Kyujung; Ha, Sung-Hun; Song, Hyerin; Yu, Hyun-Woo; Kim, Chuntae; Kim, Jong-Man; Oh, Jin-Woo

    2015-01-01

    Mimicking natural structures has been received considerable attentions, and there have been a few practical advances. Tremendous efforts based on a self-assembly technique have been contributed to the development of the novel photonic structures which are mimicking nature’s inventions. We emulate the photonic structures from an origin of colour generation of mammalian skins and avian skin/feathers using M13 phage. The structures can be generated a full range of RGB colours that can be sensitively switched by temperature and substrate materials. Consequently, we developed an M13 phage-based temperature-dependent actively controllable colour pixels platform on a microheater chip. Given the simplicity of the fabrication process, the low voltage requirements and cycling stability, the virus colour pixels enable us to substitute for conventional colour pixels for the development of various implantable, wearable and flexible devices in future. PMID:26334322

  12. Wire Bond Encapsulation for the CMS Forward Pixel Upgrade

    NASA Astrophysics Data System (ADS)

    Higginbotham, Sam; CMS Collaboration

    2015-04-01

    The Phase 1 upgrade of the pixel tracker for the CMS experiment will require the assembly of approximately 1000 modules consisting of pixel sensors bump bonded to readout chips. Electrical connections between the custom readout chips and support ASIC's that constitute the front-end of the pixel data acquisition system are made via wire bonds to a thin printed circuit board. Part of the assembly process carried out at Purdue University includes the partial encapsulation of the wire bonds for mechanical protection, prevention of electrolytic corrosion, and to damp oscillations due to Lorentz forces from transient current pulses in large magnetic fields. We present the details of the robotic assembly process which allows the deposition of the viscous encapsulant compound with 100 micron precision.

  13. Acousto-optic imaging with a smart-pixels sensor

    NASA Astrophysics Data System (ADS)

    Barjean, K.; Contreras, K.; Laudereau, J.-B.; Tinet, E.; Ettori, D.; Ramaz, F.; Tualle, J.-M.

    2015-03-01

    Acousto-optic imaging (AOI) is an emerging technique in the field of biomedical optics which combines the optical contrast allowed by diffuse optical tomography with the resolution of ultrasound (US) imaging. In this work we report the implementation, for that purpose, of a CMOS smart-pixels sensor dedicated to the real-time analysis of speckle patterns. We implemented a highly sensitive lock-in detection in each pixel in order to extract the tagged photons after an appropriate in-pixel post-processing. With this system we can acquire images in scattering samples with a spatial resolution in the 2mm range, with an integration time compatible with the dynamic of living biological tissue.

  14. Calibration analysis software for the ATLAS Pixel Detector

    NASA Astrophysics Data System (ADS)

    Stramaglia, Maria Elena

    2016-07-01

    The calibration of the ATLAS Pixel Detector at LHC fulfils two main purposes: to tune the front-end configuration parameters for establishing the best operational settings and to measure the tuning performance through a subset of scans. An analysis framework has been set up in order to take actions on the detector given the outcome of a calibration scan (e.g. to create a mask for disabling noisy pixels). The software framework to control all aspects of the Pixel Detector scans and analyses is called calibration console. The introduction of a new layer, equipped with new FE-I4 chips, required an update of the console architecture. It now handles scans and scan analyses applied together to chips with different characteristics. An overview of the newly developed calibration analysis software will be presented, together with some preliminary results.

  15. Leakage current measurements of a pixelated polycrystalline CVD diamond detector

    NASA Astrophysics Data System (ADS)

    Zain, R. M.; Maneuski, D.; O'Shea, V.; Bates, R.; Blue, A.; Cunnigham, L.; Stehl, C.; Berderman, E.; Rahim, R. A.

    2013-01-01

    Diamond has several desirable features when used as a material for radiation detection. With the invention of synthetic growth techniques, it has become feasible to look at developing diamond radiation detectors with reasonable surface areas. Polycrystalline diamond has been grown using a chemical vapour deposition (CVD) technique by the University of Augsburg and detector structures fabricated at the James Watt Nanofabrication Centre (JWNC) in the University of Glasgow in order to produce pixelated detector arrays. The anode and cathode contacts are realised by depositing gold to produce ohmic contacts. Measurements of I-V characteristics were performed to study the material uniformity. The bias voltage is stepped from -1000V to 1000V to investigate the variation of leakage current from pixel to pixel. Bulk leakage current is measured to be less than 1nA.

  16. Testbeam and laboratory characterization of CMS 3D pixel sensors

    NASA Astrophysics Data System (ADS)

    Bubna, M.; Bortoletto, D.; Alagoz, E.; Krzywda, A.; Arndt, K.; Shipsey, I.; Bolla, G.; Hinton, N.; Kok, A.; Hansen, T.-E.; Summanwar, A.; Brom, J. M.; Boscardin, M.; Chramowicz, J.; Cumalat, J.; Dalla Betta, G. F.; Dinardo, M.; Godshalk, A.; Jones, M.; Krohn, M. D.; Kumar, A.; Lei, C. M.; Mendicino, R.; Moroni, L.; Perera, L.; Povoli, M.; Prosser, A.; Rivera, R.; Solano, A.; Obertino, M. M.; Kwan, S.; Uplegger, L.; Vigani, L.; Wagner, S.

    2014-07-01

    The pixel detector is the innermost tracking device in CMS, reconstructing interaction vertices and charged particle trajectories. The sensors located in the innermost layers of the pixel detector must be upgraded for the ten-fold increase in luminosity expected at the High-Luminosity LHC (HL-LHC). As a possible replacement for planar sensors, 3D silicon technology is under consideration due to its good performance after high radiation fluence. In this paper, we report on pre- and post- irradiation measurements of CMS 3D pixel sensors with different electrode configurations from different vendors. The effects of irradiation on electrical properties, charge collection efficiency, and position resolution are discussed. Measurements of various test structures for monitoring the fabrication process and studying the bulk and surface properties of silicon sensors, such as MOS capacitors, planar and gate-controlled diodes are also presented.

  17. Silicon pixel detector prototyping in SOI CMOS technology

    NASA Astrophysics Data System (ADS)

    Dasgupta, Roma; Bugiel, Szymon; Idzik, Marek; Kapusta, Piotr; Kucewicz, Wojciech; Turala, Michal

    2016-12-01

    The Silicon-On-Insulator (SOI) CMOS is one of the most advanced and promising technology for monolithic pixel detectors design. The insulator layer that is implemented inside the silicon crystal allows to integrate sensors matrix and readout electronic on a single wafer. Moreover, the separation of electronic and substrate increases also the SOI circuits performance. The parasitic capacitances to substrate are significantly reduced, so the electronic systems are faster and consume much less power. The authors of this presentation are the members of international SOIPIX collaboration, that is developing SOI pixel detectors in 200 nm Lapis Fully-Depleted, Low-Leakage SOI CMOS. This work shows a set of advantages of SOI technology and presents possibilities for pixel detector design SOI CMOS. In particular, the preliminary results of a Cracow chip are presented.

  18. Simulation of Caliste-SO single pixel response

    NASA Astrophysics Data System (ADS)

    Barylak, J.; Barylak, A.; Mrozek, T.; Podgórski, P.; Steślicki, M.; Ścisłowski, D.

    2016-09-01

    The paper presents a method for determining the pixel response using Geant4 package. The response is calculated for cadmium telluride sensor of Caliste-SO detector. Caliste-SO will be used in STIX instrument on board Solar Orbiter, which is M-class mission of the ESA's program Cosmic Vision 2015-2025. Solar Orbiter is to be launched in October 2018. STIX instrument will provide imaging spectroscopy of solar hard X-ray emissions (4 - 150 keV) using a Fourier-imaging technique. Response of pixels in pixelized Caliste-SO detector vary between each other due to different sizes and locations. This can influence the scientific data obtained from STIX. Additionally, in the simulation we considered detector effects, like: hole tailing, damage layer, Fano and electronic noise.

  19. Performance of the INTPIX6 SOI pixel detector

    NASA Astrophysics Data System (ADS)

    Arai, Y.; Bugiel, Sz.; Dasgupta, R.; Idzik, M.; Kapusta, P.; Kucewicz, W.; Miyoshi, T.; Turala, M.

    2017-01-01

    Characterization of the monolithic pixel detector INPTIX6, designed at KEK and fabricated in Lapis 0.2 μ m Fully-Depleted, Low-Leakage Silicon-On-Insulator (SOI) CMOS technology, was performed. The INTPIX6 comprises a large area of 1408 × 896 integrating type squared pixels of 12 micron pitch. In this work the performance and measurement results of the prototypes produced on lower resistivity Czochralski type (CZ-n) and high resistivity floating zone (FZ-n) sensor wafers are presented. Using 241Am radioactive source the noise of INTPIX6 was measured, showing the ENC (Equivalent Noise Charge) of about 70 e-. The resolution calculated from the FWHM of the Iron-55 X-ray peak was about 100 e-. The radiation hardness of the SOI pixel detector was also investigated. The CZ-n type INTPIX6 received a dose of 60 krad and its performance has been continuously monitored during the irradiation.

  20. Virus based Full Colour Pixels using a Microheater

    NASA Astrophysics Data System (ADS)

    Kim, Won-Geun; Kim, Kyujung; Ha, Sung-Hun; Song, Hyerin; Yu, Hyun-Woo; Kim, Chuntae; Kim, Jong-Man; Oh, Jin-Woo

    2015-09-01

    Mimicking natural structures has been received considerable attentions, and there have been a few practical advances. Tremendous efforts based on a self-assembly technique have been contributed to the development of the novel photonic structures which are mimicking nature’s inventions. We emulate the photonic structures from an origin of colour generation of mammalian skins and avian skin/feathers using M13 phage. The structures can be generated a full range of RGB colours that can be sensitively switched by temperature and substrate materials. Consequently, we developed an M13 phage-based temperature-dependent actively controllable colour pixels platform on a microheater chip. Given the simplicity of the fabrication process, the low voltage requirements and cycling stability, the virus colour pixels enable us to substitute for conventional colour pixels for the development of various implantable, wearable and flexible devices in future.