Feature-Enhanced, Model-Based Sparse Aperture Imaging

DTIC Science & Technology

2008-03-01

See additional restrictions described on inside pages STINFO COPY AIR FORCE RESEARCH LABORATORY SENSORS DIRECTORATE WRIGHT...AND ADDRESS(ES) 8. PERFORMING ORGANIZATION Massachusetts Institute of Technology Laboratory for Information and Decision Systems 77 Massachusetts...Avenue Cambridge, MA 02139 REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) Air Force Research Laboratory 10

High dynamic range coding imaging system

NASA Astrophysics Data System (ADS)

Wu, Renfan; Huang, Yifan; Hou, Guangqi

2014-10-01

We present a high dynamic range (HDR) imaging system design scheme based on coded aperture technique. This scheme can help us obtain HDR images which have extended depth of field. We adopt Sparse coding algorithm to design coded patterns. Then we utilize the sensor unit to acquire coded images under different exposure settings. With the guide of the multiple exposure parameters, a series of low dynamic range (LDR) coded images are reconstructed. We use some existing algorithms to fuse and display a HDR image by those LDR images. We build an optical simulation model and get some simulation images to verify the novel system.

Sparse aperture endoscope

DOEpatents

Fitch, J.P.

1999-07-06

An endoscope is disclosed which reduces the volume needed by the imaging part, maintains resolution of a wide diameter optical system, while increasing tool access, and allows stereographic or interferometric processing for depth and perspective information/visualization. Because the endoscope decreases the volume consumed by imaging optics such allows a larger fraction of the volume to be used for non-imaging tools, which allows smaller incisions in surgical and diagnostic medical applications thus produces less trauma to the patient or allows access to smaller volumes than is possible with larger instruments. The endoscope utilizes fiber optic light pipes in an outer layer for illumination, a multi-pupil imaging system in an inner annulus, and an access channel for other tools in the center. The endoscope is amenable to implementation as a flexible scope, and thus increases it's utility. Because the endoscope uses a multi-aperture pupil, it can also be utilized as an optical array, allowing stereographic and interferometric processing. 7 figs.

Sparse aperture endoscope

DOEpatents

Fitch, Joseph P.

1999-07-06

An endoscope which reduces the volume needed by the imaging part thereof, maintains resolution of a wide diameter optical system, while increasing tool access, and allows stereographic or interferometric processing for depth and perspective information/visualization. Because the endoscope decreases the volume consumed by imaging optics such allows a larger fraction of the volume to be used for non-imaging tools, which allows smaller incisions in surgical and diagnostic medical applications thus produces less trauma to the patient or allows access to smaller volumes than is possible with larger instruments. The endoscope utilizes fiber optic light pipes in an outer layer for illumination, a multi-pupil imaging system in an inner annulus, and an access channel for other tools in the center. The endoscope is amenable to implementation as a flexible scope, and thus increases the utility thereof. Because the endoscope uses a multi-aperture pupil, it can also be utilized as an optical array, allowing stereographic and interferometric processing.

Sparse and redundant representations for inverse problems and recognition

NASA Astrophysics Data System (ADS)

Patel, Vishal M.

Sparse and redundant representation of data enables the description of signals as linear combinations of a few atoms from a dictionary. In this dissertation, we study applications of sparse and redundant representations in inverse problems and object recognition. Furthermore, we propose two novel imaging modalities based on the recently introduced theory of Compressed Sensing (CS). This dissertation consists of four major parts. In the first part of the dissertation, we study a new type of deconvolution algorithm that is based on estimating the image from a shearlet decomposition. Shearlets provide a multi-directional and multi-scale decomposition that has been mathematically shown to represent distributed discontinuities such as edges better than traditional wavelets. We develop a deconvolution algorithm that allows for the approximation inversion operator to be controlled on a multi-scale and multi-directional basis. Furthermore, we develop a method for the automatic determination of the threshold values for the noise shrinkage for each scale and direction without explicit knowledge of the noise variance using a generalized cross validation method. In the second part of the dissertation, we study a reconstruction method that recovers highly undersampled images assumed to have a sparse representation in a gradient domain by using partial measurement samples that are collected in the Fourier domain. Our method makes use of a robust generalized Poisson solver that greatly aids in achieving a significantly improved performance over similar proposed methods. We will demonstrate by experiments that this new technique is more flexible to work with either random or restricted sampling scenarios better than its competitors. In the third part of the dissertation, we introduce a novel Synthetic Aperture Radar (SAR) imaging modality which can provide a high resolution map of the spatial distribution of targets and terrain using a significantly reduced number of needed transmitted and/or received electromagnetic waveforms. We demonstrate that this new imaging scheme, requires no new hardware components and allows the aperture to be compressed. Also, it presents many new applications and advantages which include strong resistance to countermesasures and interception, imaging much wider swaths and reduced on-board storage requirements. The last part of the dissertation deals with object recognition based on learning dictionaries for simultaneous sparse signal approximations and feature extraction. A dictionary is learned for each object class based on given training examples which minimize the representation error with a sparseness constraint. A novel test image is then projected onto the span of the atoms in each learned dictionary. The residual vectors along with the coefficients are then used for recognition. Applications to illumination robust face recognition and automatic target recognition are presented.

Prototype Development of a Geostationary Synthetic Thinned Aperture Radiometer, GeoSTAR

NASA Technical Reports Server (NTRS)

Tanner, Alan B.; Wilson, William J.; Kangaslahti, Pekka P.; Lambrigsten, Bjorn H.; Dinardo, Steven J.; Piepmeier, Jeffrey R.; Ruf, Christopher S.; Rogacki, Steven; Gross, S. M.; Musko, Steve

2004-01-01

Preliminary details of a 2-D synthetic aperture radiometer prototype operating from 50 to 58 GHz will be presented. The instrument is being developed as a laboratory testbed, and the goal of this work is to demonstrate the technologies needed to do atmospheric soundings with high spatial resolution from Geostationary orbit. The concept is to deploy a large sparse aperture Y-array from a geostationary satellite, and to use aperture synthesis to obtain images of the earth without the need for a large mechanically scanned antenna. The laboratory prototype consists of a Y-array of 24 horn antennas, MMIC receivers, and a digital cross-correlation sub-system. System studies are discussed, including an error budget which has been derived from numerical simulations. The error budget defines key requirements, such as null offsets, phase calibration, and antenna pattern knowledge. Details of the instrument design are discussed in the context of these requirements.

GF-3 SAR Image Despeckling Based on the Improved Non-Local Means Using Non-Subsampled Shearlet Transform

NASA Astrophysics Data System (ADS)

Shi, R.; Sun, Z.

2018-04-01

GF-3 synthetic aperture radar (SAR) images are rich in information and have obvious sparse features. However, the speckle appears in the GF-3 SAR images due to the coherent imaging system and it hinders the interpretation of images seriously. Recently, Shearlet is applied to the image processing with its best sparse representation. A new Shearlet-transform-based method is proposed in this paper based on the improved non-local means. Firstly, the logarithmic operation and the non-subsampled Shearlet transformation are applied to the GF-3 SAR image. Secondly, in order to solve the problems that the image details are smoothed overly and the weight distribution is affected by the speckle, a new non-local means is used for the transformed high frequency coefficient. Thirdly, the Shearlet reconstruction is carried out. Finally, the final filtered image is obtained by an exponential operation. Experimental results demonstrate that, compared with other despeckling methods, the proposed method can suppress the speckle effectively in homogeneous regions and has better capability of edge preserving.

Advanced radiometric and interferometric milimeter-wave scene simulations

NASA Technical Reports Server (NTRS)

Hauss, B. I.; Moffa, P. J.; Steele, W. G.; Agravante, H.; Davidheiser, R.; Samec, T.; Young, S. K.

1993-01-01

Smart munitions and weapons utilize various imaging sensors (including passive IR, active and passive millimeter-wave, and visible wavebands) to detect/identify targets at short standoff ranges and in varied terrain backgrounds. In order to design and evaluate these sensors under a variety of conditions, a high-fidelity scene simulation capability is necessary. Such a capability for passive millimeter-wave scene simulation exists at TRW. TRW's Advanced Radiometric Millimeter-Wave Scene Simulation (ARMSS) code is a rigorous, benchmarked, end-to-end passive millimeter-wave scene simulation code for interpreting millimeter-wave data, establishing scene signatures and evaluating sensor performance. In passive millimeter-wave imaging, resolution is limited due to wavelength and aperture size. Where high resolution is required, the utility of passive millimeter-wave imaging is confined to short ranges. Recent developments in interferometry have made possible high resolution applications on military platforms. Interferometry or synthetic aperture radiometry allows the creation of a high resolution image with a sparsely filled aperture. Borrowing from research work in radio astronomy, we have developed and tested at TRW scene reconstruction algorithms that allow the recovery of the scene from a relatively small number of spatial frequency components. In this paper, the TRW modeling capability is described and numerical results are presented.

Feature learning and change feature classification based on deep learning for ternary change detection in SAR images

NASA Astrophysics Data System (ADS)

Gong, Maoguo; Yang, Hailun; Zhang, Puzhao

2017-07-01

Ternary change detection aims to detect changes and group the changes into positive change and negative change. It is of great significance in the joint interpretation of spatial-temporal synthetic aperture radar images. In this study, sparse autoencoder, convolutional neural networks (CNN) and unsupervised clustering are combined to solve ternary change detection problem without any supervison. Firstly, sparse autoencoder is used to transform log-ratio difference image into a suitable feature space for extracting key changes and suppressing outliers and noise. And then the learned features are clustered into three classes, which are taken as the pseudo labels for training a CNN model as change feature classifier. The reliable training samples for CNN are selected from the feature maps learned by sparse autoencoder with certain selection rules. Having training samples and the corresponding pseudo labels, the CNN model can be trained by using back propagation with stochastic gradient descent. During its training procedure, CNN is driven to learn the concept of change, and more powerful model is established to distinguish different types of changes. Unlike the traditional methods, the proposed framework integrates the merits of sparse autoencoder and CNN to learn more robust difference representations and the concept of change for ternary change detection. Experimental results on real datasets validate the effectiveness and superiority of the proposed framework.

Optical Modeling of the Alignment and Test of the NASA James Webb Space Telescope

NASA Technical Reports Server (NTRS)

Howard, Joseph M.; Hayden, Bill; Keski-Kuha, Ritva; Feinberg, Lee

2007-01-01

Optical modeling challenges of the ground alignment plan and optical test and verification of the NASA James Webb Space Telescope are discussed. Issues such as back-out of the gravity sag of light-weighted mirrors, as well as the use of a sparse-aperture auto-collimating flat system are discussed. A walk-through of the interferometer based alignment procedure is summarized, and sensitivities from the sparse aperture wavefront test are included as examples.'

Dictionary-based image reconstruction for superresolution in integrated circuit imaging.

PubMed

Cilingiroglu, T Berkin; Uyar, Aydan; Tuysuzoglu, Ahmet; Karl, W Clem; Konrad, Janusz; Goldberg, Bennett B; Ünlü, M Selim

2015-06-01

Resolution improvement through signal processing techniques for integrated circuit imaging is becoming more crucial as the rapid decrease in integrated circuit dimensions continues. Although there is a significant effort to push the limits of optical resolution for backside fault analysis through the use of solid immersion lenses, higher order laser beams, and beam apodization, signal processing techniques are required for additional improvement. In this work, we propose a sparse image reconstruction framework which couples overcomplete dictionary-based representation with a physics-based forward model to improve resolution and localization accuracy in high numerical aperture confocal microscopy systems for backside optical integrated circuit analysis. The effectiveness of the framework is demonstrated on experimental data.

Determining building interior structures using compressive sensing

NASA Astrophysics Data System (ADS)

Lagunas, Eva; Amin, Moeness G.; Ahmad, Fauzia; Nájar, Montse

2013-04-01

We consider imaging of the building interior structures using compressive sensing (CS) with applications to through-the-wall imaging and urban sensing. We consider a monostatic synthetic aperture radar imaging system employing stepped frequency waveform. The proposed approach exploits prior information of building construction practices to form an appropriate sparse representation of the building interior layout. We devise a dictionary of possible wall locations, which is consistent with the fact that interior walls are typically parallel or perpendicular to the front wall. The dictionary accounts for the dominant normal angle reflections from exterior and interior walls for the monostatic imaging system. CS is applied to a reduced set of observations to recover the true positions of the walls. Additional information about interior walls can be obtained using a dictionary of possible corner reflectors, which is the response of the junction of two walls. Supporting results based on simulation and laboratory experiments are provided. It is shown that the proposed sparsifying basis outperforms the conventional through-the-wall CS model, the wavelet sparsifying basis, and the block sparse model for building interior layout detection.

Megahertz rate, volumetric imaging of bubble clouds in sonothrombolysis using a sparse hemispherical receiver array

NASA Astrophysics Data System (ADS)

Acconcia, Christopher N.; Jones, Ryan M.; Goertz, David E.; O'Reilly, Meaghan A.; Hynynen, Kullervo

2017-09-01

It is well established that high intensity focused ultrasound can be used to disintegrate clots. This approach has the potential to rapidly and noninvasively resolve clot causing occlusions in cardiovascular diseases such as deep vein thrombosis (DVT). However, lack of an appropriate treatment monitoring tool is currently a limiting factor in its widespread adoption. Here we conduct cavitation imaging with a large aperture, sparse hemispherical receiver array during sonothrombolysis with multi-cycle burst exposures (0.1 or 1 ms burst lengths) at 1.51 MHz. It was found that bubble cloud generation on imaging correlated with the locations of clot degradation, as identified with high frequency (30 MHz) ultrasound following exposures. 3D images could be formed at integration times as short as 1 µs, revealing the initiation and rapid development of cavitation clouds. Equating to megahertz frame rates, this is an order of magnitude faster than any other imaging technique available for in vivo application. Collectively, these results suggest that the development of a device to perform DVT therapy procedures would benefit greatly from the integration of receivers tailored to bubble activity imaging.

Megahertz rate, volumetric imaging of bubble clouds in sonothrombolysis using a sparse hemispherical receiver array.

PubMed

Acconcia, Christopher N; Jones, Ryan M; Goertz, David E; O'Reilly, Meaghan A; Hynynen, Kullervo

2017-09-05

It is well established that high intensity focused ultrasound can be used to disintegrate clots. This approach has the potential to rapidly and noninvasively resolve clot causing occlusions in cardiovascular diseases such as deep vein thrombosis (DVT). However, lack of an appropriate treatment monitoring tool is currently a limiting factor in its widespread adoption. Here we conduct cavitation imaging with a large aperture, sparse hemispherical receiver array during sonothrombolysis with multi-cycle burst exposures (0.1 or 1 ms burst lengths) at 1.51 MHz. It was found that bubble cloud generation on imaging correlated with the locations of clot degradation, as identified with high frequency (30 MHz) ultrasound following exposures. 3D images could be formed at integration times as short as 1 µs, revealing the initiation and rapid development of cavitation clouds. Equating to megahertz frame rates, this is an order of magnitude faster than any other imaging technique available for in vivo application. Collectively, these results suggest that the development of a device to perform DVT therapy procedures would benefit greatly from the integration of receivers tailored to bubble activity imaging.

Future Prospects for Very High Angular Resolution Imaging in the UV/Optical

NASA Astrophysics Data System (ADS)

Allen, R. J.

2004-05-01

Achieving the most demanding science goals outlined by the previous speakers will ultimately require the development of coherent space-based arrays of UV/Optical light collectors spread over distances of hundreds of meters. It is possible to envisage ``in situ" assembly of large segmented filled-aperture telescopes in space using components ferried up with conventional launchers. However, the cost will grow roughly as the mass of material required, and this will ultimately limit the sizes of the apertures we can afford. Furthermore, since the collecting area and the angular resolution are coupled for diffraction-limited filled apertures, the sensitivity may be much higher than is actually required to do the science. Constellations of collectors deployed over large areas as interferometer arrays or sparse apertures offer the possibility of independently tailoring the angular resolution and the sensitivity in order to optimally match the science requirements. Several concept designs have been proposed to provide imaging data for different classes of targets such as protoplanetary disks, the nuclear regions of the nearest active galaxies, and the surfaces of stars of different types. Constellations of identical collectors may be built and launched at lower cost through mass production, but new challenges arise when they have to be deployed. The ``aperture" synthesized is only as good as the accuracy with which the individual collectors can be placed and held to the required figure. This ``station-keeping" problem is one of the most important engineering problems to be solved before the promise of virtually unlimited angular resolution in the UV/Optical can be realized. Among the attractive features of an array of free-flying collectors configured for imaging is the fact that the figure errors of the ``aperture" so produced may be much more random than is the case for monolithic or segmented telescopes. This can result in a significant improvement in the dynamic range and permit imaging of faint objects near much brighter extraneous nearby sources, a task presently reserved for specially-designed coronagraphs on filled apertures.

Characteristic investigation of Golay9 multiple mirror telescope with a spherical primary mirror

NASA Astrophysics Data System (ADS)

Wu, Feng; Wu, Quanying; Zhu, Xifang; Xiang, Ruxi; Qian, Lin

2017-10-01

The sparse aperture provides a novel solution to the manufacturing difficulties of modern super large telescopes. Golay configurations are optimal in the sparse aperture family. Characteristics of the Golay9 multiple mirror telescope having a spherical primary mirror are investigated. The arrangement of the nine sub-mirrors is discussed after the planar Golay9 configuration is analyzed. The characteristics of the entrance pupil are derived by analyzing the sub-aperture shapes with different relative apertures and sub-mirror sizes. Formulas about the fill factor and the overlay factor are deduced. Their maximal values are presented based on the derived tangency condition. Formulas for the point spread function (PSF) and the modulation transfer function (MTF) of the Golay9 MMT are also deduced. Two Golay9 MMT have been developed by Zemax simulation. Their PSF, MTF, fill factors, and overlay factors prove that our theoretical results are consistent with the practical simulation ones.

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

NASA Astrophysics Data System (ADS)

Podmore, Hugh; Scott, Alan; Lee, Regina

2018-02-01

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

Revolutionary astrophysics using an incoherent synthetic optical aperture

NASA Astrophysics Data System (ADS)

Rafanelli, Gerard L.; Cosner, Christopher M.; Spencer, Susan B.; Wolfe, Douglas; Newman, Arthur; Polidan, Ronald; Chakrabarti, Supriya

2017-09-01

We describe a paradigm shift for astronomical observatories that would replace circular apertures with rotating synthetic apertures. Rotating Synthetic Aperture (RSA) observatories can enable high value science measurements for the lowest mass to orbit, have superior performance relative to all sparse apertures, can provide resolution of 20m to 30m apertures having the collecting area of 8m to 12m telescopes with much less mass, risk, schedule, and cost. RSA is based on current, or near term technology and can be launched on a single, current launch vehicle to L2. Much larger apertures are possible using the NASA Space Launch System.

Revolutionary Astrophysics using an Incoherent Synthetic Optical Aperture

NASA Astrophysics Data System (ADS)

Rafanelli, Gerard L.; Cosner, Christopher M.; Spencer, Susan B.; Wolfe, Douglas w.; Newman, Arthur M.; Polidan, Ronald S.; Chakrabarti, Supriya

2018-01-01

We describe a paradigm shift for astronomical observatories that would replace circular apertures with rotating synthetic apertures. Rotating Synthetic Aperture (RSA) observatories can enable high value science measurements for the lowest mass to orbit, have superior performance relative to all sparse apertures, can provide resolution of 20m to 30m apertures having the collecting area of 8m to 12m telescopes with much less mass, risk, schedule, and cost. RSA is based on current, or near term technology and can be launched on a single, current launch vehicle to L2. Much larger apertures are possible using the NASA Space Launch System.

Dual-foci detection in photoacoustic computed tomography with coplanar light illumination and acoustic detection: a phantom study.

PubMed

Lin, Xiangwei; Liu, Chengbo; Meng, Jing; Gong, Xiaojing; Lin, Riqiang; Sun, Mingjian; Song, Liang

2018-05-01

A dual-foci transducer with coplanar light illumination and acoustic detection was applied for the first time. It overcame the small directivity angle, low-sensitivity, and large datasets in conventional circular scanning or array-based photoacoustic computed tomography (PACT). The custom-designed transducer is focused on both the scanning plane with virtual-point detection and the elevation direction for large field of view (FOV) cross-sectional imaging. Moreover, a coplanar light illumination and acoustic detection configuration can provide ring-shaped light irradiation with highly efficient acoustic detection, which in principle has a better adaptability when imaging samples of irregular surfaces. Phantom experiments showed that our PACT system can achieve high resolution (∼0.5  mm), enhanced signal-to-noise ratio (16-dB improvement), and a more complete structure in a greater FOV with an equal number of sampling points compared with the results from a flat aperture transducer. This study provides the proof of concept for the fabrication of a sparse array with the dual-foci property and large aperture size for high-quality, low-cost, and high-speed photoacoustic imaging. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Interferometric synthetic aperture radar phase unwrapping based on sparse Markov random fields by graph cuts

NASA Astrophysics Data System (ADS)

Zhou, Lifan; Chai, Dengfeng; Xia, Yu; Ma, Peifeng; Lin, Hui

2018-01-01

Phase unwrapping (PU) is one of the key processes in reconstructing the digital elevation model of a scene from its interferometric synthetic aperture radar (InSAR) data. It is known that two-dimensional (2-D) PU problems can be formulated as maximum a posteriori estimation of Markov random fields (MRFs). However, considering that the traditional MRF algorithm is usually defined on a rectangular grid, it fails easily if large parts of the wrapped data are dominated by noise caused by large low-coherence area or rapid-topography variation. A PU solution based on sparse MRF is presented to extend the traditional MRF algorithm to deal with sparse data, which allows the unwrapping of InSAR data dominated by high phase noise. To speed up the graph cuts algorithm for sparse MRF, we designed dual elementary graphs and merged them to obtain the Delaunay triangle graph, which is used to minimize the energy function efficiently. The experiments on simulated and real data, compared with other existing algorithms, both confirm the effectiveness of the proposed MRF approach, which suffers less from decorrelation effects caused by large low-coherence area or rapid-topography variation.

Study of the Imaging Capabilities of SPIRIT/SPECS Concept Interferometers

NASA Technical Reports Server (NTRS)

Allen, Ronald J.

2002-01-01

Several new space science mission concepts under development at NASA-GSFC for astronomy are intended to carry out synthetic imaging using Michelson interferometers or direct (Fizeau) imaging with sparse apertures. Examples of these mission concepts include the Stellar Imager (SI), the Space Infrared Interferometric Telescope (SPIRIT), the Submillimeter Probe of the Evolution of Cosmic Structure (SPECS), and the Fourier-Kelvin Stellar Interferometer (FKSI). We have been developing computer-based simulators for these missions. These simulators are aimed at providing a quantitative evaluation of the imaging capabilities of the mission by modeling the performance on different realistic targets in terms of sensitivity, angular resolution, and dynamic range. Both Fizeau and Michelson modes of operation can be considered. Our work is based on adapting a computer simulator called imSIM which was initially written for the Space Interferometer Mission in order to simulate the imaging mode of new missions such as those listed. This report covers the activities we have undertaken to provide a preliminary version of a simulator for the SPIRIT mission concept.

Wavefront Control Testbed (WCT) Experiment Results

NASA Technical Reports Server (NTRS)

Burns, Laura A.; Basinger, Scott A.; Campion, Scott D.; Faust, Jessica A.; Feinberg, Lee D.; Hayden, William L.; Lowman, Andrew E.; Ohara, Catherine M.; Petrone, Peter P., III

2004-01-01

The Wavefront Control Testbed (WCT) was created to develop and test wavefront sensing and control algorithms and software for the segmented James Webb Space Telescope (JWST). Last year, we changed the system configuration from three sparse aperture segments to a filled aperture with three pie shaped segments. With this upgrade we have performed experiments on fine phasing with line-of-sight and segment-to-segment jitter, dispersed fringe visibility and grism angle;. high dynamic range tilt sensing; coarse phasing with large aberrations, and sampled sub-aperture testing. This paper reviews the results of these experiments.

A multi-frequency sparse hemispherical ultrasound phased array for microbubble-mediated transcranial therapy and simultaneous cavitation mapping

NASA Astrophysics Data System (ADS)

Deng, Lulu; O'Reilly, Meaghan A.; Jones, Ryan M.; An, Ran; Hynynen, Kullervo

2016-12-01

Focused ultrasound (FUS) phased arrays show promise for non-invasive brain therapy. However, the majority of them are limited to a single transmit/receive frequency and therefore lack the versatility to expose and monitor the treatment volume. Multi-frequency arrays could offer variable transmit focal sizes under a fixed aperture, and detect different spectral content on receive for imaging purposes. Here, a three-frequency (306, 612, and 1224 kHz) sparse hemispherical ultrasound phased array (31.8 cm aperture; 128 transducer modules) was constructed and evaluated for microbubble-mediated transcranial therapy and simultaneous cavitation mapping. The array is able to perform effective electronic beam steering over a volume spanning (-40, 40) and (-30, 50) mm in the lateral and axial directions, respectively. The focal size at the geometric center is approximately 0.9 (2.1) mm, 1.7 (3.9) mm, and 3.1 (6.5) mm in lateral (axial) pressure full width at half maximum (FWHM) at 1224, 612, and 306 kHz, respectively. The array was also found capable of dual-frequency excitation and simultaneous multi-foci sonication, which enables the future exploration of more complex exposure strategies. Passive acoustic mapping of dilute microbubble clouds demonstrated that the point spread function of the receive array has a lateral (axial) intensity FWHM between 0.8-3.5 mm (1.7-11.7 mm) over a volume spanning (-25, 25) mm in both the lateral and axial directions, depending on the transmit/receive frequency combination and the imaging location. The device enabled both half and second harmonic imaging through the intact skull, which may be useful for improving the contrast-to-tissue ratio or imaging resolution, respectively. Preliminary in vivo experiments demonstrated the system’s ability to induce blood-brain barrier opening and simultaneously spatially map microbubble cavitation activity in a rat model. This work presents a tool to investigate optimal strategies for non-thermal FUS brain therapy and concurrent microbubble cavitation monitoring through the availability of multiple frequencies.

A multi-frequency sparse hemispherical ultrasound phased array for microbubble-mediated transcranial therapy and simultaneous cavitation mapping

PubMed Central

Deng, Lulu; O'Reilly, Meaghan A.; Jones, Ryan M.; An, Ran; Hynynen, Kullervo

2016-01-01

Focused ultrasound (FUS) phased arrays show promise for non-invasive brain therapy. However, the majority of them are limited to a single transmit/receive frequency and therefore lack the versatility to expose and monitor the treatment volume. Multi-frequency arrays could offer variable transmit focal sizes under a fixed aperture, and detect different spectral content on receive for imaging purposes. Here, a three-frequency (306, 612 and 1224 kHz) sparse hemispherical ultrasound phased array (31.8 cm aperture; 128 transducer modules) was constructed and evaluated for microbubble-mediated transcranial therapy and simultaneous cavitation mapping. The array is able to perform effective electronic beam steering over a volume spanning [−40, 40] and [−30, 50] mm in the lateral and axial directions, respectively. The focal size at the geometric center is approximately 0.9 (2.1) mm, 1.7 (3.9) mm, and 3.1 (6.5) mm in lateral (axial) pressure full width at half maximum (FWHM) at 1224, 612, and 306 kHz, respectively. The array was also found capable of dual-frequency excitation and simultaneous multi–foci sonication, which enables the future exploration of more complex exposure strategies. Passive acoustic mapping of dilute microbubble clouds demonstrated that the point spread function of the receive array has a lateral (axial) intensity FWHM between 0.8-3.5 mm (1.7-11.7 mm) over a volume spanning [−25, 25] mm in both the lateral and axial directions, depending on the transmit/receive frequency combination and the imaging location. The device enabled both half and second harmonic imaging through the intact skull, which may be useful for improving the contrast-to-tissue ratio or imaging resolution, respectively. Preliminary in-vivo experiments demonstrated the system's ability to induce blood-brain barrier opening and simultaneously spatially map microbubble cavitation activity in a rat model. This work presents a tool to investigate optimal strategies for non-thermal FUS brain therapy and concurrent microbubble cavitation monitoring through the availability of multiple frequencies. PMID:27845920

A multi-frequency sparse hemispherical ultrasound phased array for microbubble-mediated transcranial therapy and simultaneous cavitation mapping.

PubMed

Deng, Lulu; O'Reilly, Meaghan A; Jones, Ryan M; An, Ran; Hynynen, Kullervo

2016-12-21

Focused ultrasound (FUS) phased arrays show promise for non-invasive brain therapy. However, the majority of them are limited to a single transmit/receive frequency and therefore lack the versatility to expose and monitor the treatment volume. Multi-frequency arrays could offer variable transmit focal sizes under a fixed aperture, and detect different spectral content on receive for imaging purposes. Here, a three-frequency (306, 612, and 1224 kHz) sparse hemispherical ultrasound phased array (31.8 cm aperture; 128 transducer modules) was constructed and evaluated for microbubble-mediated transcranial therapy and simultaneous cavitation mapping. The array is able to perform effective electronic beam steering over a volume spanning (-40, 40) and (-30, 50) mm in the lateral and axial directions, respectively. The focal size at the geometric center is approximately 0.9 (2.1) mm, 1.7 (3.9) mm, and 3.1 (6.5) mm in lateral (axial) pressure full width at half maximum (FWHM) at 1224, 612, and 306 kHz, respectively. The array was also found capable of dual-frequency excitation and simultaneous multi-foci sonication, which enables the future exploration of more complex exposure strategies. Passive acoustic mapping of dilute microbubble clouds demonstrated that the point spread function of the receive array has a lateral (axial) intensity FWHM between 0.8-3.5 mm (1.7-11.7 mm) over a volume spanning (-25, 25) mm in both the lateral and axial directions, depending on the transmit/receive frequency combination and the imaging location. The device enabled both half and second harmonic imaging through the intact skull, which may be useful for improving the contrast-to-tissue ratio or imaging resolution, respectively. Preliminary in vivo experiments demonstrated the system's ability to induce blood-brain barrier opening and simultaneously spatially map microbubble cavitation activity in a rat model. This work presents a tool to investigate optimal strategies for non-thermal FUS brain therapy and concurrent microbubble cavitation monitoring through the availability of multiple frequencies.

Influence of pressure change during hydraulic tests on fracture aperture.

PubMed

Ji, Sung-Hoon; Koh, Yong-Kwon; Kuhlman, Kristopher L; Lee, Moo Yul; Choi, Jong Won

2013-03-01

In a series of field experiments, we evaluate the influence of a small water pressure change on fracture aperture during a hydraulic test. An experimental borehole is instrumented at the Korea Atomic Energy Research Institute (KAERI) Underground Research Tunnel (KURT). The target fracture for testing was found from the analyses of borehole logging and hydraulic tests. A double packer system was developed and installed in the test borehole to directly observe the aperture change due to water pressure change. Using this packer system, both aperture and flow rate are directly observed under various water pressures. Results indicate a slight change in fracture hydraulic head leads to an observable change in aperture. This suggests that aperture change should be considered when analyzing hydraulic test data from a sparsely fractured rock aquifer. © 2012, The Author(s). Groundwater © 2012, National Ground Water Association.

Sparse aperture masking at the VLT. II. Detection limits for the eight debris disks stars β Pic, AU Mic, 49 Cet, η Tel, Fomalhaut, g Lup, HD 181327 and HR 8799

NASA Astrophysics Data System (ADS)

Gauchet, L.; Lacour, S.; Lagrange, A.-M.; Ehrenreich, D.; Bonnefoy, M.; Girard, J. H.; Boccaletti, A.

2016-10-01

Context. The formation of planetary systems is a common, yet complex mechanism. Numerous stars have been identified to possess a debris disk, a proto-planetary disk or a planetary system. The understanding of such formation process requires the study of debris disks. These targets are substantial and particularly suitable for optical and infrared observations. Sparse aperture masking (SAM) is a high angular resolution technique strongly contributing to probing the region from 30 to 200 mas around the stars. This area is usually unreachable with classical imaging, and the technique also remains highly competitive compared to vortex coronagraphy. Aims: We aim to study debris disks with aperture masking to probe the close environment of the stars. Our goal is either to find low-mass companions, or to set detection limits. Methods: We observed eight stars presenting debris disks (β Pictoris, AU Microscopii, 49 Ceti, η Telescopii, Fomalhaut, g Lupi, HD 181327, and HR 8799) with SAM technique on the NaCo instrument at the Very Large Telescope (VLT). Results: No close companions were detected using closure phase information under 0.5'' of separation from the parent stars. We obtained magnitude detection limits that we converted to Jupiter masses detection limits using theoretical isochrones from evolutionary models. Conclusions: We derived upper mass limits on the presence of companions in the area of a few times the telescope's diffraction limits around each target star. Based on observations collected at the European Southern Observatory (ESO) during runs 087.C-0450(A), 087.C-0450(B) 087.C-0750(A), 088.C-0358(A).All magnitude detection limits maps are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/595/A31

Fast Physically Correct Refocusing for Sparse Light Fields Using Block-Based Multi-Rate View Interpolation.

PubMed

Huang, Chao-Tsung; Wang, Yu-Wen; Huang, Li-Ren; Chin, Jui; Chen, Liang-Gee

2017-02-01

Digital refocusing has a tradeoff between complexity and quality when using sparsely sampled light fields for low-storage applications. In this paper, we propose a fast physically correct refocusing algorithm to address this issue in a twofold way. First, view interpolation is adopted to provide photorealistic quality at infocus-defocus hybrid boundaries. Regarding its conventional high complexity, we devised a fast line-scan method specifically for refocusing, and its 1D kernel can be 30× faster than the benchmark View Synthesis Reference Software (VSRS)-1D-Fast. Second, we propose a block-based multi-rate processing flow for accelerating purely infocused or defocused regions, and a further 3- 34× speedup can be achieved for high-resolution images. All candidate blocks of variable sizes can interpolate different numbers of rendered views and perform refocusing in different subsampled layers. To avoid visible aliasing and block artifacts, we determine these parameters and the simulated aperture filter through a localized filter response analysis using defocus blur statistics. The final quadtree block partitions are then optimized in terms of computation time. Extensive experimental results are provided to show superior refocusing quality and fast computation speed. In particular, the run time is comparable with the conventional single-image blurring, which causes serious boundary artifacts.

An algorithm for extraction of periodic signals from sparse, irregularly sampled data

NASA Technical Reports Server (NTRS)

Wilcox, J. Z.

1994-01-01

Temporal gaps in discrete sampling sequences produce spurious Fourier components at the intermodulation frequencies of an oscillatory signal and the temporal gaps, thus significantly complicating spectral analysis of such sparsely sampled data. A new fast Fourier transform (FFT)-based algorithm has been developed, suitable for spectral analysis of sparsely sampled data with a relatively small number of oscillatory components buried in background noise. The algorithm's principal idea has its origin in the so-called 'clean' algorithm used to sharpen images of scenes corrupted by atmospheric and sensor aperture effects. It identifies as the signal's 'true' frequency that oscillatory component which, when passed through the same sampling sequence as the original data, produces a Fourier image that is the best match to the original Fourier space. The algorithm has generally met with succession trials with simulated data with a low signal-to-noise ratio, including those of a type similar to hourly residuals for Earth orientation parameters extracted from VLBI data. For eight oscillatory components in the diurnal and semidiurnal bands, all components with an amplitude-noise ratio greater than 0.2 were successfully extracted for all sequences and duty cycles (greater than 0.1) tested; the amplitude-noise ratios of the extracted signals were as low as 0.05 for high duty cycles and long sampling sequences. When, in addition to these high frequencies, strong low-frequency components are present in the data, the low-frequency components are generally eliminated first, by employing a version of the algorithm that searches for non-integer multiples of the discrete FET minimum frequency.

Direction of Arrival Estimation for MIMO Radar via Unitary Nuclear Norm Minimization

PubMed Central

Wang, Xianpeng; Huang, Mengxing; Wu, Xiaoqin; Bi, Guoan

2017-01-01

In this paper, we consider the direction of arrival (DOA) estimation issue of noncircular (NC) source in multiple-input multiple-output (MIMO) radar and propose a novel unitary nuclear norm minimization (UNNM) algorithm. In the proposed method, the noncircular properties of signals are used to double the virtual array aperture, and the real-valued data are obtained by utilizing unitary transformation. Then a real-valued block sparse model is established based on a novel over-complete dictionary, and a UNNM algorithm is formulated for recovering the block-sparse matrix. In addition, the real-valued NC-MUSIC spectrum is used to design a weight matrix for reweighting the nuclear norm minimization to achieve the enhanced sparsity of solutions. Finally, the DOA is estimated by searching the non-zero blocks of the recovered matrix. Because of using the noncircular properties of signals to extend the virtual array aperture and an additional real structure to suppress the noise, the proposed method provides better performance compared with the conventional sparse recovery based algorithms. Furthermore, the proposed method can handle the case of underdetermined DOA estimation. Simulation results show the effectiveness and advantages of the proposed method. PMID:28441770

Error analysis of the Golay3 optical imaging system.

PubMed

Wu, Quanying; Fan, Junliu; Wu, Feng; Zhao, Jun; Qian, Lin

2013-05-01

We use aberration theory to derive a generalized pupil function of the Golay3 imaging system when astigmatisms exist in its submirrors. Theoretical analysis and numerical simulation using ZEMAX show that the point spread function (PSF) and the modulation transfer function (MTF) of the Golay3 sparse aperture system have a periodic change when there are piston errors. When the peak-valley value of the wavefront (PV(tilt)) due to the tilt error increases from zero to λ, the PSF and the MTF change significantly, and the change direction is determined by the location of the submirror with the tilt error. When PV(tilt) becomes larger than λ, the PSF and the MTF remain unvaried. We calculate the peaks of the signal-to-noise ratio (PSNR) resulting from the piston and tilt errors according to the Strehl ratio, and show that the PSNR decreases when the errors increase.

Ground settlement monitoring from temporarily persistent scatterers between two SAR acquisitions

USGS Publications Warehouse

Lei, Z.; Xiaoli, D.; Guangcai, F.; Zhong, L.

2009-01-01

We present an improved differential interferometric synthetic aperture radar (DInSAR) analysis method that measures motions of scatterers whose phases are stable between two SAR acquisitions. Such scatterers are referred to as temporarily persistent scatterers (TPS) for simplicity. Unlike the persistent scatterer InSAR (PS-InSAR) method that relies on a time-series of interferograms, the new algorithm needs only one interferogram. TPS are identified based on pixel offsets between two SAR images, and are specially coregistered based on their estimated offsets instead of a global polynomial for the whole image. Phase unwrapping is carried out based on an algorithm for sparse data points. The method is successfully applied to measure the settlement in the Hong Kong Airport area. The buildings surrounded by vegetation were successfully selected as TPS and the tiny deformation signal over the area was detected. ??2009 IEEE.

A Study of Imaging Interferometer Simulators

NASA Technical Reports Server (NTRS)

Allen, Ronald J.

2002-01-01

Several new space science mission concepts under development at NASA-GSFC for astronomy are intended to carry out synthetic imaging using Michelson interferometers or direct (Fizeau) imaging with sparse apertures. Examples of these mission concepts include the Stellar Imager (SI), the Space Infrared Interferometric Telescope (SPIRIT), the Submillimeter Probe of the Evolution of Cosmic Structure (SPECS), and the Fourier-Kelvin Stellar Interferometer (FKSI). We have been developing computer-based simulators for these missions. These simulators are aimed at providing a quantitative evaluation of the imaging capabilities of the mission by modelling the performance on different realistic targets in terms of sensitivity, angular resolution, and dynamic range. Both Fizeau and Michelson modes of operation can be considered. Our work is based on adapting a computer simulator called imSIM, which was initially written for the Space Interferometer Mission in order to simulate the imaging mode of new missions such as those listed. In a recent GSFC-funded study we have successfully written a preliminary version of a simulator SISIM for the Stellar Imager and carried out some preliminary studies with it. In a separately funded study we have also been applying these methods to SPECS/SPIRIT.

Sparse representation based SAR vehicle recognition along with aspect angle.

PubMed

Xing, Xiangwei; Ji, Kefeng; Zou, Huanxin; Sun, Jixiang

2014-01-01

As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC) has attracted much attention in synthetic aperture radar (SAR) automatic target recognition (ATR) recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA), in which the correlation between the vehicle's aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA) feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle's aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

Signal-to-noise ratio of Singer product apertures

NASA Astrophysics Data System (ADS)

Shutler, Paul M. E.; Byard, Kevin

2017-09-01

Formulae for the signal-to-noise ratio (SNR) of Singer product apertures are derived, allowing optimal Singer product apertures to be identified, and the CPU time required to decode them is quantified. This allows a systematic comparison to be made of the performance of Singer product apertures against both conventionally wrapped Singer apertures, and also conventional product apertures such as square uniformly redundant arrays. For very large images, equivalently for images at very high resolution, the SNR of Singer product apertures is asymptotically as good as the best conventional apertures, but Singer product apertures decode faster than any conventional aperture by at least a factor of ten for image sizes up to several megapixels. These theoretical predictions are verified using numerical simulations, demonstrating that coded aperture video is for the first time a realistic possibility.

Imaging performance of annular apertures. II - Line spread functions

NASA Technical Reports Server (NTRS)

Tschunko, H. F. A.

1978-01-01

Line images formed by aberration-free optical systems with annular apertures are investigated in the whole range of central obstruction ratios. Annular apertures form lines images with central and side line groups. The number of lines in each line group is given by the ratio of the outer diameter of the annular aperture divided by the width of the annulus. The theoretical energy fraction of 0.889 in the central line of the image formed by an unobstructed aperture increases for centrally obstructed apertures to 0.932 for the central line group. Energy fractions for the central and side line groups are practically constant for all obstruction ratios and for each line group. The illumination of rectangular secondary apertures of various length/width ratios by apertures of various obstruction ratios is discussed.

Ultrafast Synthetic Transmit Aperture Imaging Using Hadamard-Encoded Virtual Sources With Overlapping Sub-Apertures.

PubMed

Ping Gong; Pengfei Song; Shigao Chen

2017-06-01

The development of ultrafast ultrasound imaging offers great opportunities to improve imaging technologies, such as shear wave elastography and ultrafast Doppler imaging. In ultrafast imaging, there are tradeoffs among image signal-to-noise ratio (SNR), resolution, and post-compounded frame rate. Various approaches have been proposed to solve this tradeoff, such as multiplane wave imaging or the attempts of implementing synthetic transmit aperture imaging. In this paper, we propose an ultrafast synthetic transmit aperture (USTA) imaging technique using Hadamard-encoded virtual sources with overlapping sub-apertures to enhance both image SNR and resolution without sacrificing frame rate. This method includes three steps: 1) create virtual sources using sub-apertures; 2) encode virtual sources using Hadamard matrix; and 3) add short time intervals (a few microseconds) between transmissions of different virtual sources to allow overlapping sub-apertures. The USTA was tested experimentally with a point target, a B-mode phantom, and in vivo human kidney micro-vessel imaging. Compared with standard coherent diverging wave compounding with the same frame rate, improvements on image SNR, lateral resolution (+33%, with B-mode phantom imaging), and contrast ratio (+3.8 dB, with in vivo human kidney micro-vessel imaging) have been achieved. The f-number of virtual sources, the number of virtual sources used, and the number of elements used in each sub-aperture can be flexibly adjusted to enhance resolution and SNR. This allows very flexible optimization of USTA for different applications.

A deconvolution extraction method for 2D multi-object fibre spectroscopy based on the regularized least-squares QR-factorization algorithm

NASA Astrophysics Data System (ADS)

Yu, Jian; Yin, Qian; Guo, Ping; Luo, A.-li

2014-09-01

This paper presents an efficient method for the extraction of astronomical spectra from two-dimensional (2D) multifibre spectrographs based on the regularized least-squares QR-factorization (LSQR) algorithm. We address two issues: we propose a modified Gaussian point spread function (PSF) for modelling the 2D PSF from multi-emission-line gas-discharge lamp images (arc images), and we develop an efficient deconvolution method to extract spectra in real circumstances. The proposed modified 2D Gaussian PSF model can fit various types of 2D PSFs, including different radial distortion angles and ellipticities. We adopt the regularized LSQR algorithm to solve the sparse linear equations constructed from the sparse convolution matrix, which we designate the deconvolution spectrum extraction method. Furthermore, we implement a parallelized LSQR algorithm based on graphics processing unit programming in the Compute Unified Device Architecture to accelerate the computational processing. Experimental results illustrate that the proposed extraction method can greatly reduce the computational cost and memory use of the deconvolution method and, consequently, increase its efficiency and practicability. In addition, the proposed extraction method has a stronger noise tolerance than other methods, such as the boxcar (aperture) extraction and profile extraction methods. Finally, we present an analysis of the sensitivity of the extraction results to the radius and full width at half-maximum of the 2D PSF.

Aperture tolerances for neutron-imaging systems in inertial confinement fusion.

PubMed

Ghilea, M C; Sangster, T C; Meyerhofer, D D; Lerche, R A; Disdier, L

2008-02-01

Neutron-imaging systems are being considered as an ignition diagnostic for the National Ignition Facility (NIF) [Hogan et al., Nucl. Fusion 41, 567 (2001)]. Given the importance of these systems, a neutron-imaging design tool is being used to quantify the effects of aperture fabrication and alignment tolerances on reconstructed neutron images for inertial confinement fusion. The simulations indicate that alignment tolerances of more than 1 mrad would introduce measurable features in a reconstructed image for both pinholes and penumbral aperture systems. These simulations further show that penumbral apertures are several times less sensitive to fabrication errors than pinhole apertures.

Reconfigurable metasurface aperture for security screening and microwave imaging

NASA Astrophysics Data System (ADS)

Sleasman, Timothy; Imani, Mohammadreza F.; Boyarsky, Michael; Pulido-Mancera, Laura; Reynolds, Matthew S.; Smith, David R.

2017-05-01

Microwave imaging systems have seen growing interest in recent decades for applications ranging from security screening to space/earth observation. However, hardware architectures commonly used for this purpose have not seen drastic changes. With the advent of metamaterials a wealth of opportunities have emerged for honing metasurface apertures for microwave imaging systems. Recent thrusts have introduced dynamic reconfigurability directly into the aperture layer, providing powerful capabilities from a physical layer with considerable simplicity. The waveforms generated from such dynamic metasurfaces make them suitable for application in synthetic aperture radar (SAR) and, more generally, computational imaging. In this paper, we investigate a dynamic metasurface aperture capable of performing microwave imaging in the K-band (17.5-26.5 GHz). The proposed aperture is planar and promises an inexpensive fabrication process via printed circuit board techniques. These traits are further augmented by the tunability of dynamic metasurfaces, which provides the dexterity necessary to generate field patterns ranging from a sequence of steered beams to a series of uncorrelated radiation patterns. Imaging is experimentally demonstrated with a voltage-tunable metasurface aperture. We also demonstrate the aperture's utility in real-time measurements and perform volumetric SAR imaging. The capabilities of a prototype are detailed and the future prospects of general dynamic metasurface apertures are discussed.

Coded aperture solution for improving the performance of traffic enforcement cameras

NASA Astrophysics Data System (ADS)

Masoudifar, Mina; Pourreza, Hamid Reza

2016-10-01

A coded aperture camera is proposed for automatic license plate recognition (ALPR) systems. It captures images using a noncircular aperture. The aperture pattern is designed for the rapid acquisition of high-resolution images while preserving high spatial frequencies of defocused regions. It is obtained by minimizing an objective function, which computes the expected value of perceptual deblurring error. The imaging conditions and camera sensor specifications are also considered in the proposed function. The designed aperture improves the depth of field (DoF) and subsequently ALPR performance. The captured images can be directly analyzed by the ALPR software up to a specific depth, which is 13 m in our case, though it is 11 m for the circular aperture. Moreover, since the deblurring results of images captured by our aperture yield fewer artifacts than those captured by the circular aperture, images can be first deblurred and then analyzed by the ALPR software. In this way, the DoF and recognition rate can be improved at the same time. Our case study shows that the proposed camera can improve the DoF up to 17 m while it is limited to 11 m in the conventional aperture.

Single image super-resolution based on compressive sensing and improved TV minimization sparse recovery

NASA Astrophysics Data System (ADS)

Vishnukumar, S.; Wilscy, M.

2017-12-01

In this paper, we propose a single image Super-Resolution (SR) method based on Compressive Sensing (CS) and Improved Total Variation (TV) Minimization Sparse Recovery. In the CS framework, low-resolution (LR) image is treated as the compressed version of high-resolution (HR) image. Dictionary Training and Sparse Recovery are the two phases of the method. K-Singular Value Decomposition (K-SVD) method is used for dictionary training and the dictionary represents HR image patches in a sparse manner. Here, only the interpolated version of the LR image is used for training purpose and thereby the structural self similarity inherent in the LR image is exploited. In the sparse recovery phase the sparse representation coefficients with respect to the trained dictionary for LR image patches are derived using Improved TV Minimization method. HR image can be reconstructed by the linear combination of the dictionary and the sparse coefficients. The experimental results show that the proposed method gives better results quantitatively as well as qualitatively on both natural and remote sensing images. The reconstructed images have better visual quality since edges and other sharp details are preserved.

Design of a nano-satellite demonstrator of an infrared imaging space interferometer: the HyperCube

NASA Astrophysics Data System (ADS)

Dohlen, Kjetil; Vives, Sébastien; Rakotonimbahy, Eddy; Sarkar, Tanmoy; Tasnim Ava, Tanzila; Baccichet, Nicola; Savini, Giorgio; Swinyard, Bruce

2014-07-01

The construction of a kilometer-baseline far infrared imaging interferometer is one of the big instrumental challenges for astronomical instrumentation in the coming decades. Recent proposals such as FIRI, SPIRIT, and PFI illustrate both science cases, from exo-planetary science to study of interstellar media and cosmology, and ideas for construction of such instruments, both in space and on the ground. An interesting option for an imaging multi-aperture interferometer with km baseline is the space-based hyper telescope (HT) where a giant, sparsely populated primary mirror is constituted of several free-flying satellites each carrying a mirror segment. All the segments point the same object and direct their part of the pupil towards a common focus where another satellite, containing recombiner optics and a detector unit, is located. In Labeyrie's [1] original HT concept, perfect phasing of all the segments was assumed, allowing snap-shot imaging within a reduced field of view and coronagraphic extinction of the star. However, for a general purpose observatory, image reconstruction using closure phase a posteriori image reconstruction is possible as long as the pupil is fully non-redundant. Such reconstruction allows for much reduced alignment tolerances, since optical path length control is only required to within several tens of wavelengths, rather than within a fraction of a wavelength. In this paper we present preliminary studies for such an instrument and plans for building a miniature version to be flown on a nano satellite. A design for recombiner optics is proposed, including a scheme for exit pupil re-organization, is proposed, indicating the focal plane satellite in the case of a km-baseline interferometer could be contained within a 1m3 unit. Different options for realization of a miniature version are presented, including instruments for solar observations in the visible and the thermal infrared and giant planet observations in the visible, and an algorithm for design of optimal aperture layout based on least-squares minimization is described. A first experimental setup realized by master students is presented, where a 20mm baseline interferometer with 1mm apertures associated with a thermal infrared camera pointed the sun. The absence of fringes in this setup is discussed in terms of spatial spectrum analysis. Finally, we discuss requirements in terms of satellite pointing requirements for such a miniature interferometer.

Image fusion using sparse overcomplete feature dictionaries

DOEpatents

Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt

2015-10-06

Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.

Wavefront Control and Image Restoration with Less Computing

NASA Technical Reports Server (NTRS)

Lyon, Richard G.

2010-01-01

PseudoDiversity is a method of recovering the wavefront in a sparse- or segmented- aperture optical system typified by an interferometer or a telescope equipped with an adaptive primary mirror consisting of controllably slightly moveable segments. (PseudoDiversity should not be confused with a radio-antenna-arraying method called pseudodiversity.) As in the cases of other wavefront- recovery methods, the streams of wavefront data generated by means of PseudoDiversity are used as feedback signals for controlling electromechanical actuators of the various segments so as to correct wavefront errors and thereby, for example, obtain a clearer, steadier image of a distant object in the presence of atmospheric turbulence. There are numerous potential applications in astronomy, remote sensing from aircraft and spacecraft, targeting missiles, sighting military targets, and medical imaging (including microscopy) through such intervening media as cells or water. In comparison with prior wavefront-recovery methods used in adaptive optics, PseudoDiversity involves considerably simpler equipment and procedures and less computation. For PseudoDiversity, there is no need to install separate metrological equipment or to use any optomechanical components beyond those that are already parts of the optical system to which the method is applied. In Pseudo- Diversity, the actuators of a subset of the segments or subapertures are driven to make the segments dither in the piston, tilt, and tip degrees of freedom. Each aperture is dithered at a unique frequency at an amplitude of a half wavelength of light. During the dithering, images on the focal plane are detected and digitized at a rate of at least four samples per dither period. In the processing of the image samples, the use of different dither frequencies makes it possible to determine the separate effects of the various dithered segments or apertures. The digitized image-detector outputs are processed in the spatial-frequency (Fourier-transform) domain to obtain measures of the piston, tip, and tilt errors over each segment or subaperture. Once these measures are known, they are fed back to the actuators to correct the errors. In addition, measures of errors that remain after correction by use of the actuators are further utilized in an algorithm in which the image is phase-corrected in the spatial-frequency domain and then transformed back to the spatial domain at each time step and summed with the images from all previous time steps to obtain a final image having a greater signal-to-noise ratio (and, hence, a visual quality) higher than would otherwise be attainable.

Beam Combination for Stellar Imager and its Application to Full-Aperture Imaging

NASA Technical Reports Server (NTRS)

Mozurkewich, D.; Carpenter, K. G.; Lyon, R. G.

2007-01-01

Stellar Imager (SI) will be a Space-Based telescope consisting of 20 to 30 separated apertures. It is designed for UV/Optical imaging of stellar surfaces and asteroseismology. This report describes details of an alternative optical design for the beam combiner, dubbed the Spatial Frequency Remapper (SFR). It sacrifices the large field of view of the Fizeau combiner. In return, spectral resolution is obtained with a diffraction grating rather than an array of energy-resolving detectors. The SFR design works in principle and has been implemented with MIRC at CHARA for a small number of apertures. Here, we show the number of optical surfaces can be reduced and the concept scales gracefully to the large number of apertures needed for Stellar Imager. We also describe a potential application of this spatial frequency remapping to improved imaging with filled aperture systems. For filled-aperture imaging, the SFR becomes the core of an improved aperture masking system. To date, aperture-masking has produced the best images with ground-based telescopes but at the expense of low sensitivity due to short exposures and discarding most of the light collected by the telescope. This design eliminates the light-loss problem previously claimed to be inherent in all aperture-masking designs. We also argue that at least in principle, the short-integration time limit can also be overcome. With these improvements, it becomes an ideal camera for TPF-C; since it can form speckle-free images in the presence of wavefront errors, it should significantly relax the stability requirements of the current designs.

A precise method for adjusting the optical system of laser sub-aperture

NASA Astrophysics Data System (ADS)

Song, Xing; Zhang, Xue-min; Yang, Jianfeng; Xue, Li

2018-02-01

In order to adapt to the requirement of modern astronomical observation and warfare, the resolution of the space telescope is needed to improve, sub-aperture stitching imaging technique is one method to improve the resolution, which could be used not only the foundation and space-based large optical systems, also used in laser transmission and microscopic imaging. A large aperture main mirror of sub-aperture stitching imaging system is composed of multiple sub-mirrors distributed according to certain laws. All sub-mirrors are off-axis mirror, so the alignment of sub-aperture stitching imaging system is more complicated than a single off-axis optical system. An alignment method based on auto-collimation imaging and interferometric imaging is introduced in this paper, by using this alignment method, a sub-aperture stitching imaging system which is composed of 12 sub-mirrors was assembled with high resolution, the beam coincidence precision is better than 0.01mm, and the system wave aberration is better than 0.05λ.

A denoising algorithm for CT image using low-rank sparse coding

NASA Astrophysics Data System (ADS)

Lei, Yang; Xu, Dong; Zhou, Zhengyang; Wang, Tonghe; Dong, Xue; Liu, Tian; Dhabaan, Anees; Curran, Walter J.; Yang, Xiaofeng

2018-03-01

We propose a denoising method of CT image based on low-rank sparse coding. The proposed method constructs an adaptive dictionary of image patches and estimates the sparse coding regularization parameters using the Bayesian interpretation. A low-rank approximation approach is used to simultaneously construct the dictionary and achieve sparse representation through clustering similar image patches. A variable-splitting scheme and a quadratic optimization are used to reconstruct CT image based on achieved sparse coefficients. We tested this denoising technology using phantom, brain and abdominal CT images. The experimental results showed that the proposed method delivers state-of-art denoising performance, both in terms of objective criteria and visual quality.

Terahertz near-field imaging using subwavelength plasmonic apertures and a quantum cascade laser source.

PubMed

Baragwanath, Adam J; Freeman, Joshua R; Gallant, Andrew J; Zeitler, J Axel; Beere, Harvey E; Ritchie, David A; Chamberlain, J Martyn

2011-07-01

The first demonstration, to our knowledge, of near-field imaging using subwavelength plasmonic apertures with a terahertz quantum cascade laser source is presented. "Bull's-eye" apertures, featuring subwavelength circular apertures flanked by periodic annular corrugations were created using a novel fabrication method. A fivefold increase in intensity was observed for plasmonic apertures over plain apertures of the same diameter. Detailed studies of the transmitted beam profiles were undertaken for apertures with both planarized and corrugated exit facets, with the former producing spatially uniform intensity profiles and subwavelength spatial resolution. Finally, a proof-of-concept imaging experiment is presented, where an inhomogeneous pharmaceutical drug coating is investigated.

Radarsat-1 and ERS InSAR analysis over southeastern coastal Louisiana: Implications for mapping water-level changes beneath swamp forests

USGS Publications Warehouse

Lu, Z.; Kwoun, Oh-Ig

2008-01-01

Detailed analysis of C-band European Remote Sensing 1 and 2 (ERS-1/ERS-2) and Radarsat-1 interferometric synthetic aperture radar (InSAR) imagery was conducted to study water-level changes of coastal wetlands of southeastern Louisiana. Radar backscattering and InSAR coherence suggest that the dominant radar backscattering mechanism for swamp forest and saline marsh is double-bounce backscattering, implying that InSAR images can be used to estimate water-level changes with unprecedented spatial details. On the one hand, InSAR images suggest that water-level changes over the study site can be dynamic and spatially heterogeneous and cannot be represented by readings from sparsely distributed gauge stations. On the other hand, InSAR phase measurements are disconnected by structures and other barriers and require absolute water-level measurements from gauge stations or other sources to convert InSAR phase values to absolute water-level changes. ?? 2006 IEEE.

Image super-resolution via sparse representation.

PubMed

Yang, Jianchao; Wright, John; Huang, Thomas S; Ma, Yi

2010-11-01

This paper presents a new approach to single-image super-resolution, based on sparse signal representation. Research on image statistics suggests that image patches can be well-represented as a sparse linear combination of elements from an appropriately chosen over-complete dictionary. Inspired by this observation, we seek a sparse representation for each patch of the low-resolution input, and then use the coefficients of this representation to generate the high-resolution output. Theoretical results from compressed sensing suggest that under mild conditions, the sparse representation can be correctly recovered from the downsampled signals. By jointly training two dictionaries for the low- and high-resolution image patches, we can enforce the similarity of sparse representations between the low resolution and high resolution image patch pair with respect to their own dictionaries. Therefore, the sparse representation of a low resolution image patch can be applied with the high resolution image patch dictionary to generate a high resolution image patch. The learned dictionary pair is a more compact representation of the patch pairs, compared to previous approaches, which simply sample a large amount of image patch pairs, reducing the computational cost substantially. The effectiveness of such a sparsity prior is demonstrated for both general image super-resolution and the special case of face hallucination. In both cases, our algorithm generates high-resolution images that are competitive or even superior in quality to images produced by other similar SR methods. In addition, the local sparse modeling of our approach is naturally robust to noise, and therefore the proposed algorithm can handle super-resolution with noisy inputs in a more unified framework.

Damage imaging using Lamb waves for SHM applications

NASA Astrophysics Data System (ADS)

Stepinski, Tadeusz; Ambroziński, Łukasz; Uhl, Tadeusz

2015-03-01

2-D ultrasonic arrays, due to their beam-steering capability and all azimuth angle coverage are a very promising tool for the inspection of plate-like structures using Lamb waves (LW). Contrary to the classical linear phased arrays (PAs) the 2D arrays enable unequivocal defect localization and they are even capable of mode selectivity of the received LWs . Recently, it has been shown that multistatic synthetic focusing (SF) algorithms applied for 2D arrays are much more effective than the classical phase array mode commonly used in NDT. The multistatic SF assumes multiple transmissions of elements in a transmitting aperture and off-line processing of the data acquired by a receiving aperture. In the simplest implementation of the technique, only a single multiplexed input and a number of output channels are required, which results in significant hardware simplification compared with the PA systems. On the one hand implementation of the multistatic SF to 2D arrays creates additional degrees of freedom during the design of the array topology, which complicates the array design process. On the other hand, it enables designing sparse arrays with performance similar to that of the fully populated dense arrays. In this paper we present a general systematic approach to the design and optimization of imaging systems based on the 2D array operating in the multistatic mode. We start from presenting principles of the SF schemes applied to LW imaging. Then, we outline the coarray concept and demonstrate how it can be used for reducing number of elements of the 2D arrays. Finally, efficient tools for the investigation and experimental verification of the designed 2D array prototypes are presented. The first step in the investigation is theoretical evaluation performed using frequency-dependent structure transfer function (STF), which enables approximate simulation of an array excited with a tone-burst in a dispersive medium. Finally, we show how scanning laser vibrometer, sensing waves in multiple points corresponding to the locations of the 2D receiving array elements, can be used as a tool for rapid experimental verification of the developed topologies. The presented methods are discussed in terms of the beampatterns and sparse versions of the fully populated array topologies are be presented. The effect of apodization applied to the array elements is also investigated. Both simulated and experimental results are included.

Side information in coded aperture compressive spectral imaging

NASA Astrophysics Data System (ADS)

Galvis, Laura; Arguello, Henry; Lau, Daniel; Arce, Gonzalo R.

2017-02-01

Coded aperture compressive spectral imagers sense a three-dimensional cube by using two-dimensional projections of the coded and spectrally dispersed source. These imagers systems often rely on FPA detectors, SLMs, micromirror devices (DMDs), and dispersive elements. The use of the DMDs to implement the coded apertures facilitates the capture of multiple projections, each admitting a different coded aperture pattern. The DMD allows not only to collect the sufficient number of measurements for spectrally rich scenes or very detailed spatial scenes but to design the spatial structure of the coded apertures to maximize the information content on the compressive measurements. Although sparsity is the only signal characteristic usually assumed for reconstruction in compressing sensing, other forms of prior information such as side information have been included as a way to improve the quality of the reconstructions. This paper presents the coded aperture design in a compressive spectral imager with side information in the form of RGB images of the scene. The use of RGB images as side information of the compressive sensing architecture has two main advantages: the RGB is not only used to improve the reconstruction quality but to optimally design the coded apertures for the sensing process. The coded aperture design is based on the RGB scene and thus the coded aperture structure exploits key features such as scene edges. Real reconstructions of noisy compressed measurements demonstrate the benefit of the designed coded apertures in addition to the improvement in the reconstruction quality obtained by the use of side information.

Laboratory demonstration of image reconstruction for coherent optical system of modular imaging collectors (COSMIC)

NASA Technical Reports Server (NTRS)

Traub, W. A.

1984-01-01

The first physical demonstration of the principle of image reconstruction using a set of images from a diffraction-blurred elongated aperture is reported. This is an optical validation of previous theoretical and numerical simulations of the COSMIC telescope array (coherent optical system of modular imaging collectors). The present experiment utilizes 17 diffraction blurred exposures of a laboratory light source, as imaged by a lens covered by a narrow-slit aperture; the aperture is rotated 10 degrees between each exposure. The images are recorded in digitized form by a CCD camera, Fourier transformed, numerically filtered, and added; the sum is then filtered and inverse Fourier transformed to form the final image. The image reconstruction process is found to be stable with respect to uncertainties in values of all physical parameters such as effective wavelength, rotation angle, pointing jitter, and aperture shape. Future experiments will explore the effects of low counting rates, autoguiding on the image, various aperture configurations, and separated optics.

Low-count PET image restoration using sparse representation

NASA Astrophysics Data System (ADS)

Li, Tao; Jiang, Changhui; Gao, Juan; Yang, Yongfeng; Liang, Dong; Liu, Xin; Zheng, Hairong; Hu, Zhanli

2018-04-01

In the field of positron emission tomography (PET), reconstructed images are often blurry and contain noise. These problems are primarily caused by the low resolution of projection data. Solving this problem by improving hardware is an expensive solution, and therefore, we attempted to develop a solution based on optimizing several related algorithms in both the reconstruction and image post-processing domains. As sparse technology is widely used, sparse prediction is increasingly applied to solve this problem. In this paper, we propose a new sparse method to process low-resolution PET images. Two dictionaries (D1 for low-resolution PET images and D2 for high-resolution PET images) are learned from a group real PET image data sets. Among these two dictionaries, D1 is used to obtain a sparse representation for each patch of the input PET image. Then, a high-resolution PET image is generated from this sparse representation using D2. Experimental results indicate that the proposed method exhibits a stable and superior ability to enhance image resolution and recover image details. Quantitatively, this method achieves better performance than traditional methods. This proposed strategy is a new and efficient approach for improving the quality of PET images.

Synthetic aperture imaging in astronomy and aerospace: introduction.

PubMed

Creech-Eakman, Michelle J; Carney, P Scott; Buscher, David F; Shao, Michael

2017-05-01

Aperture synthesis methods allow the reconstruction of images with the angular resolutions exceeding that of extremely large monolithic apertures by using arrays of smaller apertures together in combination. In this issue we present several papers with techniques relevant to amplitude interferometry, laser radar, and intensity interferometry applications.

Single-frequency 3D synthetic aperture imaging with dynamic metasurface antennas.

PubMed

Boyarsky, Michael; Sleasman, Timothy; Pulido-Mancera, Laura; Diebold, Aaron V; Imani, Mohammadreza F; Smith, David R

2018-05-20

Through aperture synthesis, an electrically small antenna can be used to form a high-resolution imaging system capable of reconstructing three-dimensional (3D) scenes. However, the large spectral bandwidth typically required in synthetic aperture radar systems to resolve objects in range often requires costly and complex RF components. We present here an alternative approach based on a hybrid imaging system that combines a dynamically reconfigurable aperture with synthetic aperture techniques, demonstrating the capability to resolve objects in three dimensions (3D), with measurements taken at a single frequency. At the core of our imaging system are two metasurface apertures, both of which consist of a linear array of metamaterial irises that couple to a common waveguide feed. Each metamaterial iris has integrated within it a diode that can be biased so as to switch the element on (radiating) or off (non-radiating), such that the metasurface antenna can produce distinct radiation profiles corresponding to different on/off patterns of the metamaterial element array. The electrically large size of the metasurface apertures enables resolution in range and one cross-range dimension, while aperture synthesis provides resolution in the other cross-range dimension. The demonstrated imaging capabilities of this system represent a step forward in the development of low-cost, high-performance 3D microwave imaging systems.

Experimental demonstration of tri-aperture Differential Synthetic Aperture Ladar

NASA Astrophysics Data System (ADS)

Zhao, Zhilong; Huang, Jianyu; Wu, Shudong; Wang, Kunpeng; Bai, Tao; Dai, Ze; Kong, Xinyi; Wu, Jin

2017-04-01

A tri-aperture Differential Synthetic Aperture Ladar (DSAL) is demonstrated in laboratory, which is configured by using one common aperture to transmit the illuminating laser and another two along-track receiving apertures to collect back-scattered laser signal for optical heterodyne detection. The image formation theory on this tri-aperture DSAL shows that there are two possible methods to reconstruct the azimuth Phase History Data (PHD) for aperture synthesis by following standard DSAL principle, either method resulting in a different matched filter as well as an azimuth image resolution. The experimental setup of the tri-aperture DSAL adopts a frequency chirped laser of about 40 mW in 1550 nm wavelength range as the illuminating source and an optical isolator composed of a polarizing beam-splitter and a quarter wave plate to virtually line the three apertures in the along-track direction. Various DSAL images up to target distance of 12.9 m are demonstrated using both PHD reconstructing methods.

Local structure preserving sparse coding for infrared target recognition

PubMed Central

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lianfa

2017-01-01

Sparse coding performs well in image classification. However, robust target recognition requires a lot of comprehensive template images and the sparse learning process is complex. We incorporate sparsity into a template matching concept to construct a local sparse structure matching (LSSM) model for general infrared target recognition. A local structure preserving sparse coding (LSPSc) formulation is proposed to simultaneously preserve the local sparse and structural information of objects. By adding a spatial local structure constraint into the classical sparse coding algorithm, LSPSc can improve the stability of sparse representation for targets and inhibit background interference in infrared images. Furthermore, a kernel LSPSc (K-LSPSc) formulation is proposed, which extends LSPSc to the kernel space to weaken the influence of the linear structure constraint in nonlinear natural data. Because of the anti-interference and fault-tolerant capabilities, both LSPSc- and K-LSPSc-based LSSM can implement target identification based on a simple template set, which just needs several images containing enough local sparse structures to learn a sufficient sparse structure dictionary of a target class. Specifically, this LSSM approach has stable performance in the target detection with scene, shape and occlusions variations. High performance is demonstrated on several datasets, indicating robust infrared target recognition in diverse environments and imaging conditions. PMID:28323824

Fracture size and transmissivity correlations: Implications for transport simulations in sparse three-dimensional discrete fracture networks following a truncated power law distribution of fracture size

NASA Astrophysics Data System (ADS)

Hyman, J. D.; Aldrich, G.; Viswanathan, H.; Makedonska, N.; Karra, S.

2016-08-01

We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semicorrelation, and noncorrelation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected so that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same. We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. These observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.

Fracture size and transmissivity correlations: Implications for transport simulations in sparse three-dimensional discrete fracture networks following a truncated power law distribution of fracture size

NASA Astrophysics Data System (ADS)

Hyman, J.; Aldrich, G. A.; Viswanathan, H. S.; Makedonska, N.; Karra, S.

2016-12-01

We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semi-correlation, and non-correlation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected so that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same.We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. These observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.

Dark-field microscopic image stitching method for surface defects evaluation of large fine optics.

PubMed

Liu, Dong; Wang, Shitong; Cao, Pin; Li, Lu; Cheng, Zhongtao; Gao, Xin; Yang, Yongying

2013-03-11

One of the challenges in surface defects evaluation of large fine optics is to detect defects of microns on surfaces of tens or hundreds of millimeters. Sub-aperture scanning and stitching is considered to be a practical and efficient method. But since there are usually few defects on the large aperture fine optics, resulting in no defects or only one run-through line feature in many sub-aperture images, traditional stitching methods encounter with mismatch problem. In this paper, a feature-based multi-cycle image stitching algorithm is proposed to solve the problem. The overlapping areas of sub-apertures are categorized based on the features they contain. Different types of overlapping areas are then stitched in different cycles with different methods. The stitching trace is changed to follow the one that determined by the features. The whole stitching procedure is a region-growing like process. Sub-aperture blocks grow bigger after each cycle and finally the full aperture image is obtained. Comparison experiment shows that the proposed method is very suitable to stitch sub-apertures that very few feature information exists in the overlapping areas and can stitch the dark-field microscopic sub-aperture images very well.

Synthetic aperture design for increased SAR image rate

DOEpatents

Bielek, Timothy P [Albuquerque, NM; Thompson, Douglas G [Albuqerque, NM; Walker, Bruce C [Albuquerque, NM

2009-03-03

High resolution SAR images of a target scene at near video rates can be produced by using overlapped, but nevertheless, full-size synthetic apertures. The SAR images, which respectively correspond to the apertures, can be analyzed in sequence to permit detection of movement in the target scene.

Differential Optical Synthetic Aperture Radar

DOEpatents

Stappaerts, Eddy A.

2005-04-12

A new differential technique for forming optical images using a synthetic aperture is introduced. This differential technique utilizes a single aperture to obtain unique (N) phases that can be processed to produce a synthetic aperture image at points along a trajectory. This is accomplished by dividing the aperture into two equal "subapertures", each having a width that is less than the actual aperture, along the direction of flight. As the platform flies along a given trajectory, a source illuminates objects and the two subapertures are configured to collect return signals. The techniques of the invention is designed to cancel common-mode errors, trajectory deviations from a straight line, and laser phase noise to provide the set of resultant (N) phases that can produce an image having a spatial resolution corresponding to a synthetic aperture.

Sparse Reconstruction Techniques in MRI: Methods, Applications, and Challenges to Clinical Adoption

PubMed Central

Yang, Alice Chieh-Yu; Kretzler, Madison; Sudarski, Sonja; Gulani, Vikas; Seiberlich, Nicole

2016-01-01

The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in Magnetic Resonance Imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstructions, they all rely on the idea that a priori information about the sparsity of MR images can be employed to reconstruct full images from undersampled data. This review describes the basic ideas behind sparse reconstruction techniques, how they could be applied to improve MR imaging, and the open challenges to their general adoption in a clinical setting. The fundamental principles underlying different classes of sparse reconstructions techniques are examined, and the requirements that each make on the undersampled data outlined. Applications that could potentially benefit from the accelerations that sparse reconstructions could provide are described, and clinical studies using sparse reconstructions reviewed. Lastly, technical and clinical challenges to widespread implementation of sparse reconstruction techniques, including optimization, reconstruction times, artifact appearance, and comparison with current gold-standards, are discussed. PMID:27003227

Electromagnetic scattering analysis of a three-dimensional-cavity-backed aperture in an infinite ground plane using a combined finite element method/method of moments approach

NASA Technical Reports Server (NTRS)

Reddy, C. J.; Deshpande, Manohar D.; Cockrell, C. R.; Beck, F. B.

1995-01-01

A combined finite element method/method of moments (FEM/MoM) approach is used to analyze the electromagnetic scattering properties of a three-dimensional-cavity-backed aperture in an infinite ground plane. The FEM is used to formulate the fields inside the cavity, and the MoM (with subdomain bases) in both spectral and spatial domains is used to formulate the fields above the ground plane. Fields in the aperture and the cavity are solved using a system of equations resulting from the combination of the FEM and the MoM. By virtue of the FEM, this combined approach is applicable to all arbitrarily shaped cavities with inhomogeneous material fillings, and because of the subdomain bases used in the MoM, the apertures can be of any arbitrary shape. This approach leads to a partly sparse and partly full symmetric matrix, which is efficiently solved using a biconjugate gradient algorithm. Numerical results are presented to validate the analysis.

A Spherical Active Coded Aperture for 4π Gamma-ray Imaging

DOE PAGES

Hellfeld, Daniel; Barton, Paul; Gunter, Donald; ...

2017-09-22

Gamma-ray imaging facilitates the efficient detection, characterization, and localization of compact radioactive sources in cluttered environments. Fieldable detector systems employing active planar coded apertures have demonstrated broad energy sensitivity via both coded aperture and Compton imaging modalities. But, planar configurations suffer from a limited field-of-view, especially in the coded aperture mode. In order to improve upon this limitation, we introduce a novel design by rearranging the detectors into an active coded spherical configuration, resulting in a 4pi isotropic field-of-view for both coded aperture and Compton imaging. This work focuses on the low- energy coded aperture modality and the optimization techniquesmore » used to determine the optimal number and configuration of 1 cm 3 CdZnTe coplanar grid detectors on a 14 cm diameter sphere with 192 available detector locations.« less

Synthetic Aperture Acoustic Imaging of Non-Metallic Cords

DTIC Science & Technology

2012-04-01

Washington Headquarters Services , Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA, 22202-4302...collected with a research prototype synthetic aperture acoustic ( SAA ) imaging system. SAA imaging is an emerging technique that can serve as an...inexpensive alternative or logical complement to synthetic aperture radar (SAR). The SAA imaging system uses an acoustic transceiver (speaker and

Image fusion via nonlocal sparse K-SVD dictionary learning.

PubMed

Li, Ying; Li, Fangyi; Bai, Bendu; Shen, Qiang

2016-03-01

Image fusion aims to merge two or more images captured via various sensors of the same scene to construct a more informative image by integrating their details. Generally, such integration is achieved through the manipulation of the representations of the images concerned. Sparse representation plays an important role in the effective description of images, offering a great potential in a variety of image processing tasks, including image fusion. Supported by sparse representation, in this paper, an approach for image fusion by the use of a novel dictionary learning scheme is proposed. The nonlocal self-similarity property of the images is exploited, not only at the stage of learning the underlying description dictionary but during the process of image fusion. In particular, the property of nonlocal self-similarity is combined with the traditional sparse dictionary. This results in an improved learned dictionary, hereafter referred to as the nonlocal sparse K-SVD dictionary (where K-SVD stands for the K times singular value decomposition that is commonly used in the literature), and abbreviated to NL_SK_SVD. The performance of the NL_SK_SVD dictionary is applied for image fusion using simultaneous orthogonal matching pursuit. The proposed approach is evaluated with different types of images, and compared with a number of alternative image fusion techniques. The resultant superior fused images using the present approach demonstrates the efficacy of the NL_SK_SVD dictionary in sparse image representation.

Image quality affected by diffraction of aperture structure arrangement in transparent active-matrix organic light-emitting diode displays.

PubMed

Tsai, Yu-Hsiang; Huang, Mao-Hsiu; Jeng, Wei-de; Huang, Ting-Wei; Lo, Kuo-Lung; Ou-Yang, Mang

2015-10-01

Transparent display is one of the main technologies in next-generation displays, especially for augmented reality applications. An aperture structure is attached on each display pixel to partition them into transparent and black regions. However, diffraction blurs caused by the aperture structure typically degrade the transparent image when the light from a background object passes through finite aperture window. In this paper, the diffraction effect of an active-matrix organic light-emitting diode display (AMOLED) is studied. Several aperture structures have been proposed and implemented. Based on theoretical analysis and simulation, the appropriate aperture structure will effectively reduce the blur. The analysis data are also consistent with the experimental results. Compared with the various transparent aperture structure on AMOLED, diffraction width (zero energy position of diffraction pattern) of the optimize aperture structure can be reduced 63% and 31% in the x and y directions in CASE 3. Associated with a lenticular lens on the aperture structure, the improvement could reach to 77% and 54% of diffraction width in the x and y directions. Modulation transfer function and practical images are provided to evaluate the improvement of image blurs.

Self characterization of a coded aperture array for neutron source imaging

NASA Astrophysics Data System (ADS)

Volegov, P. L.; Danly, C. R.; Fittinghoff, D. N.; Guler, N.; Merrill, F. E.; Wilde, C. H.

2014-12-01

The neutron imaging system at the National Ignition Facility (NIF) is an important diagnostic tool for measuring the two-dimensional size and shape of the neutrons produced in the burning deuterium-tritium plasma during the stagnation stage of inertial confinement fusion implosions. Since the neutron source is small (˜100 μm) and neutrons are deeply penetrating (>3 cm) in all materials, the apertures used to achieve the desired 10-μm resolution are 20-cm long, triangular tapers machined in gold foils. These gold foils are stacked to form an array of 20 apertures for pinhole imaging and three apertures for penumbral imaging. These apertures must be precisely aligned to accurately place the field of view of each aperture at the design location, or the location of the field of view for each aperture must be measured. In this paper we present a new technique that has been developed for the measurement and characterization of the precise location of each aperture in the array. We present the detailed algorithms used for this characterization and the results of reconstructed sources from inertial confinement fusion implosion experiments at NIF.

4D Light Field Imaging System Using Programmable Aperture

NASA Technical Reports Server (NTRS)

Bae, Youngsam

2012-01-01

Complete depth information can be extracted from analyzing all angles of light rays emanated from a source. However, this angular information is lost in a typical 2D imaging system. In order to record this information, a standard stereo imaging system uses two cameras to obtain information from two view angles. Sometimes, more cameras are used to obtain information from more angles. However, a 4D light field imaging technique can achieve this multiple-camera effect through a single-lens camera. Two methods are available for this: one using a microlens array, and the other using a moving aperture. The moving-aperture method can obtain more complete stereo information. The existing literature suggests a modified liquid crystal panel [LC (liquid crystal) panel, similar to ones commonly used in the display industry] to achieve a moving aperture. However, LC panels cannot withstand harsh environments and are not qualified for spaceflight. In this regard, different hardware is proposed for the moving aperture. A digital micromirror device (DMD) will replace the liquid crystal. This will be qualified for harsh environments for the 4D light field imaging. This will enable an imager to record near-complete stereo information. The approach to building a proof-ofconcept is using existing, or slightly modified, off-the-shelf components. An SLR (single-lens reflex) lens system, which typically has a large aperture for fast imaging, will be modified. The lens system will be arranged so that DMD can be integrated. The shape of aperture will be programmed for single-viewpoint imaging, multiple-viewpoint imaging, and coded aperture imaging. The novelty lies in using a DMD instead of a LC panel to move the apertures for 4D light field imaging. The DMD uses reflecting mirrors, so any light transmission lost (which would be expected from the LC panel) will be minimal. Also, the MEMS-based DMD can withstand higher temperature and pressure fluctuation than a LC panel can. Robotics need near complete stereo images for their autonomous navigation, manipulation, and depth approximation. The imaging system can provide visual feedback

Low-order wavefront sensing for coronagraphic telescopes

NASA Astrophysics Data System (ADS)

Subedi, Hari; Kasdin, Jeremy; Peter Varnai

2018-01-01

Space telescopes equipped with a coronagraph to detect and characterize exoplanets must have the ability to sense and control low-order wavefront aberrations. Most concepts for low-order wavefront sensing use the starlight rejected by the coronagraph to sense these aberrations. The sensor must be able to make precise estimates and be robust to photon and read noise. A thorough study of various differential low-order wavefront sensors (LOWFSs) would be beneficial for future space-based observatories designed for exoplanet detection and characterization. In this talk, we will expand on the comparison of different LOWFSs that use the rejected starlight either from the coronagraphic focal plane or the Lyot plane to estimate these aberrations. We will also present the experimental results of the sparse aperture mask (SAM) LOWFS that we have designed at the Princeton High Contrast Imaging Lab (PHCIL).

A novel three-dimensional image reconstruction method for near-field coded aperture single photon emission computerized tomography

PubMed Central

Mu, Zhiping; Hong, Baoming; Li, Shimin; Liu, Yi-Hwa

2009-01-01

Coded aperture imaging for two-dimensional (2D) planar objects has been investigated extensively in the past, whereas little success has been achieved in imaging 3D objects using this technique. In this article, the authors present a novel method of 3D single photon emission computerized tomography (SPECT) reconstruction for near-field coded aperture imaging. Multiangular coded aperture projections are acquired and a stack of 2D images is reconstructed separately from each of the projections. Secondary projections are subsequently generated from the reconstructed image stacks based on the geometry of parallel-hole collimation and the variable magnification of near-field coded aperture imaging. Sinograms of cross-sectional slices of 3D objects are assembled from the secondary projections, and the ordered subset expectation and maximization algorithm is employed to reconstruct the cross-sectional image slices from the sinograms. Experiments were conducted using a customized capillary tube phantom and a micro hot rod phantom. Imaged at approximately 50 cm from the detector, hot rods in the phantom with diameters as small as 2.4 mm could be discerned in the reconstructed SPECT images. These results have demonstrated the feasibility of the authors’ 3D coded aperture image reconstruction algorithm for SPECT, representing an important step in their effort to develop a high sensitivity and high resolution SPECT imaging system. PMID:19544769

Synthetic aperture integration (SAI) algorithm for SAR imaging

DOEpatents

Chambers, David H; Mast, Jeffrey E; Paglieroni, David W; Beer, N. Reginald

2013-07-09

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Research on segmentation based on multi-atlas in brain MR image

NASA Astrophysics Data System (ADS)

Qian, Yuejing

2018-03-01

Accurate segmentation of specific tissues in brain MR image can be effectively achieved with the multi-atlas-based segmentation method, and the accuracy mainly depends on the image registration accuracy and fusion scheme. This paper proposes an automatic segmentation method based on the multi-atlas for brain MR image. Firstly, to improve the registration accuracy in the area to be segmented, we employ a target-oriented image registration method for the refinement. Then In the label fusion, we proposed a new algorithm to detect the abnormal sparse patch and simultaneously abandon the corresponding abnormal sparse coefficients, this method is made based on the remaining sparse coefficients combined with the multipoint label estimator strategy. The performance of the proposed method was compared with those of the nonlocal patch-based label fusion method (Nonlocal-PBM), the sparse patch-based label fusion method (Sparse-PBM) and majority voting method (MV). Based on our experimental results, the proposed method is efficient in the brain MR images segmentation compared with MV, Nonlocal-PBM, and Sparse-PBM methods.

Optical coherence tomography retinal image reconstruction via nonlocal weighted sparse representation

NASA Astrophysics Data System (ADS)

Abbasi, Ashkan; Monadjemi, Amirhassan; Fang, Leyuan; Rabbani, Hossein

2018-03-01

We present a nonlocal weighted sparse representation (NWSR) method for reconstruction of retinal optical coherence tomography (OCT) images. To reconstruct a high signal-to-noise ratio and high-resolution OCT images, utilization of efficient denoising and interpolation algorithms are necessary, especially when the original data were subsampled during acquisition. However, the OCT images suffer from the presence of a high level of noise, which makes the estimation of sparse representations a difficult task. Thus, the proposed NWSR method merges sparse representations of multiple similar noisy and denoised patches to better estimate a sparse representation for each patch. First, the sparse representation of each patch is independently computed over an overcomplete dictionary, and then a nonlocal weighted sparse coefficient is computed by averaging representations of similar patches. Since the sparsity can reveal relevant information from noisy patches, combining noisy and denoised patches' representations is beneficial to obtain a more robust estimate of the unknown sparse representation. The denoised patches are obtained by applying an off-the-shelf image denoising method and our method provides an efficient way to exploit information from noisy and denoised patches' representations. The experimental results on denoising and interpolation of spectral domain OCT images demonstrated the effectiveness of the proposed NWSR method over existing state-of-the-art methods.

ImSyn: photonic image synthesis applied to synthetic aperture radar, microscopy, and ultrasound imaging

NASA Astrophysics Data System (ADS)

Turpin, Terry M.; Lafuse, James L.

1993-02-01

ImSynTM is an image synthesis technology, developed and patented by Essex Corporation. ImSynTM can provide compact, low cost, and low power solutions to some of the most difficult image synthesis problems existing today. The inherent simplicity of ImSynTM enables the manufacture of low cost and reliable photonic systems for imaging applications ranging from airborne reconnaissance to doctor's office ultrasound. The initial application of ImSynTM technology has been to SAR processing; however, it has a wide range of applications such as: image correlation, image compression, acoustic imaging, x-ray tomographic (CAT, PET, SPECT), magnetic resonance imaging (MRI), microscopy, range- doppler mapping (extended TDOA/FDOA). This paper describes ImSynTM in terms of synthetic aperture microscopy and then shows how the technology can be extended to ultrasound and synthetic aperture radar. The synthetic aperture microscope (SAM) enables high resolution three dimensional microscopy with greater dynamic range than real aperture microscopes. SAM produces complex image data, enabling the use of coherent image processing techniques. Most importantly SAM produces the image data in a form that is easily manipulated by a digital image processing workstation.

Spatial imaging of UV emission from Jupiter and Saturn

NASA Technical Reports Server (NTRS)

Clarke, J. T.; Moos, H. W.

1981-01-01

Spatial imaging with the IUE is accomplished both by moving one of the apertures in a series of exposures and within the large aperture in a single exposure. The image of the field of view subtended by the large aperture is focussed directly onto the detector camera face at each wavelength; since the spatial resolution of the instrument is 5 to 6 arc sec and the aperture extends 23.0 by 10.3 arc sec, imaging both parallel and perpendicular to dispersion is possible in a single exposure. The correction for the sensitivity variation along the slit at 1216 A is obtained from exposures of diffuse geocoronal H Ly alpha emission. The relative size of the aperture superimposed on the apparent discs of Jupiter and Saturn in typical observation is illustrated. By moving the planet image 10 to 20 arc sec along the major axis of the aperture (which is constrained to point roughly north-south) maps of the discs of these planets are obtained with 6 arc sec spatial resolution.

Switched Antenna Array Tile for Real-Time Microwave Imaging Aperture

DTIC Science & Technology

2016-06-26

Switched Antenna Array Tile for Real -Time Microwave Imaging Aperture William F. Moulder, Janusz J. Majewski, Charles M. Coldwell, James D. Krieger...Fast Imaging Algorithm 10mm 250mm Switched Array Tile Fig. 1. Diagram of real -time imaging array, with fabricated antenna tile. except for antenna...formed. IV. CONCLUSIONS A switched array tile to be used in a real time imaging aperture has been presented. Design and realization of the tile were

Theoretical characterization of annular array as a volumetric optoacoustic ultrasound handheld probe

NASA Astrophysics Data System (ADS)

Kalkhoran, Mohammad Azizian; Vray, Didier

2018-02-01

Optoacoustic ultrasound (OPUS) is a promising hybridized technique for simultaneous acquisition of functional and morphological data. The optical specificity of optoacoustic leverages the diagnostic aptitude of ultrasonography beyond anatomy. However, this integration has been rarely practiced for volumetric imaging. The challenge lies in the effective imaging probes that preserve the functionality of both modalities. The potentials of a sparse annular array for volumetric OPUS imaging are theoretically investigated. In order to evaluate and optimize the performance characteristics of the probe, series of analysis in the framework of system model matrix was carried out. The two criteria of voxel crosstalk and eigenanalysis have been employed to unveil information about the spatial sensitivity, aliasing, and number of definable spatial frequency components. Based on these benchmarks, the optimal parameters for volumetric handheld probe are determined. In particular, the number, size, and the arrangement of the elements and overall aperture dimension were investigated. The result of the numerical simulation suggests that the segmented-annular array of 128 negatively focused elements with 1λ × 20λ size, operating at 5-MHz central frequency showcases a good agreement with the physical requirement of both imaging systems. We hypothesize that these features enable a high-throughput volumetric passive/active ultrasonic imaging system with great potential for clinical applications.

Near-Field Terahertz Transmission Imaging at 0.210 Terahertz Using a Simple Aperture Technique

DTIC Science & Technology

2015-10-01

This report discusses a simple aperture useful for terahertz near-field imaging at .2010 terahertz ( lambda = 1.43 millimeters). The aperture requires...achieve a spatial resolution of lambda /7. The aperture can be scaled with the assistance of machinery found in conventional machine shops to achieve similar results using shorter terahertz wavelengths.

APT: Aperture Photometry Tool

NASA Astrophysics Data System (ADS)

Laher, Russ

2012-08-01

Aperture Photometry Tool (APT) is software for astronomers and students interested in manually exploring the photometric qualities of astronomical images. It has a graphical user interface (GUI) which allows the image data associated with aperture photometry calculations for point and extended sources to be visualized and, therefore, more effectively analyzed. Mouse-clicking on a source in the displayed image draws a circular or elliptical aperture and sky annulus around the source and computes the source intensity and its uncertainty, along with several commonly used measures of the local sky background and its variability. The results are displayed and can be optionally saved to an aperture-photometry-table file and plotted on graphs in various ways using functions available in the software. APT is geared toward processing sources in a small number of images and is not suitable for bulk processing a large number of images, unlike other aperture photometry packages (e.g., SExtractor). However, APT does have a convenient source-list tool that enables calculations for a large number of detections in a given image. The source-list tool can be run either in automatic mode to generate an aperture photometry table quickly or in manual mode to permit inspection and adjustment of the calculation for each individual detection. APT displays a variety of useful graphs, including image histogram, and aperture slices, source scatter plot, sky scatter plot, sky histogram, radial profile, curve of growth, and aperture-photometry-table scatter plots and histograms. APT has functions for customizing calculations, including outlier rejection, pixel “picking” and “zapping,” and a selection of source and sky models. The radial-profile-interpolation source model, accessed via the radial-profile-plot panel, allows recovery of source intensity from pixels with missing data and can be especially beneficial in crowded fields.

Foucault imaging by using non-dedicated transmission electron microscope

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

Taniguchi, Yoshifumi; Matsumoto, Hiroaki; Harada, Ken

2012-08-27

An electron optical system for observing Foucault images was constructed using a conventional transmission electron microscope without any special equipment for Lorentz microscopy. The objective lens was switched off and an electron beam was converged by a condenser optical system to the crossover on the selected area aperture plane. The selected area aperture was used as an objective aperture to select the deflected beam for Foucault mode, and the successive image-forming lenses were controlled for observation of the specimen images. The irradiation area on the specimen was controlled by selecting the appropriate diameter of the condenser aperture.

Deep Marginalized Sparse Denoising Auto-Encoder for Image Denoising

NASA Astrophysics Data System (ADS)

Ma, Hongqiang; Ma, Shiping; Xu, Yuelei; Zhu, Mingming

2018-01-01

Stacked Sparse Denoising Auto-Encoder (SSDA) has been successfully applied to image denoising. As a deep network, the SSDA network with powerful data feature learning ability is superior to the traditional image denoising algorithms. However, the algorithm has high computational complexity and slow convergence rate in the training. To address this limitation, we present a method of image denoising based on Deep Marginalized Sparse Denoising Auto-Encoder (DMSDA). The loss function of Sparse Denoising Auto-Encoder is marginalized so that it satisfies both sparseness and marginality. The experimental results show that the proposed algorithm can not only outperform SSDA in the convergence speed and training time, but also has better denoising performance than the current excellent denoising algorithms, including both the subjective and objective evaluation of image denoising.

SAVI: Synthetic apertures for long-range, subdiffraction-limited visible imaging using Fourier ptychography

PubMed Central

Holloway, Jason; Wu, Yicheng; Sharma, Manoj K.; Cossairt, Oliver; Veeraraghavan, Ashok

2017-01-01

Synthetic aperture radar is a well-known technique for improving resolution in radio imaging. Extending these synthetic aperture techniques to the visible light domain is not straightforward because optical receivers cannot measure phase information. We propose to use macroscopic Fourier ptychography (FP) as a practical means of creating a synthetic aperture for visible imaging to achieve subdiffraction-limited resolution. We demonstrate the first working prototype for macroscopic FP in a reflection imaging geometry that is capable of imaging optically rough objects. In addition, a novel image space denoising regularization is introduced during phase retrieval to reduce the effects of speckle and improve perceptual quality of the recovered high-resolution image. Our approach is validated experimentally where the resolution of various diffuse objects is improved sixfold. PMID:28439550

Electron microscope aperture system

NASA Technical Reports Server (NTRS)

Heinemann, K. (Inventor)

1976-01-01

An electron microscope including an electron source, a condenser lens having either a circular aperture for focusing a solid cone of electrons onto a specimen or an annular aperture for focusing a hollow cone of electrons onto the specimen, and an objective lens having an annular objective aperture, for focusing electrons passing through the specimen onto an image plane are described. The invention also entails a method of making the annular objective aperture using electron imaging, electrolytic deposition and ion etching techniques.

Magnetic Resonance Super-resolution Imaging Measurement with Dictionary-optimized Sparse Learning

NASA Astrophysics Data System (ADS)

Li, Jun-Bao; Liu, Jing; Pan, Jeng-Shyang; Yao, Hongxun

2017-06-01

Magnetic Resonance Super-resolution Imaging Measurement (MRIM) is an effective way of measuring materials. MRIM has wide applications in physics, chemistry, biology, geology, medical and material science, especially in medical diagnosis. It is feasible to improve the resolution of MR imaging through increasing radiation intensity, but the high radiation intensity and the longtime of magnetic field harm the human body. Thus, in the practical applications the resolution of hardware imaging reaches the limitation of resolution. Software-based super-resolution technology is effective to improve the resolution of image. This work proposes a framework of dictionary-optimized sparse learning based MR super-resolution method. The framework is to solve the problem of sample selection for dictionary learning of sparse reconstruction. The textural complexity-based image quality representation is proposed to choose the optimal samples for dictionary learning. Comprehensive experiments show that the dictionary-optimized sparse learning improves the performance of sparse representation.

Self characterization of a coded aperture array for neutron source imaging

DOE PAGES

Volegov, P. L.; Danly, C. R.; Fittinghoff, D. N.; ...

2014-12-15

The neutron imaging system at the National Ignition Facility (NIF) is an important diagnostic tool for measuring the two-dimensional size and shape of the neutrons produced in the burning DT plasma during the stagnation stage of ICF implosions. Since the neutron source is small (~100 μm) and neutrons are deeply penetrating (>3 cm) in all materials, the apertures used to achieve the desired 10-μm resolution are 20-cm long, triangular tapers machined in gold foils. These gold foils are stacked to form an array of 20 apertures for pinhole imaging and three apertures for penumbral imaging. These apertures must be preciselymore » aligned to accurately place the field of view of each aperture at the design location, or the location of the field of view for each aperture must be measured. In this paper we present a new technique that has been developed for the measurement and characterization of the precise location of each aperture in the array. We present the detailed algorithms used for this characterization and the results of reconstructed sources from inertial confinement fusion implosion experiments at NIF.« less

Evaluation of the CT Parameters to Suppress Renal Cysts Pseudoenhancement Effect: Influence of the Virtual Monochromatic Spectral Images, the Model-based Iterative Reconstruction Algorithm and the Aperture Size in Phantom Model.

PubMed

Sugisawa, Koichi; Ichikawa, Katsuhiro; Minamishima, Kazuya; Hasegawa, Masakazu; Yamada, Yoshitake; Jinzaki, Masahiro

2017-01-01

The purpose of this study was to evaluate the effect of the virtual monochromatic spectral images (VMSI) and the model-based iterative reconstruction (MBIR) images, to evaluate the influence of the aperture size (40- and 20-mm beam) on renal pseudoenhancement (PE) compared with the filtered back projection (FBP) images. The renal compartment-CT phantom was filled with iodinated contrast material diluted to the attenuation of 180 Hounsfield units (HU) at 120 kV. The water-filled spherical structures, which simulate cyst, were inserted into the renal compartment. Those diameters were 7, 15 and 25 mm. These were scanned by conventional mode (helical scan, 120 kV-FBP) and dual energy mode. 70 keV-VMSI were reconstructed from the dual energy mode, and MBIR images were reconstructed from conventional mode at 40- and 20-mm aperture. Additionally, the phantom was scanned using non-helical mode with 20-mm aperture, and FBP images were reconstructed. The CT value of the PE for cyst areas was measured for these images. The CT values of the cysts were 20.0-14.3 HU on the FBP images, 12.8-12.7 HU on the 70 keV-VMSI (PE-inhibition ratio was 36.0-11.2%) and 16.2-14.0 HU on the MBIR images (19.0-2.1%), respectively, at 40-mm aperture. The PE-inhibition ratio scanned by 20-mm aperture was improved by 28.0% with FBP, 32.8% with 70 keV-VMSI and 29.6% with MBIR compared with 40-mm aperture. One of the FBP images with non-helical mode was 11.6 HU. The best CT technique to minimize PE was the combination of 70 keV-VMSI and 20-mm aperture.

Fracture size and transmissivity correlations: Implications for transport simulations in sparse three-dimensional discrete fracture networks following a truncated power law distribution of fracture size

DOE PAGES

Hyman, Jeffrey De'Haven; Aldrich, Garrett Allen; Viswanathan, Hari S.; ...

2016-08-01

We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semicorrelation, and noncorrelation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected somore » that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same. We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. Lastly, these observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.« less

Fracture size and transmissivity correlations: Implications for transport simulations in sparse three-dimensional discrete fracture networks following a truncated power law distribution of fracture size

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

Hyman, Jeffrey De'Haven; Aldrich, Garrett Allen; Viswanathan, Hari S.

We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semicorrelation, and noncorrelation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected somore » that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same. We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. Lastly, these observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.« less

Medical image classification based on multi-scale non-negative sparse coding.

PubMed

Zhang, Ruijie; Shen, Jian; Wei, Fushan; Li, Xiong; Sangaiah, Arun Kumar

2017-11-01

With the rapid development of modern medical imaging technology, medical image classification has become more and more important in medical diagnosis and clinical practice. Conventional medical image classification algorithms usually neglect the semantic gap problem between low-level features and high-level image semantic, which will largely degrade the classification performance. To solve this problem, we propose a multi-scale non-negative sparse coding based medical image classification algorithm. Firstly, Medical images are decomposed into multiple scale layers, thus diverse visual details can be extracted from different scale layers. Secondly, for each scale layer, the non-negative sparse coding model with fisher discriminative analysis is constructed to obtain the discriminative sparse representation of medical images. Then, the obtained multi-scale non-negative sparse coding features are combined to form a multi-scale feature histogram as the final representation for a medical image. Finally, SVM classifier is combined to conduct medical image classification. The experimental results demonstrate that our proposed algorithm can effectively utilize multi-scale and contextual spatial information of medical images, reduce the semantic gap in a large degree and improve medical image classification performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Method of forming aperture plate for electron microscope

NASA Technical Reports Server (NTRS)

Heinemann, K. (Inventor)

1974-01-01

An electron microscope is described with an electron source a condenser lens having either a circular aperture for focusing a solid cone of electrons onto a specimen or an annular aperture for focusing a hollow cone of electrons onto the specimen. It also has objective lens with an annular objective aperture, for focusing electrons passing through the specimen onto an image plane. A method of making the annular objective aperture using electron imaging, electrolytic deposition and ion etching techniques is included.

Classification of multispectral or hyperspectral satellite imagery using clustering of sparse approximations on sparse representations in learned dictionaries obtained using efficient convolutional sparse coding

DOEpatents

Moody, Daniela; Wohlberg, Brendt

2018-01-02

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

Sparse ice: Geophysical, biological and Indigenous knowledge perspectives on a habitat for ice-associated fauna

NASA Astrophysics Data System (ADS)

Lee, O. A.; Eicken, H.; Weyapuk, W., Jr.; Adams, B.; Mohoney, A. R.

2015-12-01

The significance of highly dispersed, remnant Arctic sea ice as a platform for marine mammals and indigenous hunters in spring and summer may have increased disproportionately with changes in the ice cover. As dispersed remnant ice becomes more common in the future it will be increasingly important to understand its ecological role for upper trophic levels such as marine mammals and its role for supporting primary productivity of ice-associated algae. Potential sparse ice habitat at sea ice concentrations below 15% is difficult to detect using remote sensing data alone. A combination of high resolution satellite imagery (including Synthetic Aperture Radar), data from the Barrow sea ice radar, and local observations from indigenous sea ice experts was used to detect sparse sea ice in the Alaska Arctic. Traditional knowledge on sea ice use by marine mammals was used to delimit the scales where sparse ice could still be used as habitat for seals and walrus. Potential sparse ice habitat was quantified with respect to overall spatial extent, size of ice floes, and density of floes. Sparse ice persistence offshore did not prevent the occurrence of large coastal walrus haul outs, but the lack of sparse ice and early sea ice retreat coincided with local observations of ringed seal pup mortality. Observations from indigenous hunters will continue to be an important source of information for validating remote sensing detections of sparse ice, and improving understanding of marine mammal adaptations to sea ice change.

Saturation of the anisoplanatic error in horizontal imaging scenarios

NASA Astrophysics Data System (ADS)

Beck, Jeffrey; Bos, Jeremy P.

2017-09-01

We evaluate the piston-removed anisoplanatic error for smaller apertures imaging over long horizontal paths. Previous works have shown that the piston and tilt compensated anisoplanatic error saturates to values less than one squared radian. Under these conditions the definition of the isoplanatic angle is unclear. These works focused on nadir pointing telescope systems with aperture sizes between five meters and one half meter. We directly extend this work to horizontal imaging scenarios with aperture sizes smaller than one half meter. We assume turbulence is constant along the imaging path and that the ratio of the aperture size to the atmospheric coherence length is on the order of unity.

Oblong-Shaped-Focused Transducers for Intravascular Ultrasound Imaging.

PubMed

Lee, Junsu; Jang, Jihun; Chang, Jin Ho

2017-03-01

In intravascular ultrasound (IVUS) imaging, a transducer is inserted into a blood vessel and rotated to obtain image data. For this purpose, the transducer aperture is typically less than 0.5 mm in diameter, which causes natural focusing to occur in the imaging depth ranging from 1 to 5 mm. Due to the small aperture, however, it is not viable to conduct geometric focusing in order to enhance the spatial resolution of IVUS images. Furthermore, this hampers narrowing the slice thickness of a cross-sectional scan plane in the imaging depth, which leads to lowering spatial and contrast resolutions of IVUS images. To solve this problem, we propose an oblong-shaped-focused transducer for IVUS imaging. Unlike the conventional IVUS transducers with either a circular or a square flat aperture, the proposed transducer has an oblong aperture of which long side is positioned along a blood vessel. This unique configuration makes it possible to conduct geometric focusing at a desired depth in the elevation direction. In this study, furthermore, it is demonstrated that a spherically shaped aperture in both lateral and elevation directions also improves lateral resolution, compared to the conventional flat aperture. To ascertain this, the conventional and the proposed IVUS transducers were designed and fabricated to evaluate and to compare their imaging performances through wire phantom and tissue-mimicking phantom experiments. For the proposed 50-MHz IVUS transducer, a PZT piece of 0.5 × 1.0 mm 2 was spherically shaped for elevation focus at 3 mm by using the conventional press-focusing technique whereas the conventional one has a flat aperture of 0.5 × 0.5 mm 2 . The experimental results demonstrated that the proposed IVUS transducer is capable of improving spatial and contrast resolutions of IVUS images.

Tomographic Imaging of a Forested Area By Airborne Multi-Baseline P-Band SAR.

PubMed

Frey, Othmar; Morsdorf, Felix; Meier, Erich

2008-09-24

In recent years, various attempts have been undertaken to obtain information about the structure of forested areas from multi-baseline synthetic aperture radar data. Tomographic processing of such data has been demonstrated for airborne L-band data but the quality of the focused tomographic images is limited by several factors. In particular, the common Fourierbased focusing methods are susceptible to irregular and sparse sampling, two problems, that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. In this paper, a tomographic focusing method based on the time-domain back-projection algorithm is proposed, which maintains the geometric relationship between the original sensor positions and the imaged target and is therefore able to cope with irregular sampling without introducing any approximations with respect to the geometry. The tomographic focusing quality is assessed by analysing the impulse response of simulated point targets and an in-scene corner reflector. And, in particular, several tomographic slices of a volume representing a forested area are given. The respective P-band tomographic data set consisting of eleven flight tracks has been acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR).

Group-sparse representation with dictionary learning for medical image denoising and fusion.

PubMed

Li, Shutao; Yin, Haitao; Fang, Leyuan

2012-12-01

Recently, sparse representation has attracted a lot of interest in various areas. However, the standard sparse representation does not consider the intrinsic structure, i.e., the nonzero elements occur in clusters, called group sparsity. Furthermore, there is no dictionary learning method for group sparse representation considering the geometrical structure of space spanned by atoms. In this paper, we propose a novel dictionary learning method, called Dictionary Learning with Group Sparsity and Graph Regularization (DL-GSGR). First, the geometrical structure of atoms is modeled as the graph regularization. Then, combining group sparsity and graph regularization, the DL-GSGR is presented, which is solved by alternating the group sparse coding and dictionary updating. In this way, the group coherence of learned dictionary can be enforced small enough such that any signal can be group sparse coded effectively. Finally, group sparse representation with DL-GSGR is applied to 3-D medical image denoising and image fusion. Specifically, in 3-D medical image denoising, a 3-D processing mechanism (using the similarity among nearby slices) and temporal regularization (to perverse the correlations across nearby slices) are exploited. The experimental results on 3-D image denoising and image fusion demonstrate the superiority of our proposed denoising and fusion approaches.

A finite element-boundary integral formulation for scattering by three-dimensional cavity-backed apertures

NASA Technical Reports Server (NTRS)

Jin, Jian-Ming; Volakis, John L.

1990-01-01

A numerical technique is proposed for the electromagnetic characterization of the scattering by a three-dimensional cavity-backed aperture in an infinite ground plane. The technique combines the finite element and boundary integral methods to formulate a system of equations for the solution of the aperture fields and those inside the cavity. Specifically, the finite element method is employed to formulate the fields in the cavity region and the boundary integral approach is used in conjunction with the equivalence principle to represent the fields above the ground plane. Unlike traditional approaches, the proposed technique does not require knowledge of the cavity's Green's function and is, therefore, applicable to arbitrary shape depressions and material fillings. Furthermore, the proposed formulation leads to a system having a partly full and partly sparse as well as symmetric and banded matrix which can be solved efficiently using special algorithms.

Microstructure Images Restoration of Metallic Materials Based upon KSVD and Smoothing Penalty Sparse Representation Approach.

PubMed

Li, Qing; Liang, Steven Y

2018-04-20

Microstructure images of metallic materials play a significant role in industrial applications. To address image degradation problem of metallic materials, a novel image restoration technique based on K-means singular value decomposition (KSVD) and smoothing penalty sparse representation (SPSR) algorithm is proposed in this work, the microstructure images of aluminum alloy 7075 (AA7075) material are used as examples. To begin with, to reflect the detail structure characteristics of the damaged image, the KSVD dictionary is introduced to substitute the traditional sparse transform basis (TSTB) for sparse representation. Then, due to the image restoration, modeling belongs to a highly underdetermined equation, and traditional sparse reconstruction methods may cause instability and obvious artifacts in the reconstructed images, especially reconstructed image with many smooth regions and the noise level is strong, thus the SPSR (here, q = 0.5) algorithm is designed to reconstruct the damaged image. The results of simulation and two practical cases demonstrate that the proposed method has superior performance compared with some state-of-the-art methods in terms of restoration performance factors and visual quality. Meanwhile, the grain size parameters and grain boundaries of microstructure image are discussed before and after they are restored by proposed method.

Alternatively Constrained Dictionary Learning For Image Superresolution.

PubMed

Lu, Xiaoqiang; Yuan, Yuan; Yan, Pingkun

2014-03-01

Dictionaries are crucial in sparse coding-based algorithm for image superresolution. Sparse coding is a typical unsupervised learning method to study the relationship between the patches of high-and low-resolution images. However, most of the sparse coding methods for image superresolution fail to simultaneously consider the geometrical structure of the dictionary and the corresponding coefficients, which may result in noticeable superresolution reconstruction artifacts. In other words, when a low-resolution image and its corresponding high-resolution image are represented in their feature spaces, the two sets of dictionaries and the obtained coefficients have intrinsic links, which has not yet been well studied. Motivated by the development on nonlocal self-similarity and manifold learning, a novel sparse coding method is reported to preserve the geometrical structure of the dictionary and the sparse coefficients of the data. Moreover, the proposed method can preserve the incoherence of dictionary entries and provide the sparse coefficients and learned dictionary from a new perspective, which have both reconstruction and discrimination properties to enhance the learning performance. Furthermore, to utilize the model of the proposed method more effectively for single-image superresolution, this paper also proposes a novel dictionary-pair learning method, which is named as two-stage dictionary training. Extensive experiments are carried out on a large set of images comparing with other popular algorithms for the same purpose, and the results clearly demonstrate the effectiveness of the proposed sparse representation model and the corresponding dictionary learning algorithm.

Liver segmentation from CT images using a sparse priori statistical shape model (SP-SSM).

PubMed

Wang, Xuehu; Zheng, Yongchang; Gan, Lan; Wang, Xuan; Sang, Xinting; Kong, Xiangfeng; Zhao, Jie

2017-01-01

This study proposes a new liver segmentation method based on a sparse a priori statistical shape model (SP-SSM). First, mark points are selected in the liver a priori model and the original image. Then, the a priori shape and its mark points are used to obtain a dictionary for the liver boundary information. Second, the sparse coefficient is calculated based on the correspondence between mark points in the original image and those in the a priori model, and then the sparse statistical model is established by combining the sparse coefficients and the dictionary. Finally, the intensity energy and boundary energy models are built based on the intensity information and the specific boundary information of the original image. Then, the sparse matching constraint model is established based on the sparse coding theory. These models jointly drive the iterative deformation of the sparse statistical model to approximate and accurately extract the liver boundaries. This method can solve the problems of deformation model initialization and a priori method accuracy using the sparse dictionary. The SP-SSM can achieve a mean overlap error of 4.8% and a mean volume difference of 1.8%, whereas the average symmetric surface distance and the root mean square symmetric surface distance can reach 0.8 mm and 1.4 mm, respectively.

FWT2D: A massively parallel program for frequency-domain full-waveform tomography of wide-aperture seismic data—Part 1: Algorithm

NASA Astrophysics Data System (ADS)

Sourbier, Florent; Operto, Stéphane; Virieux, Jean; Amestoy, Patrick; L'Excellent, Jean-Yves

2009-03-01

This is the first paper in a two-part series that describes a massively parallel code that performs 2D frequency-domain full-waveform inversion of wide-aperture seismic data for imaging complex structures. Full-waveform inversion methods, namely quantitative seismic imaging methods based on the resolution of the full wave equation, are computationally expensive. Therefore, designing efficient algorithms which take advantage of parallel computing facilities is critical for the appraisal of these approaches when applied to representative case studies and for further improvements. Full-waveform modelling requires the resolution of a large sparse system of linear equations which is performed with the massively parallel direct solver MUMPS for efficient multiple-shot simulations. Efficiency of the multiple-shot solution phase (forward/backward substitutions) is improved by using the BLAS3 library. The inverse problem relies on a classic local optimization approach implemented with a gradient method. The direct solver returns the multiple-shot wavefield solutions distributed over the processors according to a domain decomposition driven by the distribution of the LU factors. The domain decomposition of the wavefield solutions is used to compute in parallel the gradient of the objective function and the diagonal Hessian, this latter providing a suitable scaling of the gradient. The algorithm allows one to test different strategies for multiscale frequency inversion ranging from successive mono-frequency inversion to simultaneous multifrequency inversion. These different inversion strategies will be illustrated in the following companion paper. The parallel efficiency and the scalability of the code will also be quantified.

System design of an optical interferometer based on compressive sensing

NASA Astrophysics Data System (ADS)

Liu, Gang; Wen, De-Sheng; Song, Zong-Xi

2018-07-01

In this paper, we develop a new optical interferometric telescope architecture based on compressive sensing (CS) theory. Traditional optical telescopes with large apertures must be large in size, heavy and have high-power consumption, which limits the development of space-based telescopes. A turning point has occurred in the advent of imaging technology that utilizes Fourier-domain interferometry. This technology can reduce the system size, weight and power consumption by an order of magnitude compared to traditional optical telescopes at the same resolution. CS theory demonstrates that incomplete and noisy Fourier measurements may suffice for the exact reconstruction of sparse or compressible signals. Our proposed architecture combines advantages from the two frameworks, and the performance is evaluated through simulations. The results indicate the ability to efficiently sample spatial frequencies, while being lightweight and compact in size. Another attractive property of our architecture is the strong denoising ability for Gaussian noise.

Land subsidence caused by the East Mesa geothermal field, California, observed using SAR interferometry

USGS Publications Warehouse

Massonnet, D.; Holzer, T.; Vadon, H.

1997-01-01

Interferometric combination of pairs of synthetic aperture radar (SAR) images acquired by the ERS-1 satellite maps the deformation field associated with the activity of the East Mesa geothermal plant, located in southern California. SAR interferometry is applied to this flat area without the need of a digital terrain model. Several combinations are used to ascertain the nature of the phenomenon. Short term interferograms reveal surface phase changes on agricultural fields similar to what had been observed previously with SEASAT radar data. Long term (2 years) interferograms allow the study of land subsidence and improve prior knowledge of the displacement field, and agree with existing, sparse levelling data. This example illustrates the power of the interferometric technique for deriving accurate industrial intelligence as well as its potential for legal action, in cases involving environmental damages. Copyright 1997 by the American Geophysical Union.

Formation Control of the MAXIM L2 Libration Orbit Mission

NASA Technical Reports Server (NTRS)

Folta, David; Hartman, Kate; Howell, Kathleen; Marchand, Belinda

2004-01-01

The Micro-Arcsecond Imaging Mission (MAXIM), a proposed concept for the Structure and Evolution of the Universe (SEU) Black Hole Imaging mission, is designed to make a ten million-fold improvement in X-ray image clarity of celestial objects by providing better than 0.1 microarcsecond imaging. To achieve mission requirements, MAXIM will have to improve on pointing by orders of magnitude. This pointing requirement impacts the control and design of the formation. Currently the architecture is comprised of 25 spacecraft, which will form the sparse apertures of a grazing incidence X-ray interferometer covering the 0.3-10 keV bandpass. This configuration will deploy 24 spacecraft as optics modules and one as the detector. The formation must allow for long duration continuous science observations and also for reconfiguration that permits re-pointing of the formation. In this paper, we provide analysis and trades of several control efforts that are dependent upon the pointing requirements and the configuration and dimensions of the MAXIM formation. We emphasize the utilization of natural motions in the Lagrangian regions that minimize the control efforts and we address both continuous and discrete control via LQR and feedback linearization. Results provide control cost, configuration options, and capabilities as guidelines for the development of this complex mission.

Inspection design using 2D phased array, TFM and cueMAP software

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

McGilp, Ailidh; Dziewierz, Jerzy; Lardner, Tim

2014-02-18

A simulation suite, cueMAP, has been developed to facilitate the design of inspection processes and sparse 2D array configurations. At the core of cueMAP is a Total Focusing Method (TFM) imaging algorithm that enables computer assisted design of ultrasonic inspection scenarios, including the design of bespoke array configurations to match the inspection criteria. This in-house developed TFM code allows for interactive evaluation of image quality indicators of ultrasonic imaging performance when utilizing a 2D phased array working in FMC/TFM mode. The cueMAP software uses a series of TFM images to build a map of resolution, contrast and sensitivity of imagingmore » performance of a simulated reflector, swept across the inspection volume. The software takes into account probe properties, wedge or water standoff, and effects of specimen curvature. In the validation process of this new software package, two 2D arrays have been evaluated on 304n stainless steel samples, typical of the primary circuit in nuclear plants. Thick section samples have been inspected using a 1MHz 2D matrix array. Due to the processing efficiency of the software, the data collected from these array configurations has been used to investigate the influence sub-aperture operation on inspection performance.« less

Central obscuration effects on optical synthetic aperture imaging

NASA Astrophysics Data System (ADS)

Wang, Xue-wen; Luo, Xiao; Zheng, Li-gong; Zhang, Xue-jun

2014-02-01

Due to the central obscuration problem exists in most optical synthetic aperture systems, it is necessary to analyze its effects on their image performance. Based on the incoherent diffraction limited imaging theory, a Golay-3 type synthetic aperture system was used to study the central obscuration effects on the point spread function (PSF) and the modulation transfer function (MTF). It was found that the central obscuration does not affect the width of the central peak of the PSF and the cutoff spatial frequency of the MTF, but attenuate the first sidelobe of the PSF and the midfrequency of the MTF. The imaging simulation of a Golay-3 type synthetic aperture system with central obscuration proved this conclusion. At last, a Wiener Filter restoration algorithm was used to restore the image of this system, the images were obviously better.

Wavefield properties of a shallow long-period event and tremor at Kilauea Volcano, Hawaii

USGS Publications Warehouse

Saccorotti, G.; Chouet, B.; Dawson, P.

2001-01-01

The wavefields of tremor and a long-period (LP) event associated with the ongoing eruptive activity at Kilauea Volcano, Hawaii, are investigated using a combination of dense small-aperture (300 m) and sparse large-aperture (5 km) arrays deployed in the vicinity of the summit caldera. Measurements of azimuth and slowness for tremor recorded on the small-aperture array indicate a bimodal nature of the observed wavefield. At frequencies below 2 Hz, the wavefield is dominated by body waves impinging the array with steep incidence. These arrivals are attributed to the oceanic microseismic noise. In the 2-6 Hz band, the wavefield is dominated by waves propagating from sources located at shallow depths (<1 km) beneath the eastern edge of the Halemaumau pit crater. The hypocenter of the LP event, determined from frequency-slowness analyses combined with phase picks, appears to be located close to the source of tremor but at a shallower depth (<0.1 km). The wavefields of tremor and LP event are characterized by a complex composition of body and surface waves, whose propagation and polarization properties are strongly affected by topographic and structural features in the summit caldera region. Analyses of the directional properties of the wavefield in the 2-6 Hz band point to the directions of main scattering sources, which are consistent with pronounced velocity contrasts imaged in a high-resolution three-dimensional velocity model of the caldera region. The frequency and Q of the dominant peak observed in the spectra of the LP event may be explained as the dominant oscillation mode of a crack with scale length 20-100 m and aperture of a few centimeters filled with bubbly water. The mechanism driving the shallow tremor appears to be consistent with a sustained excitation originating in the oscillations of a bubbly cloud resulting from vesiculation and degassing in the magma. ?? 2001 Elsevier Science B.V. All rights reserved.

Stellar Imager - Observing the Universe in High Definition

NASA Technical Reports Server (NTRS)

Carpenter, Kenneth

2009-01-01

Stellar Imager (SI) is a space-based, UV Optical Interferometer (UVOI) with over 200x the resolution of HST. It will enable 0.1 milli-arcsec spectral imaging of stellar surfaces and the Universe in general and open an enormous new 'discovery space' for Astrophysics with its combination of high angular resolution, dynamic imaging, and spectral energy resolution. SI's goal is to study the role of magnetism in the Universe and revolutionize our understanding of: 1) Solar/Stellar Magnetic Activity and their impact on Space Weather, Planetary Climates. and Life, 2) Magnetic and Accretion Processes and their roles in the Origin and Evolution of Structure and in the Transport of Matter throughout the Universe, 3) the close-in structure of Active Galactic Nuclei and their winds, and 4) Exo-Solar Planet Transits and Disks. The SI mission is targeted for the mid 2020's - thus significant technology development in the upcoming decade is critical to enabling it and future spacebased sparse aperture telescope and distributed spacecraft missions. The key technology needs include: 1) precision formation flying of many spacecraft, 2) precision metrology over km-scales, 3) closed-loop control of many-element, sparse optical arrays, 4) staged-control systems with very high dynamic ranges (nm to km-scale). It is critical that the importance of timely development of these capabilities is called out in the upcoming Astrophysics and Heliophysics Decadal Surveys, to enable the flight of such missions in the following decade. S1 is a 'Landmark/Discovery Mission' in 2005 Heliophysics Roadmap and a candidate UVOI in the 2006 Astrophysics Strategic Plan. It is a NASA Vision Mission ('NASA Space Science Vision Missions' (2008), ed. M. Allen) and has also been recommended for further study in the 2008 NRC interim report on missions potentially enabled enhanced by an Ares V' launch, although a incrementally-deployed version could be launched using smaller rockets.

Impulse Response Shaping for Ultra Wide Band SAR in a Circular Flight Path

NASA Technical Reports Server (NTRS)

Jin, Michael Y.

1996-01-01

An ultra wide band SAR (synthetic aperture radar) has potential applications on imaging underground objects. Flying this SAR in a circular flight path is an efficient way to acquire high resolution images from a localized area. This paper characterizes the impulse response of sucha system. The results indicate that to achieve an image with a more uniformed resolution over the entire imaged area, proper weighting coeficients should be applied to both the principle aperture and the complimentary aperture.

Laser fresnel distance measuring system and method

NASA Technical Reports Server (NTRS)

Campbell, Jonathan W. (Inventor); Lehner, David L. (Inventor); Smalley, Larry L. (Inventor); Smith, legal representative, Molly C. (Inventor); Sanders, Alvin J. (Inventor); Earl, Dennis Duncan (Inventor); Allison, Stephen W. (Inventor); Smith, Kelly L. (Inventor)

2008-01-01

A method and system for determining range to a target are provided. A beam of electromagnetic energy is transmitted through an aperture in an opaque screen such that a portion of the beam passes through the aperture to generate a region of diffraction that varies as a function of distance from the aperture. An imaging system is focused on a target plane in the region of diffraction with the generated image being compared to known diffraction patterns. Each known diffraction pattern has a unique value associated therewith that is indicative of a distance from the aperture. A match between the generated image and at least one of the known diffraction patterns is indicative of a distance between the aperture and target plane.

Subsurface Grain Morphology Reconstruction by Differential Aperture X-ray Microscopy

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

Eisenlohr, Philip; Shanthraj, Pratheek; Vande Kieft, Brendan R.

A multistep, non-destructive grain morphology reconstruction methodology that is applicable to near-surface volumes is developed and tested on synthetic grain structures. This approach probes the subsurface crystal orientation using differential aperture x-ray microscopy on a sparse grid across the microstructure volume of interest. Resulting orientation data are clustered according to proximity in physical and orientation space and used as seed points for an initial Voronoi tessellation to (crudely) approximate the grain morphology. Curvature-driven grain boundary relaxation, simulated by means of the Voronoi implicit interface method, progressively improves the reconstruction accuracy. The similarity between bulk and readily accessible surface reconstruction errormore » provides an objective termination criterion for boundary relaxation.« less

Total variation-based method for radar coincidence imaging with model mismatch for extended target

NASA Astrophysics Data System (ADS)

Cao, Kaicheng; Zhou, Xiaoli; Cheng, Yongqiang; Fan, Bo; Qin, Yuliang

2017-11-01

Originating from traditional optical coincidence imaging, radar coincidence imaging (RCI) is a staring/forward-looking imaging technique. In RCI, the reference matrix must be computed precisely to reconstruct the image as preferred; unfortunately, such precision is almost impossible due to the existence of model mismatch in practical applications. Although some conventional sparse recovery algorithms are proposed to solve the model-mismatch problem, they are inapplicable to nonsparse targets. We therefore sought to derive the signal model of RCI with model mismatch by replacing the sparsity constraint item with total variation (TV) regularization in the sparse total least squares optimization problem; in this manner, we obtain the objective function of RCI with model mismatch for an extended target. A more robust and efficient algorithm called TV-TLS is proposed, in which the objective function is divided into two parts and the perturbation matrix and scattering coefficients are updated alternately. Moreover, due to the ability of TV regularization to recover sparse signal or image with sparse gradient, TV-TLS method is also applicable to sparse recovering. Results of numerical experiments demonstrate that, for uniform extended targets, sparse targets, and real extended targets, the algorithm can achieve preferred imaging performance both in suppressing noise and in adapting to model mismatch.

The Effect of a Pre-Lens Aperture on the Temperature Range and Image Uniformity of Microbolometer Infrared Cameras

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

Dinwiddie, Ralph Barton; Parris, Larkin S.; Lindal, John M.

This paper explores the temperature range extension of long-wavelength infrared (LWIR) cameras by placing an aperture in front of the lens. An aperture smaller than the lens will reduce the radiance to the sensor, allowing the camera to image targets much hotter than typically allowable. These higher temperatures were accurately determined after developing a correction factor which was applied to the built-in temperature calibration. The relationship between aperture diameter and temperature range is linear. The effect of pre-lens apertures on the image uniformity is a form of anti-vignetting, meaning the corners appear brighter (hotter) than the rest of the image.more » An example of using this technique to measure temperatures of high melting point polymers during 3D printing provide valuable information of the time required for the weld-line temperature to fall below the glass transition temperature.« less

First imagery generated by near-field real-time aperture synthesis passive millimetre wave imagers at 94 GHz and 183 GHz

NASA Astrophysics Data System (ADS)

Salmon, Neil A.; Mason, Ian; Wilkinson, Peter; Taylor, Chris; Scicluna, Peter

2010-10-01

The first passive millimetre wave (PMMW) imagery is presented from two proof-of-concept aperture synthesis demonstrators, developed to investigate the use of aperture synthesis for personnel security screening and all weather flying at 94 GHz, and satellite based earth observation at 183 GHz [1]. Emission from point noise sources and discharge tubes are used to examine the coherence on system baselines and to measure the point spread functions, making comparisons with theory. Image quality is examined using near field aperture synthesis and G-matrix calibration imaging algorithms. The radiometric sensitivity is measured using the emission from absorbers at elevated temperatures acting as extended sources and compared with theory. Capabilities of the latest Field Programmable Gate Arrays (FPGA) technologies for aperture synthesis PMMW imaging in all-weather and security screening applications are examined.

Joint estimation of high resolution images and depth maps from light field cameras

NASA Astrophysics Data System (ADS)

Ohashi, Kazuki; Takahashi, Keita; Fujii, Toshiaki

2014-03-01

Light field cameras are attracting much attention as tools for acquiring 3D information of a scene through a single camera. The main drawback of typical lenselet-based light field cameras is the limited resolution. This limitation comes from the structure where a microlens array is inserted between the sensor and the main lens. The microlens array projects 4D light field on a single 2D image sensor at the sacrifice of the resolution; the angular resolution and the position resolution trade-off under the fixed resolution of the image sensor. This fundamental trade-off remains after the raw light field image is converted to a set of sub-aperture images. The purpose of our study is to estimate a higher resolution image from low resolution sub-aperture images using a framework of super-resolution reconstruction. In this reconstruction, these sub-aperture images should be registered as accurately as possible. This registration is equivalent to depth estimation. Therefore, we propose a method where super-resolution and depth refinement are performed alternatively. Most of the process of our method is implemented by image processing operations. We present several experimental results using a Lytro camera, where we increased the resolution of a sub-aperture image by three times horizontally and vertically. Our method can produce clearer images compared to the original sub-aperture images and the case without depth refinement.

In vivo visualization of robotically implemented synthetic tracked aperture ultrasound (STRATUS) imaging system using curvilinear array

NASA Astrophysics Data System (ADS)

Zhang, Haichong K.; Aalamifar, Fereshteh; Boctor, Emad M.

2016-04-01

Synthetic aperture for ultrasound is a technique utilizing a wide aperture in both transmit and receive to enhance the ultrasound image quality. The limitation of synthetic aperture is the maximum available aperture size limit determined by the physical size of ultrasound probe. We propose Synthetic-Tracked Aperture Ultrasound (STRATUS) imaging system to overcome the limitation by extending the beamforming aperture size through ultrasound probe tracking. With a setup involving a robotic arm, the ultrasound probe is moved using the robotic arm, while the positions on a scanning trajectory are tracked in real-time. Data from each pose are synthesized to construct a high resolution image. In previous studies, we have demonstrated the feasibility through phantom experiments. However, various additional factors such as real-time data collection or motion artifacts should be taken into account when the in vivo target becomes the subject. In this work, we build a robot-based STRATUS imaging system with continuous data collection capability considering the practical implementation. A curvilinear array is used instead of a linear array to benefit from its wider capture angle. We scanned human forearms under two scenarios: one submerged the arm in the water tank under 10 cm depth, and the other directly scanned the arm from the surface. The image contrast improved 5.51 dB, and 9.96 dB for the underwater scan and the direct scan, respectively. The result indicates the practical feasibility of STRATUS imaging system, and the technique can be potentially applied to the wide range of human body.

Precise Aperture-Dependent Motion Compensation with Frequency Domain Fast Back-Projection Algorithm.

PubMed

Zhang, Man; Wang, Guanyong; Zhang, Lei

2017-10-26

Precise azimuth-variant motion compensation (MOCO) is an essential and difficult task for high-resolution synthetic aperture radar (SAR) imagery. In conventional post-filtering approaches, residual azimuth-variant motion errors are generally compensated through a set of spatial post-filters, where the coarse-focused image is segmented into overlapped blocks concerning the azimuth-dependent residual errors. However, image domain post-filtering approaches, such as precise topography- and aperture-dependent motion compensation algorithm (PTA), have difficulty of robustness in declining, when strong motion errors are involved in the coarse-focused image. In this case, in order to capture the complete motion blurring function within each image block, both the block size and the overlapped part need necessary extension leading to degeneration of efficiency and robustness inevitably. Herein, a frequency domain fast back-projection algorithm (FDFBPA) is introduced to deal with strong azimuth-variant motion errors. FDFBPA disposes of the azimuth-variant motion errors based on a precise azimuth spectrum expression in the azimuth wavenumber domain. First, a wavenumber domain sub-aperture processing strategy is introduced to accelerate computation. After that, the azimuth wavenumber spectrum is partitioned into a set of wavenumber blocks, and each block is formed into a sub-aperture coarse resolution image via the back-projection integral. Then, the sub-aperture images are straightforwardly fused together in azimuth wavenumber domain to obtain a full resolution image. Moreover, chirp-Z transform (CZT) is also introduced to implement the sub-aperture back-projection integral, increasing the efficiency of the algorithm. By disusing the image domain post-filtering strategy, robustness of the proposed algorithm is improved. Both simulation and real-measured data experiments demonstrate the effectiveness and superiority of the proposal.

Microstructure Images Restoration of Metallic Materials Based upon KSVD and Smoothing Penalty Sparse Representation Approach

PubMed Central

Liang, Steven Y.

2018-01-01

Microstructure images of metallic materials play a significant role in industrial applications. To address image degradation problem of metallic materials, a novel image restoration technique based on K-means singular value decomposition (KSVD) and smoothing penalty sparse representation (SPSR) algorithm is proposed in this work, the microstructure images of aluminum alloy 7075 (AA7075) material are used as examples. To begin with, to reflect the detail structure characteristics of the damaged image, the KSVD dictionary is introduced to substitute the traditional sparse transform basis (TSTB) for sparse representation. Then, due to the image restoration, modeling belongs to a highly underdetermined equation, and traditional sparse reconstruction methods may cause instability and obvious artifacts in the reconstructed images, especially reconstructed image with many smooth regions and the noise level is strong, thus the SPSR (here, q = 0.5) algorithm is designed to reconstruct the damaged image. The results of simulation and two practical cases demonstrate that the proposed method has superior performance compared with some state-of-the-art methods in terms of restoration performance factors and visual quality. Meanwhile, the grain size parameters and grain boundaries of microstructure image are discussed before and after they are restored by proposed method. PMID:29677163

Assessment of actual evapotranspiration over a semiarid heterogeneous land surface by means of coupled low-resolution remote sensing data with an energy balance model: comparison to extra-large aperture scintillometer measurements

NASA Astrophysics Data System (ADS)

Saadi, Sameh; Boulet, Gilles; Bahir, Malik; Brut, Aurore; Delogu, Émilie; Fanise, Pascal; Mougenot, Bernard; Simonneaux, Vincent; Lili Chabaane, Zohra

2018-04-01

In semiarid areas, agricultural production is restricted by water availability; hence, efficient agricultural water management is a major issue. The design of tools providing regional estimates of evapotranspiration (ET), one of the most relevant water balance fluxes, may help the sustainable management of water resources. Remote sensing provides periodic data about actual vegetation temporal dynamics (through the normalized difference vegetation index, NDVI) and water availability under water stress (through the surface temperature Tsurf), which are crucial factors controlling ET. In this study, spatially distributed estimates of ET (or its energy equivalent, the latent heat flux LE) in the Kairouan plain (central Tunisia) were computed by applying the Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) model fed by low-resolution remote sensing data (Terra and Aqua MODIS). The work's goal was to assess the operational use of the SPARSE model and the accuracy of the modeled (i) sensible heat flux (H) and (ii) daily ET over a heterogeneous semiarid landscape with complex land cover (i.e., trees, winter cereals, summer vegetables). SPARSE was run to compute instantaneous estimates of H and LE fluxes at the satellite overpass times. The good correspondence (R2 = 0.60 and 0.63 and RMSE = 57.89 and 53.85 W m-2 for Terra and Aqua, respectively) between instantaneous H estimates and large aperture scintillometer (XLAS) H measurements along a path length of 4 km over the study area showed that the SPARSE model presents satisfactory accuracy. Results showed that, despite the fairly large scatter, the instantaneous LE can be suitably estimated at large scales (RMSE = 47.20 and 43.20 W m-2 for Terra and Aqua, respectively, and R2 = 0.55 for both satellites). Additionally, water stress was investigated by comparing modeled (SPARSE) and observed (XLAS) water stress values; we found that most points were located within a 0.2 confidence interval, thus the general tendencies are well reproduced. Even though extrapolation of instantaneous latent heat flux values to daily totals was less obvious, daily ET estimates are deemed acceptable.

Visual properties and memorising scenes: Effects of image-space sparseness and uniformity.

PubMed

Lukavský, Jiří; Děchtěrenko, Filip

2017-10-01

Previous studies have demonstrated that humans have a remarkable capacity to memorise a large number of scenes. The research on memorability has shown that memory performance can be predicted by the content of an image. We explored how remembering an image is affected by the image properties within the context of the reference set, including the extent to which it is different from its neighbours (image-space sparseness) and if it belongs to the same category as its neighbours (uniformity). We used a reference set of 2,048 scenes (64 categories), evaluated pairwise scene similarity using deep features from a pretrained convolutional neural network (CNN), and calculated the image-space sparseness and uniformity for each image. We ran three memory experiments, varying the memory workload with experiment length and colour/greyscale presentation. We measured the sensitivity and criterion value changes as a function of image-space sparseness and uniformity. Across all three experiments, we found separate effects of 1) sparseness on memory sensitivity, and 2) uniformity on the recognition criterion. People better remembered (and correctly rejected) images that were more separated from others. People tended to make more false alarms and fewer miss errors in images from categorically uniform portions of the image-space. We propose that both image-space properties affect human decisions when recognising images. Additionally, we found that colour presentation did not yield better memory performance over grayscale images.

Towards the low-dose characterization of beam sensitive nanostructures via implementation of sparse image acquisition in scanning transmission electron microscopy

NASA Astrophysics Data System (ADS)

Hwang, Sunghwan; Han, Chang Wan; Venkatakrishnan, Singanallur V.; Bouman, Charles A.; Ortalan, Volkan

2017-04-01

Scanning transmission electron microscopy (STEM) has been successfully utilized to investigate atomic structure and chemistry of materials with atomic resolution. However, STEM’s focused electron probe with a high current density causes the electron beam damages including radiolysis and knock-on damage when the focused probe is exposed onto the electron-beam sensitive materials. Therefore, it is highly desirable to decrease the electron dose used in STEM for the investigation of biological/organic molecules, soft materials and nanomaterials in general. With the recent emergence of novel sparse signal processing theories, such as compressive sensing and model-based iterative reconstruction, possibilities of operating STEM under a sparse acquisition scheme to reduce the electron dose have been opened up. In this paper, we report our recent approach to implement a sparse acquisition in STEM mode executed by a random sparse-scan and a signal processing algorithm called model-based iterative reconstruction (MBIR). In this method, a small portion, such as 5% of randomly chosen unit sampling areas (i.e. electron probe positions), which corresponds to pixels of a STEM image, within the region of interest (ROI) of the specimen are scanned with an electron probe to obtain a sparse image. Sparse images are then reconstructed using the MBIR inpainting algorithm to produce an image of the specimen at the original resolution that is consistent with an image obtained using conventional scanning methods. Experimental results for down to 5% sampling show consistency with the full STEM image acquired by the conventional scanning method. Although, practical limitations of the conventional STEM instruments, such as internal delays of the STEM control electronics and the continuous electron gun emission, currently hinder to achieve the full potential of the sparse acquisition STEM in realizing the low dose imaging condition required for the investigation of beam-sensitive materials, the results obtained in our experiments demonstrate the sparse acquisition STEM imaging is potentially capable of reducing the electron dose by at least 20 times expanding the frontiers of our characterization capabilities for investigation of biological/organic molecules, polymers, soft materials and nanostructures in general.

An all-optronic synthetic aperture lidar

NASA Astrophysics Data System (ADS)

Turbide, Simon; Marchese, Linda; Terroux, Marc; Babin, François; Bergeron, Alain

2012-09-01

Synthetic Aperture Radar (SAR) is a mature technology that overcomes the diffraction limit of an imaging system's real aperture by taking advantage of the platform motion to coherently sample multiple sections of an aperture much larger than the physical one. Synthetic Aperture Lidar (SAL) is the extension of SAR to much shorter wavelengths (1.5 μm vs 5 cm). This new technology can offer higher resolution images in day or night time as well as in certain adverse conditions. It could be a powerful tool for Earth monitoring (ship detection, frontier surveillance, ocean monitoring) from aircraft, unattended aerial vehicle (UAV) or spatial platforms. A continuous flow of high-resolution images covering large areas would however produce a large amount of data involving a high cost in term of post-processing computational time. This paper presents a laboratory demonstration of a SAL system complete with image reconstruction based on optronic processing. This differs from the more traditional digital approach by its real-time processing capability. The SAL system is discussed and images obtained from a non-metallic diffuse target at ranges up to 3m are shown, these images being processed by a real-time optronic SAR processor origiinally designed to reconstruct SAR images from ENVISAT/ASAR data.

The AdaptiSPECT Imaging Aperture

PubMed Central

Chaix, Cécile; Moore, Jared W.; Van Holen, Roel; Barrett, Harrison H.; Furenlid, Lars R.

2015-01-01

In this paper, we present the imaging aperture of an adaptive SPECT imaging system being developed at the Center for Gamma Ray Imaging (AdaptiSPECT). AdaptiSPECT is designed to automatically change its configuration in response to preliminary data, in order to improve image quality for a particular task. In a traditional pinhole SPECT imaging system, the characteristics (magnification, resolution, field of view) are set by the geometry of the system, and any modification can be accomplished only by manually changing the collimator and the distance of the detector to the center of the field of view. Optimization of the imaging system for a specific task on a specific individual is therefore difficult. In an adaptive SPECT imaging system, on the other hand, the configuration can be conveniently changed under computer control. A key component of an adaptive SPECT system is its aperture. In this paper, we present the design, specifications, and fabrication of the adaptive pinhole aperture that will be used for AdaptiSPECT, as well as the controls that enable autonomous adaptation. PMID:27019577

Optimization of Transmit Parameters in Cardiac Strain Imaging With Full and Partial Aperture Coherent Compounding.

PubMed

Sayseng, Vincent; Grondin, Julien; Konofagou, Elisa E

2018-05-01

Coherent compounding methods using the full or partial transmit aperture have been investigated as a possible means of increasing strain measurement accuracy in cardiac strain imaging; however, the optimal transmit parameters in either compounding approach have yet to be determined. The relationship between strain estimation accuracy and transmit parameters-specifically the subaperture, angular aperture, tilt angle, number of virtual sources, and frame rate-in partial aperture (subaperture compounding) and full aperture (steered compounding) fundamental mode cardiac imaging was thus investigated and compared. Field II simulation of a 3-D cylindrical annulus undergoing deformation and twist was developed to evaluate accuracy of 2-D strain estimation in cross-sectional views. The tradeoff between frame rate and number of virtual sources was then investigated via transthoracic imaging in the parasternal short-axis view of five healthy human subjects, using the strain filter to quantify estimation precision. Finally, the optimized subaperture compounding sequence (25-element subperture, 90° angular aperture, 10 virtual sources, 300-Hz frame rate) was compared to the optimized steered compounding sequence (60° angular aperture, 15° tilt, 10 virtual sources, 300-Hz frame rate) via transthoracic imaging of five healthy subjects. Both approaches were determined to estimate cumulative radial strain with statistically equivalent precision (subaperture compounding E(SNRe %) = 3.56, and steered compounding E(SNRe %) = 4.26).

Multifrequency Aperture-Synthesizing Microwave Radiometer System (MFASMR). Volume 1

NASA Technical Reports Server (NTRS)

Wiley, C. A.; Chang, M. U.

1981-01-01

Background material and a systems analysis of a multifrequency aperture - synthesizing microwave radiometer system is presented. It was found that the system does not exhibit high performance because much of the available thermal power is not used in the construction of the image and because the image that can be formed has a resolution of only ten lines. An analysis of image reconstruction is given. The system is compared with conventional aperture synthesis systems.

View-interpolation of sparsely sampled sinogram using convolutional neural network

NASA Astrophysics Data System (ADS)

Lee, Hoyeon; Lee, Jongha; Cho, Suengryong

2017-02-01

Spare-view sampling and its associated iterative image reconstruction in computed tomography have actively investigated. Sparse-view CT technique is a viable option to low-dose CT, particularly in cone-beam CT (CBCT) applications, with advanced iterative image reconstructions with varying degrees of image artifacts. One of the artifacts that may occur in sparse-view CT is the streak artifact in the reconstructed images. Another approach has been investigated for sparse-view CT imaging by use of the interpolation methods to fill in the missing view data and that reconstructs the image by an analytic reconstruction algorithm. In this study, we developed an interpolation method using convolutional neural network (CNN), which is one of the widely used deep-learning methods, to find missing projection data and compared its performances with the other interpolation techniques.

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

Hellfeld, Daniel; Barton, Paul; Gunter, Donald

Gamma-ray imaging facilitates the efficient detection, characterization, and localization of compact radioactive sources in cluttered environments. Fieldable detector systems employing active planar coded apertures have demonstrated broad energy sensitivity via both coded aperture and Compton imaging modalities. But, planar configurations suffer from a limited field-of-view, especially in the coded aperture mode. In order to improve upon this limitation, we introduce a novel design by rearranging the detectors into an active coded spherical configuration, resulting in a 4pi isotropic field-of-view for both coded aperture and Compton imaging. This work focuses on the low- energy coded aperture modality and the optimization techniquesmore » used to determine the optimal number and configuration of 1 cm 3 CdZnTe coplanar grid detectors on a 14 cm diameter sphere with 192 available detector locations.« less

TRIPPy: Trailed Image Photometry in Python

NASA Astrophysics Data System (ADS)

Fraser, Wesley; Alexandersen, Mike; Schwamb, Megan E.; Marsset, Michaël; Pike, Rosemary E.; Kavelaars, J. J.; Bannister, Michele T.; Benecchi, Susan; Delsanti, Audrey

2016-06-01

Photometry of moving sources typically suffers from a reduced signal-to-noise ratio (S/N) or flux measurements biased to incorrect low values through the use of circular apertures. To address this issue, we present the software package, TRIPPy: TRailed Image Photometry in Python. TRIPPy introduces the pill aperture, which is the natural extension of the circular aperture appropriate for linearly trailed sources. The pill shape is a rectangle with two semicircular end-caps and is described by three parameters, the trail length and angle, and the radius. The TRIPPy software package also includes a new technique to generate accurate model point-spread functions (PSFs) and trailed PSFs (TSFs) from stationary background sources in sidereally tracked images. The TSF is merely the convolution of the model PSF, which consists of a moffat profile, and super-sampled lookup table. From the TSF, accurate pill aperture corrections can be estimated as a function of pill radius with an accuracy of 10 mmag for highly trailed sources. Analogous to the use of small circular apertures and associated aperture corrections, small radius pill apertures can be used to preserve S/Ns of low flux sources, with appropriate aperture correction applied to provide an accurate, unbiased flux measurement at all S/Ns.

Spot restoration for GPR image post-processing

DOEpatents

Paglieroni, David W; Beer, N. Reginald

2014-05-20

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Buried object detection in GPR images

DOEpatents

Paglieroni, David W; Chambers, David H; Bond, Steven W; Beer, W. Reginald

2014-04-29

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Locality constrained joint dynamic sparse representation for local matching based face recognition.

PubMed

Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun

2014-01-01

Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC.

Aperture Photometry Tool

NASA Astrophysics Data System (ADS)

Laher, Russ R.; Gorjian, Varoujan; Rebull, Luisa M.; Masci, Frank J.; Fowler, John W.; Helou, George; Kulkarni, Shrinivas R.; Law, Nicholas M.

2012-07-01

Aperture Photometry Tool (APT) is software for astronomers and students interested in manually exploring the photometric qualities of astronomical images. It is a graphical user interface (GUI) designed to allow the image data associated with aperture photometry calculations for point and extended sources to be visualized and, therefore, more effectively analyzed. The finely tuned layout of the GUI, along with judicious use of color-coding and alerting, is intended to give maximal user utility and convenience. Simply mouse-clicking on a source in the displayed image will instantly draw a circular or elliptical aperture and sky annulus around the source and will compute the source intensity and its uncertainty, along with several commonly used measures of the local sky background and its variability. The results are displayed and can be optionally saved to an aperture-photometry-table file and plotted on graphs in various ways using functions available in the software. APT is geared toward processing sources in a small number of images and is not suitable for bulk processing a large number of images, unlike other aperture photometry packages (e.g., SExtractor). However, APT does have a convenient source-list tool that enables calculations for a large number of detections in a given image. The source-list tool can be run either in automatic mode to generate an aperture photometry table quickly or in manual mode to permit inspection and adjustment of the calculation for each individual detection. APT displays a variety of useful graphs with just the push of a button, including image histogram, x and y aperture slices, source scatter plot, sky scatter plot, sky histogram, radial profile, curve of growth, and aperture-photometry-table scatter plots and histograms. APT has many functions for customizing the calculations, including outlier rejection, pixel “picking” and “zapping,” and a selection of source and sky models. The radial-profile-interpolation source model, which is accessed via the radial-profile-plot panel, allows recovery of source intensity from pixels with missing data and can be especially beneficial in crowded fields.

Edge detection for optical synthetic aperture based on deep neural network

NASA Astrophysics Data System (ADS)

Tan, Wenjie; Hui, Mei; Liu, Ming; Kong, Lingqin; Dong, Liquan; Zhao, Yuejin

2017-09-01

Synthetic aperture optics systems can meet the demands of the next-generation space telescopes being lighter, larger and foldable. However, the boundaries of segmented aperture systems are much more complex than that of the whole aperture. More edge regions mean more imaging edge pixels, which are often mixed and discretized. In order to achieve high-resolution imaging, it is necessary to identify the gaps between the sub-apertures and the edges of the projected fringes. In this work, we introduced the algorithm of Deep Neural Network into the edge detection of optical synthetic aperture imaging. According to the detection needs, we constructed image sets by experiments and simulations. Based on MatConvNet, a toolbox of MATLAB, we ran the neural network, trained it on training image set and tested its performance on validation set. The training was stopped when the test error on validation set stopped declining. As an input image is given, each intra-neighbor area around the pixel is taken into the network, and scanned pixel by pixel with the trained multi-hidden layers. The network outputs make a judgment on whether the center of the input block is on edge of fringes. We experimented with various pre-processing and post-processing techniques to reveal their influence on edge detection performance. Compared with the traditional algorithms or their improvements, our method makes decision on a much larger intra-neighbor, and is more global and comprehensive. Experiments on more than 2,000 images are also given to prove that our method outperforms classical algorithms in optical images-based edge detection.

High-resolution imaging gamma-ray spectroscopy with externally segmented germanium detectors

NASA Technical Reports Server (NTRS)

Callas, J. L.; Mahoney, W. A.; Varnell, L. S.; Wheaton, W. A.

1993-01-01

Externally segmented germanium detectors promise a breakthrough in gamma-ray imaging capabilities while retaining the superb energy resolution of germanium spectrometers. An angular resolution of 0.2 deg becomes practical by combining position-sensitive germanium detectors having a segment thickness of a few millimeters with a one-dimensional coded aperture located about a meter from the detectors. Correspondingly higher angular resolutions are possible with larger separations between the detectors and the coded aperture. Two-dimensional images can be obtained by rotating the instrument. Although the basic concept is similar to optical or X-ray coded-aperture imaging techniques, several complicating effects arise because of the penetrating nature of gamma rays. The complications include partial transmission through the coded aperture elements, Compton scattering in the germanium detectors, and high background count rates. Extensive electron-photon Monte Carlo modeling of a realistic detector/coded-aperture/collimator system has been performed. Results show that these complicating effects can be characterized and accounted for with no significant loss in instrument sensitivity.

Terahertz-wave near-field imaging with subwavelength resolution using surface-wave-assisted bow-tie aperture

NASA Astrophysics Data System (ADS)

Ishihara, Kunihiko; Ohashi, Keishi; Ikari, Tomofumi; Minamide, Hiroaki; Yokoyama, Hiroyuki; Shikata, Jun-ichi; Ito, Hiromasa

2006-11-01

We demonstrate the terahertz-wave near-field imaging with subwavelength resolution using a bow-tie shaped aperture surrounded by concentric periodic structures in a metal film. A subwavelength aperture with concentric periodic grooves, which are known as a bull's eye structure, shows extremely large enhanced transmission beyond the diffraction limit caused by the resonant excitation of surface waves. Additionally, a bow-tie aperture exhibits extraordinary field enhancement at the sharp tips of the metal, which enhances the transmission and the subwavelength spatial resolution. We introduced a bow-tie aperture to the bull's eye structure and achieved high spatial resolution (˜λ/17) in the near-field region. The terahertz-wave near-field image of the subwavelength metal pattern (pattern width=20μm) was obtained for the wavelength of 207μm.

Hartmann test for the James Webb Space Telescope

NASA Astrophysics Data System (ADS)

Knight, J. Scott; Feinberg, Lee; Howard, Joseph; Acton, D. Scott; Whitman, Tony L.; Smith, Koby

2016-07-01

The James Webb Space Telescope's (JWST) end-to-end optical system will be tested in a cryogenic vacuum environment before launch at NASA Johnson Space Center's (JSC) Apollo-era, historic Chamber A thermal vacuum facility. During recent pre-test runs with a prototype "Pathfinder" telescope, the vibration in this environment was found to be challenging for the baseline test approach, which uses phase retrieval of images created by three sub-apertures of the telescope. To address the vibration, an alternate strategy implemented using classic Hartmann test principles combined with precise mirror mechanisms to provide a testing approach that is insensitive to the dynamics environment of the chamber. The measurements and sensitivities of the Hartmann approach are similar to those using phase retrieval over the original sparse aperture test. The Hartmann test concepts have been implemented on the JWST Test Bed Telescope, which provided the rationale and empirical evidence indicating that this Hartmann style approach would be valuable in supplementing the baseline test approach. This paper presents a Hartmann approach implemented during the recent Pathfinder test along with the test approach that is currently being considered for the full optical system test of JWST. Comparisons are made between the baseline phase retrieval approach and the Hartmann approach in addition to demonstrating how the two test methodologies support each other to reduce risk during the JWST full optical system test.

Image fusion based on Bandelet and sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Jiuxing; Zhang, Wei; Li, Xuzhi

2018-04-01

Bandelet transform could acquire geometric regular direction and geometric flow, sparse representation could represent signals with as little as possible atoms on over-complete dictionary, both of which could be used to image fusion. Therefore, a new fusion method is proposed based on Bandelet and Sparse Representation, to fuse Bandelet coefficients of multi-source images and obtain high quality fusion effects. The test are performed on remote sensing images and simulated multi-focus images, experimental results show that the performance of new method is better than tested methods according to objective evaluation indexes and subjective visual effects.

Subsurface Grain Morphology Reconstruction by Differential Aperture X-ray Microscopy

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

Eisenlohr, Philip; Shanthraj, Pratheek; Vande Kieft, Brendan R.

A multistep, non-destructive grain morphology reconstruction methodology that is applicable to near-surface volumes is developed and tested on synthetic grain structures. This approach probes the subsurface crystal orientation using differential aperture X-ray microscopy (DAXM) on a sparse grid across the microstructure volume of interest. Resulting orientation data is clustered according to proximity in physical and orientation space and used as seed points for an initial Voronoi tessellation to (crudely) approximate the grain morphology. Curvature-driven grain boundary relaxation, simulated by means of the Voronoi Implicit Interface Method (VIIM), progressively improves the reconstruction accuracy. The similarity between bulk and readily accessible surfacemore » reconstruction error provides an objective termination criterion for boundary relaxation.« less

Class of near-perfect coded apertures

NASA Technical Reports Server (NTRS)

Cannon, T. M.; Fenimore, E. E.

1977-01-01

Coded aperture imaging of gamma ray sources has long promised an improvement in the sensitivity of various detector systems. The promise has remained largely unfulfilled, however, for either one of two reasons. First, the encoding/decoding method produces artifacts, which even in the absence of quantum noise, restrict the quality of the reconstructed image. This is true of most correlation-type methods. Second, if the decoding procedure is of the deconvolution variety, small terms in the transfer function of the aperture can lead to excessive noise in the reconstructed image. It is proposed to circumvent both of these problems by use of a uniformly redundant array (URA) as the coded aperture in conjunction with a special correlation decoding method.

Terahertz Near-Field Imaging Using Enhanced Transmission through a Single Subwavelength Aperture

NASA Astrophysics Data System (ADS)

Ishihara, Kunihiko; Ikari, Tomofumi; Minamide, Hiroaki; Shikata, Jun-ichi; Ohashi, Keishi; Yokoyama, Hiroyuki; Ito, Hiromasa

2005-07-01

We demonstrate terahertz (THz) near-field imaging using resonantly enhanced transmission of THz-wave radiation (λ˜ 200 μm) through a bull’s eye structure (a single subwavelength aperture surrounded by concentric periodic grooves in a metal plate). The bull’s eye structure shows extremely large enhanced transmission, which has the advantage for a single subwavelength aperture. The spatial resolution for the bull’s eye structure (with an aperture diameter d=100 μm) is evaluated in the near-field region, and a resolution of 50 μm (corresponding to λ/4) is achieved. We obtain the THz near-field images of the subwavelength metal pattern with a spatial resolution below the diffraction limit.

Early development in synthetic aperture lidar sensing and processing for on-demand high resolution imaging

NASA Astrophysics Data System (ADS)

Bergeron, Alain; Turbide, Simon; Terroux, Marc; Marchese, Linda; Harnisch, Bernd

2017-11-01

The quest for real-time high resolution is of prime importance for surveillance applications specially in disaster management and rescue mission. Synthetic aperture radar provides meter-range resolution images in all weather conditions. Often installed on satellites the revisit time can be too long to support real-time operations on the ground. Synthetic aperture lidar can be lightweight and offers centimeter-range resolution. Onboard airplane or unmanned air vehicle this technology would allow for timelier reconnaissance. INO has developed a synthetic aperture radar table prototype and further used a real-time optronic processor to fulfill image generation on-demand. The early positive results using both technologies are presented in this paper.

Increasing circular synthetic aperture sonar resolution via adapted wave atoms deconvolution.

PubMed

Pailhas, Yan; Petillot, Yvan; Mulgrew, Bernard

2017-04-01

Circular Synthetic Aperture Sonar (CSAS) processing computes coherently Synthetic Aperture Sonar (SAS) data acquired along a circular trajectory. This approach has a number of advantages, in particular it maximises the aperture length of a SAS system, producing very high resolution sonar images. CSAS image reconstruction using back-projection algorithms, however, introduces a dissymmetry in the impulse response, as the imaged point moves away from the centre of the acquisition circle. This paper proposes a sampling scheme for the CSAS image reconstruction which allows every point, within the full field of view of the system, to be considered as the centre of a virtual CSAS acquisition scheme. As a direct consequence of using the proposed resampling scheme, the point spread function (PSF) is uniform for the full CSAS image. Closed form solutions for the CSAS PSF are derived analytically, both in the image and the Fourier domain. The thorough knowledge of the PSF leads naturally to the proposed adapted atom waves basis for CSAS image decomposition. The atom wave deconvolution is successfully applied to simulated data, increasing the image resolution by reducing the PSF energy leakage.

Spatially assisted down-track median filter for GPR image post-processing

DOEpatents

Paglieroni, David W; Beer, N Reginald

2014-10-07

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Spatially adaptive migration tomography for multistatic GPR imaging

DOEpatents

Paglieroni, David W; Beer, N. Reginald

2013-08-13

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Zero source insertion technique to account for undersampling in GPR imaging

DOEpatents

Chambers, David H; Mast, Jeffrey E; Paglieroni, David W

2014-02-25

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Real-time system for imaging and object detection with a multistatic GPR array

DOEpatents

Paglieroni, David W; Beer, N Reginald; Bond, Steven W; Top, Philip L; Chambers, David H; Mast, Jeffrey E; Donetti, John G; Mason, Blake C; Jones, Steven M

2014-10-07

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

Fabrication of the pinhole aperture for AdaptiSPECT

PubMed Central

Kovalsky, Stephen; Kupinski, Matthew A.; Barrett, Harrison H.; Furenlid, Lars R.

2015-01-01

AdaptiSPECT is a pre-clinical pinhole SPECT imaging system under final construction at the Center for Gamma-Ray Imaging. The system is designed to be able to autonomously change its imaging configuration. The system comprises 16 detectors mounted on translational stages to move radially away and towards the center of the field-of-view. The system also possesses an adaptive pinhole aperture with multiple collimator diameters and pinhole sizes, as well as the possibility to switch between multiplexed and non-multiplexed imaging configurations. In this paper, we describe the fabrication of the AdaptiSPECT pinhole aperture and its controllers. PMID:26146443

Adaptive Microwave Staring Correlated Imaging for Targets Appearing in Discrete Clusters.

PubMed

Tian, Chao; Jiang, Zheng; Chen, Weidong; Wang, Dongjin

2017-10-21

Microwave staring correlated imaging (MSCI) can achieve ultra-high resolution in real aperture staring radar imaging using the correlated imaging process (CIP) under all-weather and all-day circumstances. The CIP must combine the received echo signal with the temporal-spatial stochastic radiation field. However, a precondition of the CIP is that the continuous imaging region must be discretized to a fine grid, and the measurement matrix should be accurately computed, which makes the imaging process highly complex when the MSCI system observes a wide area. This paper proposes an adaptive imaging approach for the targets in discrete clusters to reduce the complexity of the CIP. The approach is divided into two main stages. First, as discrete clustered targets are distributed in different range strips in the imaging region, the transmitters of the MSCI emit narrow-pulse waveforms to separate the echoes of the targets in different strips in the time domain; using spectral entropy, a modified method robust against noise is put forward to detect the echoes of the discrete clustered targets, based on which the strips with targets can be adaptively located. Second, in a strip with targets, the matched filter reconstruction algorithm is used to locate the regions with targets, and only the regions of interest are discretized to a fine grid; sparse recovery is used, and the band exclusion is used to maintain the non-correlation of the dictionary. Simulation results are presented to demonstrate that the proposed approach can accurately and adaptively locate the regions with targets and obtain high-quality reconstructed images.

A conceptual design for an exoplanet imager

NASA Astrophysics Data System (ADS)

Hyland, David C.; Winkeller, Jon; Mosher, Robert; Momin, Anif; Iglesias, Gerardo; Donnellan, Quentin; Stanley, Jerry; Myers, Storm; Whittington, William G.; Asazuma, Taro; Slagle, Kami; Newton, Lindsay; Bourgeois, Scott; Tejeda, Donny; Young, Brian; Shaver, Nick; Cooper, Jacob; Underwood, Dennis; Perkins, James; Morea, Nathan; Goodnight, Ryan; Colunga, Aaron; Peltier, Scott; Singleton, Zane; Brashear, John; McPherson, Ronald; Guillory, Winston; Patel, Sunil; Stovall, Rachel; Meyer, Ryall; Eberle, Patrick; Morrison, Cole; Mong, Chun Yu

2007-09-01

This paper reports the results of a design study for an exoplanet imaging system. The design team consisted of the students in the "Electromagnetic Sensing for Space-Bourne Imaging" class taught by the principal author in the Spring, 2005 semester. The design challenge was to devise a space system capable of forming 10X10 pixel images of terrestrial-class planets out to 10 parsecs, observing in the 9.0 to 17.0 microns range. It was presumed that this system would operate after the Terrestrial Planet Finder had been deployed and had identified a number of planetary systems for more detailed imaging. The design team evaluated a large number of tradeoffs, starting with the use of a single monolithic telescope, versus a truss-mounted sparse aperture, versus a formation of free-flying telescopes. Having selected the free-flyer option, the team studied a variety of sensing technologies, including amplitude interferometry, intensity correlation imaging (ICI, based on the Brown-Twiss effect and phase retrieval), heterodyne interferometry and direct electric field reconstruction. Intensity correlation imaging was found to have several advantages. It does not require combiner spacecraft, nor nanometer-level control of the relative positions, nor diffraction-limited optics. Orbit design, telescope design, spacecraft structural design, thermal management and communications architecture trades were also addressed. A six spacecraft design involving non-repeating baselines was selected. By varying the overall scale of the baselines it was found possible to unambiguously characterize an entire multi-planet system, to image the parent star and, for the largest base scales, to determine 10X10 pixel images of individual planets.

3D ultrasound computer tomography: Hardware setup, reconstruction methods and first clinical results

NASA Astrophysics Data System (ADS)

Gemmeke, Hartmut; Hopp, Torsten; Zapf, Michael; Kaiser, Clemens; Ruiter, Nicole V.

2017-11-01

A promising candidate for improved imaging of breast cancer is ultrasound computer tomography (USCT). Current experimental USCT systems are still focused in elevation dimension resulting in a large slice thickness, limited depth of field, loss of out-of-plane reflections, and a large number of movement steps to acquire a stack of images. 3D USCT emitting and receiving spherical wave fronts overcomes these limitations. We built an optimized 3D USCT, realizing for the first time the full benefits of a 3D system. The point spread function could be shown to be nearly isotropic in 3D, to have very low spatial variability and fit the predicted values. The contrast of the phantom images is very satisfactory in spite of imaging with a sparse aperture. The resolution and imaged details of the reflectivity reconstruction are comparable to a 3 T MRI volume. Important for the obtained resolution are the simultaneously obtained results of the transmission tomography. The KIT 3D USCT was then tested in a pilot study on ten patients. The primary goals of the pilot study were to test the USCT device, the data acquisition protocols, the image reconstruction methods and the image fusion techniques in a clinical environment. The study was conducted successfully; the data acquisition could be carried out for all patients with an average imaging time of six minutes per breast. The reconstructions provide promising images. Overlaid volumes of the modalities show qualitative and quantitative information at a glance. This paper gives a summary of the involved techniques, methods, and first results.

Example-Based Image Colorization Using Locality Consistent Sparse Representation.

PubMed

Bo Li; Fuchen Zhao; Zhuo Su; Xiangguo Liang; Yu-Kun Lai; Rosin, Paul L

2017-11-01

Image colorization aims to produce a natural looking color image from a given gray-scale image, which remains a challenging problem. In this paper, we propose a novel example-based image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target gray-scale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features, and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from the reference image, we further introduce a locality promoting regularization term into the energy formulation, which substantially improves the matching consistency and subsequent colorization results. Target superpixels are colorized based on the chrominance information from the dominant reference superpixels. Finally, to further improve coherence while preserving sharpness, we develop a new edge-preserving filter for chrominance channels with the guidance from the target gray-scale image. To the best of our knowledge, this is the first work on sparse pursuit image colorization from single reference images. Experimental results demonstrate that our colorization method outperforms the state-of-the-art methods, both visually and quantitatively using a user study.

MO-FG-204-08: Optimization-Based Image Reconstruction From Unevenly Distributed Sparse Projection Views

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

Xie, Huiqiao; Yang, Yi; Tang, Xiangyang

2015-06-15

Purpose: Optimization-based reconstruction has been proposed and investigated for reconstructing CT images from sparse views, as such the radiation dose can be substantially reduced while maintaining acceptable image quality. The investigation has so far focused on reconstruction from evenly distributed sparse views. Recognizing the clinical situations wherein only unevenly sparse views are available, e.g., image guided radiation therapy, CT perfusion and multi-cycle cardiovascular imaging, we investigate the performance of optimization-based image reconstruction from unevenly sparse projection views in this work. Methods: The investigation is carried out using the FORBILD and an anthropomorphic head phantoms. In the study, 82 views, whichmore » are evenly sorted out from a full (360°) axial CT scan consisting of 984 views, form sub-scan I. Another 82 views are sorted out in a similar manner to form sub-scan II. As such, a CT scan with sparse (164) views at 1:6 ratio are formed. By shifting the two sub-scans relatively in view angulation, a CT scan with unevenly distributed sparse (164) views at 1:6 ratio are formed. An optimization-based method is implemented to reconstruct images from the unevenly distributed views. By taking the FBP reconstruction from the full scan (984 views) as the reference, the root mean square (RMS) between the reference and the optimization-based reconstruction is used to evaluate the performance quantitatively. Results: In visual inspection, the optimization-based method outperforms the FBP substantially in the reconstruction from unevenly distributed, which are quantitatively verified by the RMS gauged globally and in ROIs in both the FORBILD and anthropomorphic head phantoms. The RMS increases with increasing severity in the uneven angular distribution, especially in the case of anthropomorphic head phantom. Conclusion: The optimization-based image reconstruction can save radiation dose up to 12-fold while providing acceptable image quality for advanced clinical applications wherein only unevenly distributed sparse views are available. Research Grants: W81XWH-12-1-0138 (DoD), Sinovision Technologies.« less

Finger vein verification system based on sparse representation.

PubMed

Xin, Yang; Liu, Zhi; Zhang, Haixia; Zhang, Hong

2012-09-01

Finger vein verification is a promising biometric pattern for personal identification in terms of security and convenience. The recognition performance of this technology heavily relies on the quality of finger vein images and on the recognition algorithm. To achieve efficient recognition performance, a special finger vein imaging device is developed, and a finger vein recognition method based on sparse representation is proposed. The motivation for the proposed method is that finger vein images exhibit a sparse property. In the proposed system, the regions of interest (ROIs) in the finger vein images are segmented and enhanced. Sparse representation and sparsity preserving projection on ROIs are performed to obtain the features. Finally, the features are measured for recognition. An equal error rate of 0.017% was achieved based on the finger vein image database, which contains images that were captured by using the near-IR imaging device that was developed in this study. The experimental results demonstrate that the proposed method is faster and more robust than previous methods.

Multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement

NASA Astrophysics Data System (ADS)

Yan, Dan; Bai, Lianfa; Zhang, Yi; Han, Jing

2018-02-01

For the problems of missing details and performance of the colorization based on sparse representation, we propose a conceptual model framework for colorizing gray-scale images, and then a multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement (CEMDC) is proposed based on this framework. The algorithm can achieve a natural colorized effect for a gray-scale image, and it is consistent with the human vision. First, the algorithm establishes a multi-sparse dictionary classification colorization model. Then, to improve the accuracy rate of the classification, the corresponding local constraint algorithm is proposed. Finally, we propose a detail enhancement based on Laplacian Pyramid, which is effective in solving the problem of missing details and improving the speed of image colorization. In addition, the algorithm not only realizes the colorization of the visual gray-scale image, but also can be applied to the other areas, such as color transfer between color images, colorizing gray fusion images, and infrared images.

Multiple Sparse Representations Classification

PubMed Central

Plenge, Esben; Klein, Stefan S.; Niessen, Wiro J.; Meijering, Erik

2015-01-01

Sparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In this empirical study we propose to further leverage the redundancy of the learned dictionaries to achieve a more accurate classifier. In conventional SRC, each image pixel is associated with a small patch surrounding it. Using these patches, a dictionary is trained for each class in a supervised fashion. Commonly, redundant/overcomplete dictionaries are trained and image patches are sparsely represented by a linear combination of only a few of the dictionary elements. Given a set of trained dictionaries, a new patch is sparse coded using each of them, and subsequently assigned to the class whose dictionary yields the minimum residual energy. We propose a generalization of this scheme. The method, which we call multiple sparse representations classification (mSRC), is based on the observation that an overcomplete, class specific dictionary is capable of generating multiple accurate and independent estimates of a patch belonging to the class. So instead of finding a single sparse representation of a patch for each dictionary, we find multiple, and the corresponding residual energies provides an enhanced statistic which is used to improve classification. We demonstrate the efficacy of mSRC for three example applications: pixelwise classification of texture images, lumen segmentation in carotid artery magnetic resonance imaging (MRI), and bifurcation point detection in carotid artery MRI. We compare our method with conventional SRC, K-nearest neighbor, and support vector machine classifiers. The results show that mSRC outperforms SRC and the other reference methods. In addition, we present an extensive evaluation of the effect of the main mSRC parameters: patch size, dictionary size, and sparsity level. PMID:26177106

Extended sources near-field processing of experimental aperture synthesis data and application of the Gerchberg method for enhancing radiometric three-dimensional millimetre-wave images in security screening portals

NASA Astrophysics Data System (ADS)

Salmon, Neil A.

2017-10-01

Aperture synthesis for passive millimetre wave imaging provides a means to screen people for concealed threats in the extreme near-field configuration of a portal, a regime where the imager to subject distance is of the order of both the required depth-of-field and the field-of-view. Due to optical aberrations, focal plane array imagers cannot deliver the large depth-of-fields and field-of-views required in this regime. Active sensors on the other hand can deliver these but face challenges of illumination, speckle and multi-path issues when imaging canyon regions of the body. Fortunately an aperture synthesis passive millimetre wave imaging system can deliver large depth-of-fields and field-of-views, whilst having no speckle effects, as the radiometric emission from the human body is spatially incoherent. Furthermore, as in portal security screening scenarios the aperture synthesis imaging technique delivers a half-wavelength spatial resolution, it can effectively screen the whole of the human body. Some recent measurements are presented that demonstrate the three-dimensional imaging capability of extended sources using a 22 GHz aperture synthesis system. A comparison is made between imagery generated via the analytic Fourier transform and a gridding fast Fourier transform method. The analytic Fourier transform enables aliasing in the imagery to be more clearly identified. Some initial results are also presented of how the Gerchberg technique, an image enhancement algorithm used in radio astronomy, is adapted for three-dimensional imaging in security screening. This technique is shown to be able to improve the quality of imagery, without adding extra receivers to the imager. The requirements of a walk through security screening system for use at entrances to airport departure lounges are discussed, concluding that these can be met by an aperture synthesis imager.

Single-event transient imaging with an ultra-high-speed temporally compressive multi-aperture CMOS image sensor.

PubMed

Mochizuki, Futa; Kagawa, Keiichiro; Okihara, Shin-ichiro; Seo, Min-Woong; Zhang, Bo; Takasawa, Taishi; Yasutomi, Keita; Kawahito, Shoji

2016-02-22

In the work described in this paper, an image reproduction scheme with an ultra-high-speed temporally compressive multi-aperture CMOS image sensor was demonstrated. The sensor captures an object by compressing a sequence of images with focal-plane temporally random-coded shutters, followed by reconstruction of time-resolved images. Because signals are modulated pixel-by-pixel during capturing, the maximum frame rate is defined only by the charge transfer speed and can thus be higher than those of conventional ultra-high-speed cameras. The frame rate and optical efficiency of the multi-aperture scheme are discussed. To demonstrate the proposed imaging method, a 5×3 multi-aperture image sensor was fabricated. The average rising and falling times of the shutters were 1.53 ns and 1.69 ns, respectively. The maximum skew among the shutters was 3 ns. The sensor observed plasma emission by compressing it to 15 frames, and a series of 32 images at 200 Mfps was reconstructed. In the experiment, by correcting disparities and considering temporal pixel responses, artifacts in the reconstructed images were reduced. An improvement in PSNR from 25.8 dB to 30.8 dB was confirmed in simulations.

Sparse coded image super-resolution using K-SVD trained dictionary based on regularized orthogonal matching pursuit.

PubMed

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2015-01-01

Image super-resolution (SR) plays a vital role in medical imaging that allows a more efficient and effective diagnosis process. Usually, diagnosing is difficult and inaccurate from low-resolution (LR) and noisy images. Resolution enhancement through conventional interpolation methods strongly affects the precision of consequent processing steps, such as segmentation and registration. Therefore, we propose an efficient sparse coded image SR reconstruction technique using a trained dictionary. We apply a simple and efficient regularized version of orthogonal matching pursuit (ROMP) to seek the coefficients of sparse representation. ROMP has the transparency and greediness of OMP and the robustness of the L1-minization that enhance the dictionary learning process to capture feature descriptors such as oriented edges and contours from complex images like brain MRIs. The sparse coding part of the K-SVD dictionary training procedure is modified by substituting OMP with ROMP. The dictionary update stage allows simultaneously updating an arbitrary number of atoms and vectors of sparse coefficients. In SR reconstruction, ROMP is used to determine the vector of sparse coefficients for the underlying patch. The recovered representations are then applied to the trained dictionary, and finally, an optimization leads to high-resolution output of high-quality. Experimental results demonstrate that the super-resolution reconstruction quality of the proposed scheme is comparatively better than other state-of-the-art schemes.

Hierarchical Bayesian sparse image reconstruction with application to MRFM.

PubMed

Dobigeon, Nicolas; Hero, Alfred O; Tourneret, Jean-Yves

2009-09-01

This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gaussian noise. Our hierarchical Bayes model is well suited to such naturally sparse image applications as it seamlessly accounts for properties such as sparsity and positivity of the image via appropriate Bayes priors. We propose a prior that is based on a weighted mixture of a positive exponential distribution and a mass at zero. The prior has hyperparameters that are tuned automatically by marginalization over the hierarchical Bayesian model. To overcome the complexity of the posterior distribution, a Gibbs sampling strategy is proposed. The Gibbs samples can be used to estimate the image to be recovered, e.g., by maximizing the estimated posterior distribution. In our fully Bayesian approach, the posteriors of all the parameters are available. Thus, our algorithm provides more information than other previously proposed sparse reconstruction methods that only give a point estimate. The performance of the proposed hierarchical Bayesian sparse reconstruction method is illustrated on synthetic data and real data collected from a tobacco virus sample using a prototype MRFM instrument.

Face recognition via sparse representation of SIFT feature on hexagonal-sampling image

NASA Astrophysics Data System (ADS)

Zhang, Daming; Zhang, Xueyong; Li, Lu; Liu, Huayong

2018-04-01

This paper investigates a face recognition approach based on Scale Invariant Feature Transform (SIFT) feature and sparse representation. The approach takes advantage of SIFT which is local feature other than holistic feature in classical Sparse Representation based Classification (SRC) algorithm and possesses strong robustness to expression, pose and illumination variations. Since hexagonal image has more inherit merits than square image to make recognition process more efficient, we extract SIFT keypoint in hexagonal-sampling image. Instead of matching SIFT feature, firstly the sparse representation of each SIFT keypoint is given according the constructed dictionary; secondly these sparse vectors are quantized according dictionary; finally each face image is represented by a histogram and these so-called Bag-of-Words vectors are classified by SVM. Due to use of local feature, the proposed method achieves better result even when the number of training sample is small. In the experiments, the proposed method gave higher face recognition rather than other methods in ORL and Yale B face databases; also, the effectiveness of the hexagonal-sampling in the proposed method is verified.

Radar signal pre-processing to suppress surface bounce and multipath

DOEpatents

Paglieroni, David W; Mast, Jeffrey E; Beer, N. Reginald

2013-12-31

A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes that return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

An efficient classification method based on principal component and sparse representation.

PubMed

Zhai, Lin; Fu, Shujun; Zhang, Caiming; Liu, Yunxian; Wang, Lu; Liu, Guohua; Yang, Mingqiang

2016-01-01

As an important application in optical imaging, palmprint recognition is interfered by many unfavorable factors. An effective fusion of blockwise bi-directional two-dimensional principal component analysis and grouping sparse classification is presented. The dimension reduction and normalizing are implemented by the blockwise bi-directional two-dimensional principal component analysis for palmprint images to extract feature matrixes, which are assembled into an overcomplete dictionary in sparse classification. A subspace orthogonal matching pursuit algorithm is designed to solve the grouping sparse representation. Finally, the classification result is gained by comparing the residual between testing and reconstructed images. Experiments are carried out on a palmprint database, and the results show that this method has better robustness against position and illumination changes of palmprint images, and can get higher rate of palmprint recognition.

Implementing an Accurate and Rapid Sparse Sampling Approach for Low-Dose Atomic Resolution STEM Imaging

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

Kovarik, Libor; Stevens, Andrew J.; Liyu, Andrey V.

Aberration correction for scanning transmission electron microscopes (STEM) has dramatically increased spatial image resolution for beam-stable materials, but it is the sample stability rather than the microscope that often limits the practical resolution of STEM images. To extract physical information from images of beam sensitive materials it is becoming clear that there is a critical dose/dose-rate below which the images can be interpreted as representative of the pristine material, while above it the observation is dominated by beam effects. Here we describe an experimental approach for sparse sampling in the STEM and in-painting image reconstruction in order to reduce themore » electron dose/dose-rate to the sample during imaging. By characterizing the induction limited rise-time and hysteresis in scan coils, we show that sparse line-hopping approach to scan randomization can be implemented that optimizes both the speed of the scan and the amount of the sample that needs to be illuminated by the beam. The dose and acquisition time for the sparse sampling is shown to be effectively decreased by factor of 5x relative to conventional acquisition, permitting imaging of beam sensitive materials to be obtained without changing the microscope operating parameters. As a result, the use of sparse line-hopping scan to acquire STEM images is demonstrated with atomic resolution aberration corrected Z-contrast images of CaCO 3, a material that is traditionally difficult to image by TEM/STEM because of dose issues.« less

Implementing an Accurate and Rapid Sparse Sampling Approach for Low-Dose Atomic Resolution STEM Imaging

DOE PAGES

Kovarik, Libor; Stevens, Andrew J.; Liyu, Andrey V.; ...

2016-10-17

Aberration correction for scanning transmission electron microscopes (STEM) has dramatically increased spatial image resolution for beam-stable materials, but it is the sample stability rather than the microscope that often limits the practical resolution of STEM images. To extract physical information from images of beam sensitive materials it is becoming clear that there is a critical dose/dose-rate below which the images can be interpreted as representative of the pristine material, while above it the observation is dominated by beam effects. Here we describe an experimental approach for sparse sampling in the STEM and in-painting image reconstruction in order to reduce themore » electron dose/dose-rate to the sample during imaging. By characterizing the induction limited rise-time and hysteresis in scan coils, we show that sparse line-hopping approach to scan randomization can be implemented that optimizes both the speed of the scan and the amount of the sample that needs to be illuminated by the beam. The dose and acquisition time for the sparse sampling is shown to be effectively decreased by factor of 5x relative to conventional acquisition, permitting imaging of beam sensitive materials to be obtained without changing the microscope operating parameters. The use of sparse line-hopping scan to acquire STEM images is demonstrated with atomic resolution aberration corrected Z-contrast images of CaCO3, a material that is traditionally difficult to image by TEM/STEM because of dose issues.« less

Coded aperture detector: an image sensor with sub 20-nm pixel resolution.

PubMed

Miyakawa, Ryan; Mayer, Rafael; Wojdyla, Antoine; Vannier, Nicolas; Lesser, Ian; Aron-Dine, Shifrah; Naulleau, Patrick

2014-08-11

We describe the coded aperture detector, a novel image sensor based on uniformly redundant arrays (URAs) with customizable pixel size, resolution, and operating photon energy regime. In this sensor, a coded aperture is scanned laterally at the image plane of an optical system, and the transmitted intensity is measured by a photodiode. The image intensity is then digitally reconstructed using a simple convolution. We present results from a proof-of-principle optical prototype, demonstrating high-fidelity image sensing comparable to a CCD. A 20-nm half-pitch URA fabricated by the Center for X-ray Optics (CXRO) nano-fabrication laboratory is presented that is suitable for high-resolution image sensing at EUV and soft X-ray wavelengths.

Formation Control of the MAXIM L2 Libration Orbit Mission

NASA Technical Reports Server (NTRS)

Folta, David; Hartman, Kate; Howell, Kathleen; Marchand, Belinda

2004-01-01

The Micro-Arcsecond X-ray Imaging Mission (MAXIM), a proposed concept for the Structure and Evolution of the Universe (SEU) Black Hole Imager mission, is designed to make a ten million-fold improvement in X-ray image clarity of celestial objects by providing better than 0.1 micro-arcsecond imaging. Currently the mission architecture comprises 25 spacecraft, 24 as optics modules and one as the detector, which will form sparse sub-apertures of a grazing incidence X-ray interferometer covering the 0.3-10 keV bandpass. This formation must allow for long duration continuous science observations and also for reconfiguration that permits re-pointing of the formation. To achieve these mission goals, the formation is required to cooperatively point at desired targets. Once pointed, the individual elements of the MAXIM formation must remain stable, maintaining their relative positions and attitudes below a critical threshold. These pointing and formation stability requirements impact the control and design of the formation. In this paper, we provide analysis of control efforts that are dependent upon the stability and the configuration and dimensions of the MAXIM formation. We emphasize the utilization of natural motions in the Lagrangian regions to minimize the control efforts and we address continuous control via input feedback linearization (IFL). Results provide control cost, configuration options, and capabilities as guidelines for the development of this complex mission.

Sparse magnetic resonance imaging reconstruction using the bregman iteration

NASA Astrophysics Data System (ADS)

Lee, Dong-Hoon; Hong, Cheol-Pyo; Lee, Man-Woo

2013-01-01

Magnetic resonance imaging (MRI) reconstruction needs many samples that are sequentially sampled by using phase encoding gradients in a MRI system. It is directly connected to the scan time for the MRI system and takes a long time. Therefore, many researchers have studied ways to reduce the scan time, especially, compressed sensing (CS), which is used for sparse images and reconstruction for fewer sampling datasets when the k-space is not fully sampled. Recently, an iterative technique based on the bregman method was developed for denoising. The bregman iteration method improves on total variation (TV) regularization by gradually recovering the fine-scale structures that are usually lost in TV regularization. In this study, we studied sparse sampling image reconstruction using the bregman iteration for a low-field MRI system to improve its temporal resolution and to validate its usefulness. The image was obtained with a 0.32 T MRI scanner (Magfinder II, SCIMEDIX, Korea) with a phantom and an in-vivo human brain in a head coil. We applied random k-space sampling, and we determined the sampling ratios by using half the fully sampled k-space. The bregman iteration was used to generate the final images based on the reduced data. We also calculated the root-mean-square-error (RMSE) values from error images that were obtained using various numbers of bregman iterations. Our reconstructed images using the bregman iteration for sparse sampling images showed good results compared with the original images. Moreover, the RMSE values showed that the sparse reconstructed phantom and the human images converged to the original images. We confirmed the feasibility of sparse sampling image reconstruction methods using the bregman iteration with a low-field MRI system and obtained good results. Although our results used half the sampling ratio, this method will be helpful in increasing the temporal resolution at low-field MRI systems.

CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition

PubMed Central

Gou, Shuiping; Wang, Yueyue; Wang, Zhilong; Peng, Yong; Zhang, Xiaopeng; Jiao, Licheng; Wu, Jianshe

2013-01-01

Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA), Linearized Alternating Direction Method with Adaptive Penalty (LADMAP) and Go Decomposition (GoDec). Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images. PMID:24023764

Synthetic aperture imaging in ultrasound calibration

NASA Astrophysics Data System (ADS)

Ameri, Golafsoun; Baxter, John S. H.; McLeod, A. Jonathan; Jayaranthe, Uditha L.; Chen, Elvis C. S.; Peters, Terry M.

2014-03-01

Ultrasound calibration allows for ultrasound images to be incorporated into a variety of interventional applica­ tions. Traditional Z- bar calibration procedures rely on wired phantoms with an a priori known geometry. The line fiducials produce small, localized echoes which are then segmented from an array of ultrasound images from different tracked probe positions. In conventional B-mode ultrasound, the wires at greater depths appear blurred and are difficult to segment accurately, limiting the accuracy of ultrasound calibration. This paper presents a novel ultrasound calibration procedure that takes advantage of synthetic aperture imaging to reconstruct high resolution ultrasound images at arbitrary depths. In these images, line fiducials are much more readily and accu­ rately segmented, leading to decreased calibration error. The proposed calibration technique is compared to one based on B-mode ultrasound. The fiducial localization error was improved from 0.21mm in conventional B-mode images to 0.15mm in synthetic aperture images corresponding to an improvement of 29%. This resulted in an overall reduction of calibration error from a target registration error of 2.00mm to 1.78mm, an improvement of 11%. Synthetic aperture images display greatly improved segmentation capabilities due to their improved resolution and interpretability resulting in improved calibration.

See-through Detection and 3D Reconstruction Using Terahertz Leaky-Wave Radar Based on Sparse Signal Processing

NASA Astrophysics Data System (ADS)

Murata, Koji; Murano, Kosuke; Watanabe, Issei; Kasamatsu, Akifumi; Tanaka, Toshiyuki; Monnai, Yasuaki

2018-02-01

We experimentally demonstrate see-through detection and 3D reconstruction using terahertz leaky-wave radar based on sparse signal processing. The application of terahertz waves to radar has received increasing attention in recent years for its potential to high-resolution and see-through detection. Among others, the implementation using a leaky-wave antenna is promising for compact system integration with beam steering capability based on frequency sweep. However, the use of a leaky-wave antenna poses a challenge on signal processing. Since a leaky-wave antenna combines the entire signal captured by each part of the aperture into a single output, the conventional array signal processing assuming access to a respective antenna element is not applicable. In this paper, we apply an iterative recovery algorithm "CoSaMP" to signals acquired with terahertz leaky-wave radar for clutter mitigation and aperture synthesis. We firstly demonstrate see-through detection of target location even when the radar is covered with an opaque screen, and therefore, the radar signal is disturbed by clutter. Furthermore, leveraging the robustness of the algorithm against noise, we also demonstrate 3D reconstruction of distributed targets by synthesizing signals collected from different orientations. The proposed approach will contribute to the smart implementation of terahertz leaky-wave radar.

Off-Grid Direction of Arrival Estimation Based on Joint Spatial Sparsity for Distributed Sparse Linear Arrays

PubMed Central

Liang, Yujie; Ying, Rendong; Lu, Zhenqi; Liu, Peilin

2014-01-01

In the design phase of sensor arrays during array signal processing, the estimation performance and system cost are largely determined by array aperture size. In this article, we address the problem of joint direction-of-arrival (DOA) estimation with distributed sparse linear arrays (SLAs) and propose an off-grid synchronous approach based on distributed compressed sensing to obtain larger array aperture. We focus on the complex source distribution in the practical applications and classify the sources into common and innovation parts according to whether a signal of source can impinge on all the SLAs or a specific one. For each SLA, we construct a corresponding virtual uniform linear array (ULA) to create the relationship of random linear map between the signals respectively observed by these two arrays. The signal ensembles including the common/innovation sources for different SLAs are abstracted as a joint spatial sparsity model. And we use the minimization of concatenated atomic norm via semidefinite programming to solve the problem of joint DOA estimation. Joint calculation of the signals observed by all the SLAs exploits their redundancy caused by the common sources and decreases the requirement of array size. The numerical results illustrate the advantages of the proposed approach. PMID:25420150

Joint image restoration and location in visual navigation system

NASA Astrophysics Data System (ADS)

Wu, Yuefeng; Sang, Nong; Lin, Wei; Shao, Yuanjie

2018-02-01

Image location methods are the key technologies of visual navigation, most previous image location methods simply assume the ideal inputs without taking into account the real-world degradations (e.g. low resolution and blur). In view of such degradations, the conventional image location methods first perform image restoration and then match the restored image on the reference image. However, the defective output of the image restoration can affect the result of localization, by dealing with the restoration and location separately. In this paper, we present a joint image restoration and location (JRL) method, which utilizes the sparse representation prior to handle the challenging problem of low-quality image location. The sparse representation prior states that the degraded input image, if correctly restored, will have a good sparse representation in terms of the dictionary constructed from the reference image. By iteratively solving the image restoration in pursuit of the sparest representation, our method can achieve simultaneous restoration and location. Based on such a sparse representation prior, we demonstrate that the image restoration task and the location task can benefit greatly from each other. Extensive experiments on real scene images with Gaussian blur are carried out and our joint model outperforms the conventional methods of treating the two tasks independently.

Simulation of co-phase error correction of optical multi-aperture imaging system based on stochastic parallel gradient decent algorithm

NASA Astrophysics Data System (ADS)

He, Xiaojun; Ma, Haotong; Luo, Chuanxin

2016-10-01

The optical multi-aperture imaging system is an effective way to magnify the aperture and increase the resolution of telescope optical system, the difficulty of which lies in detecting and correcting of co-phase error. This paper presents a method based on stochastic parallel gradient decent algorithm (SPGD) to correct the co-phase error. Compared with the current method, SPGD method can avoid detecting the co-phase error. This paper analyzed the influence of piston error and tilt error on image quality based on double-aperture imaging system, introduced the basic principle of SPGD algorithm, and discuss the influence of SPGD algorithm's key parameters (the gain coefficient and the disturbance amplitude) on error control performance. The results show that SPGD can efficiently correct the co-phase error. The convergence speed of the SPGD algorithm is improved with the increase of gain coefficient and disturbance amplitude, but the stability of the algorithm reduced. The adaptive gain coefficient can solve this problem appropriately. This paper's results can provide the theoretical reference for the co-phase error correction of the multi-aperture imaging system.

Image Reconstruction from Under sampled Fourier Data Using the Polynomial Annihilation Transform

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

Archibald, Richard K.; Gelb, Anne; Platte, Rodrigo

Fourier samples are collected in a variety of applications including magnetic resonance imaging and synthetic aperture radar. The data are typically under-sampled and noisy. In recent years, l 1 regularization has received considerable attention in designing image reconstruction algorithms from under-sampled and noisy Fourier data. The underlying image is assumed to have some sparsity features, that is, some measurable features of the image have sparse representation. The reconstruction algorithm is typically designed to solve a convex optimization problem, which consists of a fidelity term penalized by one or more l 1 regularization terms. The Split Bregman Algorithm provides a fastmore » explicit solution for the case when TV is used for the l1l1 regularization terms. Due to its numerical efficiency, it has been widely adopted for a variety of applications. A well known drawback in using TV as an l 1 regularization term is that the reconstructed image will tend to default to a piecewise constant image. This issue has been addressed in several ways. Recently, the polynomial annihilation edge detection method was used to generate a higher order sparsifying transform, and was coined the “polynomial annihilation (PA) transform.” This paper adapts the Split Bregman Algorithm for the case when the PA transform is used as the l 1 regularization term. In so doing, we achieve a more accurate image reconstruction method from under-sampled and noisy Fourier data. Our new method compares favorably to the TV Split Bregman Algorithm, as well as to the popular TGV combined with shearlet approach.« less

Mapping Water Level Dynamics over Central Congo River Using PALSAR Images, Envisat Altimetry, and Landsat NDVI Data

NASA Astrophysics Data System (ADS)

Kim, D.; Lee, H.; Jung, H. C.; Beighley, E.; Laraque, A.; Tshimanga, R.; Alsdorf, D. E.

2016-12-01

Rivers and wetlands are very important for ecological habitats, and it plays a key role in providing a source of greenhouse gases (CO2 and CH4). The floodplains ecosystems depend on the process between the vegetation and flood characteristics. The water level is a prerequisite to an understanding of terrestrial water storage and discharge. Despite the lack of in situ data over the Congo Basin, which is the world's third largest in size ( 3.7 million km2), and second only to the Amazon River in discharge ( 40,500 m3 s-1 annual average between 1902 and 2015 in the main Brazzaville-Kinshasa gauging station), the surface water level dynamics in the wetlands have been successfully estimated using satellite altimetry, backscattering coefficients (σ0) from Synthetic Aperture Radar (SAR) images and, interferometric SAR technique. However, the water level estimation of the Congo River remains poorly quantified due to the sparse orbital spacing of radar altimeters. Hence, we essentially have limited information only over the sparsely distributed the so-called "virtual stations". The backscattering coefficients from SAR images have been successfully used to distinguish different vegetation types, to monitor flood conditions, and to access soil moistures over the wetlands. However, σ0 has not been used to measure the water level changes over the open river because of very week return signal due to specular scattering. In this study, we have discovered that changes in σ0 over the Congo River occur mainly due to the water level changes in the river with the existence of the water plants (macrophytes, emergent plants, and submersed plant), depending on the rising and falling stage inside the depression of the "Cuvette Centrale". We expand the finding into generating the multi-temporal water level maps over the Congo River using PALSAR σ0, Envisat altimetry, and Landsat Normalized Difference Vegetation Index (NDVI) data. We also present preliminary estimates of the river discharge using the water level maps.

Aperture shape dependencies in extended depth of focus for imaging camera by wavefront coding

NASA Astrophysics Data System (ADS)

Sakita, Koichi; Ohta, Mitsuhiko; Shimano, Takeshi; Sakemoto, Akito

2015-02-01

Optical transfer functions (OTFs) on various directional spatial frequency axes for cubic phase mask (CPM) with circular and square apertures are investigated. Although OTF has no zero points, it has a very close value to zero for a circular aperture at low frequencies on diagonal axis, which results in degradation of restored images. The reason for close-to-zero value in OTF is also analyzed in connection with point spread function profiles using Fourier slice theorem. To avoid close-to-zero condition, square aperture with CPM is indispensable in WFC. We optimized cubic coefficient α of CPM and coefficients of digital filter, and succeeded to get excellent de-blurred images at large depth of field.

Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples

PubMed Central

Lakshmanan, Manu N.; Greenberg, Joel A.; Samei, Ehsan; Kapadia, Anuj J.

2016-01-01

Abstract. A scatter imaging technique for the differentiation of cancerous and healthy breast tissue in a heterogeneous sample is introduced in this work. Such a technique has potential utility in intraoperative margin assessment during lumpectomy procedures. In this work, we investigate the feasibility of the imaging method for tumor classification using Monte Carlo simulations and physical experiments. The coded aperture coherent scatter spectral imaging technique was used to reconstruct three-dimensional (3-D) images of breast tissue samples acquired through a single-position snapshot acquisition, without rotation as is required in coherent scatter computed tomography. We perform a quantitative assessment of the accuracy of the cancerous voxel classification using Monte Carlo simulations of the imaging system; describe our experimental implementation of coded aperture scatter imaging; show the reconstructed images of the breast tissue samples; and present segmentations of the 3-D images in order to identify the cancerous and healthy tissue in the samples. From the Monte Carlo simulations, we find that coded aperture scatter imaging is able to reconstruct images of the samples and identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) inside them with a cancerous voxel identification sensitivity, specificity, and accuracy of 92.4%, 91.9%, and 92.0%, respectively. From the experimental results, we find that the technique is able to identify cancerous and healthy tissue samples and reconstruct differential coherent scatter cross sections that are highly correlated with those measured by other groups using x-ray diffraction. Coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue inside samples within a time on the order of a minute per slice. PMID:26962543

Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples.

PubMed

Lakshmanan, Manu N; Greenberg, Joel A; Samei, Ehsan; Kapadia, Anuj J

2016-01-01

A scatter imaging technique for the differentiation of cancerous and healthy breast tissue in a heterogeneous sample is introduced in this work. Such a technique has potential utility in intraoperative margin assessment during lumpectomy procedures. In this work, we investigate the feasibility of the imaging method for tumor classification using Monte Carlo simulations and physical experiments. The coded aperture coherent scatter spectral imaging technique was used to reconstruct three-dimensional (3-D) images of breast tissue samples acquired through a single-position snapshot acquisition, without rotation as is required in coherent scatter computed tomography. We perform a quantitative assessment of the accuracy of the cancerous voxel classification using Monte Carlo simulations of the imaging system; describe our experimental implementation of coded aperture scatter imaging; show the reconstructed images of the breast tissue samples; and present segmentations of the 3-D images in order to identify the cancerous and healthy tissue in the samples. From the Monte Carlo simulations, we find that coded aperture scatter imaging is able to reconstruct images of the samples and identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) inside them with a cancerous voxel identification sensitivity, specificity, and accuracy of 92.4%, 91.9%, and 92.0%, respectively. From the experimental results, we find that the technique is able to identify cancerous and healthy tissue samples and reconstruct differential coherent scatter cross sections that are highly correlated with those measured by other groups using x-ray diffraction. Coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue inside samples within a time on the order of a minute per slice.

Reconstructing cortical current density by exploring sparseness in the transform domain

NASA Astrophysics Data System (ADS)

Ding, Lei

2009-05-01

In the present study, we have developed a novel electromagnetic source imaging approach to reconstruct extended cortical sources by means of cortical current density (CCD) modeling and a novel EEG imaging algorithm which explores sparseness in cortical source representations through the use of L1-norm in objective functions. The new sparse cortical current density (SCCD) imaging algorithm is unique since it reconstructs cortical sources by attaining sparseness in a transform domain (the variation map of cortical source distributions). While large variations are expected to occur along boundaries (sparseness) between active and inactive cortical regions, cortical sources can be reconstructed and their spatial extents can be estimated by locating these boundaries. We studied the SCCD algorithm using numerous simulations to investigate its capability in reconstructing cortical sources with different extents and in reconstructing multiple cortical sources with different extent contrasts. The SCCD algorithm was compared with two L2-norm solutions, i.e. weighted minimum norm estimate (wMNE) and cortical LORETA. Our simulation data from the comparison study show that the proposed sparse source imaging algorithm is able to accurately and efficiently recover extended cortical sources and is promising to provide high-accuracy estimation of cortical source extents.

Evaluation of fast highly undersampled contrast-enhanced MR angiography (sparse CE-MRA) in intracranial applications - initial study.

PubMed

Gratz, Marcel; Schlamann, Marc; Goericke, Sophia; Maderwald, Stefan; Quick, Harald H

2017-03-01

To assess the image quality of sparsely sampled contrast-enhanced MR angiography (sparse CE-MRA) providing high spatial resolution and whole-head coverage. Twenty-three patients scheduled for contrast-enhanced MR imaging of the head, (N = 19 with intracranial pathologies, N = 9 with vascular diseases), were included. Sparse CE-MRA at 3 Tesla was conducted using a single dose of contrast agent. Two neuroradiologists independently evaluated the data regarding vascular visibility and diagnostic value of overall 24 parameters and vascular segments on a 5-point ordinary scale (5 = very good, 1 = insufficient vascular visibility). Contrast bolus timing and the resulting arterio-venous overlap was also evaluated. Where available (N = 9), sparse CE-MRA was compared to intracranial Time-of-Flight MRA. The overall rating across all patients for sparse CE-MRA was 3.50 ± 1.07. Direct influence of the contrast bolus timing on the resulting image quality was observed. Overall mean vascular visibility and image quality across different features was rated good to intermediate (3.56 ± 0.95). The average performance of intracranial Time-of-Flight was rated 3.84 ± 0.87 across all patients and 3.54 ± 0.62 across all features. Sparse CE-MRA provides high-quality 3D MRA with high spatial resolution and whole-head coverage within short acquisition time. Accurate contrast bolus timing is mandatory. • Sparse CE-MRA enables fast vascular imaging with full brain coverage. • Volumes with sub-millimetre resolution can be acquired within 10 seconds. • Reader's ratings are good to intermediate and dependent on contrast bolus timing. • The method provides an excellent overview and allows screening for vascular pathologies.

Full-reference quality assessment of stereoscopic images by learning binocular receptive field properties.

PubMed

Shao, Feng; Li, Kemeng; Lin, Weisi; Jiang, Gangyi; Yu, Mei; Dai, Qionghai

2015-10-01

Quality assessment of 3D images encounters more challenges than its 2D counterparts. Directly applying 2D image quality metrics is not the solution. In this paper, we propose a new full-reference quality assessment for stereoscopic images by learning binocular receptive field properties to be more in line with human visual perception. To be more specific, in the training phase, we learn a multiscale dictionary from the training database, so that the latent structure of images can be represented as a set of basis vectors. In the quality estimation phase, we compute sparse feature similarity index based on the estimated sparse coefficient vectors by considering their phase difference and amplitude difference, and compute global luminance similarity index by considering luminance changes. The final quality score is obtained by incorporating binocular combination based on sparse energy and sparse complexity. Experimental results on five public 3D image quality assessment databases demonstrate that in comparison with the most related existing methods, the devised algorithm achieves high consistency with subjective assessment.

Three-Dimensional Terahertz Coded-Aperture Imaging Based on Single Input Multiple Output Technology.

PubMed

Chen, Shuo; Luo, Chenggao; Deng, Bin; Wang, Hongqiang; Cheng, Yongqiang; Zhuang, Zhaowen

2018-01-19

As a promising radar imaging technique, terahertz coded-aperture imaging (TCAI) can achieve high-resolution, forward-looking, and staring imaging by producing spatiotemporal independent signals with coded apertures. In this paper, we propose a three-dimensional (3D) TCAI architecture based on single input multiple output (SIMO) technology, which can reduce the coding and sampling times sharply. The coded aperture applied in the proposed TCAI architecture loads either purposive or random phase modulation factor. In the transmitting process, the purposive phase modulation factor drives the terahertz beam to scan the divided 3D imaging cells. In the receiving process, the random phase modulation factor is adopted to modulate the terahertz wave to be spatiotemporally independent for high resolution. Considering human-scale targets, images of each 3D imaging cell are reconstructed one by one to decompose the global computational complexity, and then are synthesized together to obtain the complete high-resolution image. As for each imaging cell, the multi-resolution imaging method helps to reduce the computational burden on a large-scale reference-signal matrix. The experimental results demonstrate that the proposed architecture can achieve high-resolution imaging with much less time for 3D targets and has great potential in applications such as security screening, nondestructive detection, medical diagnosis, etc.

The application of Fresnel zone plate based projection in optofluidic microscopy.

PubMed

Wu, Jigang; Cui, Xiquan; Lee, Lap Man; Yang, Changhuei

2008-09-29

Optofluidic microscopy (OFM) is a novel technique for low-cost, high-resolution on-chip microscopy imaging. In this paper we report the use of the Fresnel zone plate (FZP) based projection in OFM as a cost-effective and compact means for projecting the transmission through an OFM's aperture array onto a sensor grid. We demonstrate this approach by employing a FZP (diameter = 255 microm, focal length = 800 microm) that has been patterned onto a glass slide to project the transmission from an array of apertures (diameter = 1 microm, separation = 10 microm) onto a CMOS sensor. We are able to resolve the contributions from 44 apertures on the sensor under the illumination from a HeNe laser (wavelength = 633 nm). The imaging quality of the FZP determines the effective field-of-view (related to the number of resolvable transmissions from apertures) but not the image resolution of such an OFM system--a key distinction from conventional microscope systems. We demonstrate the capability of the integrated system by flowing the protist Euglena gracilis across the aperture array microfluidically and performing OFM imaging of the samples.

Simultaneous usage of pinhole and penumbral apertures for imaging small scale neutron sources from inertial confinement fusion experiments.

PubMed

Guler, N; Volegov, P; Danly, C R; Grim, G P; Merrill, F E; Wilde, C H

2012-10-01

Inertial confinement fusion experiments at the National Ignition Facility are designed to understand the basic principles of creating self-sustaining fusion reactions by laser driven compression of deuterium-tritium (DT) filled cryogenic plastic capsules. The neutron imaging diagnostic provides information on the distribution of the central fusion reaction region and the surrounding DT fuel by observing neutron images in two different energy bands for primary (13-17 MeV) and down-scattered (6-12 MeV) neutrons. From this, the final shape and size of the compressed capsule can be estimated and the symmetry of the compression can be inferred. These experiments provide small sources with high yield neutron flux. An aperture design that includes an array of pinholes and penumbral apertures has provided the opportunity to image the same source with two different techniques. This allows for an evaluation of these different aperture designs and reconstruction algorithms.

Space-time encoding for high frame rate ultrasound imaging.

PubMed

Misaridis, Thanassis X; Jensen, Jørgen A

2002-05-01

Frame rate in ultrasound imaging can be dramatically increased by using sparse synthetic transmit aperture (STA) beamforming techniques. The two main drawbacks of the method are the low signal-to-noise ratio (SNR) and the motion artifacts, that degrade the image quality. In this paper we propose a spatio-temporal encoding for STA imaging based on simultaneous transmission of two quasi-orthogonal tapered linear FM signals. The excitation signals are an up- and a down-chirp with frequency division and a cross-talk of -55 dB. The received signals are first cross-correlated with the appropriate code, then spatially decoded and finally beamformed for each code, yielding two images per emission. The spatial encoding is a Hadamard encoding previously suggested by Chiao et al. [in: Proceedings of the IEEE Ultrasonics Symposium, 1997, p. 1679]. The Hadamard matrix has half the size of the transmit element groups, due to the orthogonality of the temporal encoded wavefronts. Thus, with this method, the frame rate is doubled compared to previous systems. Another advantage is the utilization of temporal codes which are more robust to attenuation. With the proposed technique it is possible to obtain images dynamically focused in both transmit and receive with only two firings. This reduces the problem of motion artifacts. The method has been tested with extensive simulations using Field II. Resolution and SNR are compared with uncoded STA imaging and conventional phased-array imaging. The range resolution remains the same for coded STA imaging with four emissions and is slightly degraded for STA imaging with two emissions due to the -55 dB cross-talk between the signals. The additional proposed temporal encoding adds more than 15 dB on the SNR gain, yielding a SNR at the same order as in phased-array imaging.

Wide-aperture aspherical lens for high-resolution terahertz imaging

NASA Astrophysics Data System (ADS)

Chernomyrdin, Nikita V.; Frolov, Maxim E.; Lebedev, Sergey P.; Reshetov, Igor V.; Spektor, Igor E.; Tolstoguzov, Viktor L.; Karasik, Valeriy E.; Khorokhorov, Alexei M.; Koshelev, Kirill I.; Schadko, Aleksander O.; Yurchenko, Stanislav O.; Zaytsev, Kirill I.

2017-01-01

In this paper, we introduce wide-aperture aspherical lens for high-resolution terahertz (THz) imaging. The lens has been designed and analyzed by numerical methods of geometrical optics and electrodynamics. It has been made of high-density polyethylene by shaping at computer-controlled lathe and characterized using a continuous-wave THz imaging setup based on a backward-wave oscillator and Golay detector. The concept of image contrast has been implemented to estimate image quality. According to the experimental data, the lens allows resolving two points spaced at 0.95λ distance with a contrast of 15%. To highlight high resolution in the THz images, the wide-aperture lens has been employed for studying printed electronic circuit board containing sub-wavelength-scale elements. The observed results justify the high efficiency of the proposed lens design.

Joint sparse coding based spatial pyramid matching for classification of color medical image.

PubMed

Shi, Jun; Li, Yi; Zhu, Jie; Sun, Haojie; Cai, Yin

2015-04-01

Although color medical images are important in clinical practice, they are usually converted to grayscale for further processing in pattern recognition, resulting in loss of rich color information. The sparse coding based linear spatial pyramid matching (ScSPM) and its variants are popular for grayscale image classification, but cannot extract color information. In this paper, we propose a joint sparse coding based SPM (JScSPM) method for the classification of color medical images. A joint dictionary can represent both the color information in each color channel and the correlation between channels. Consequently, the joint sparse codes calculated from a joint dictionary can carry color information, and therefore this method can easily transform a feature descriptor originally designed for grayscale images to a color descriptor. A color hepatocellular carcinoma histological image dataset was used to evaluate the performance of the proposed JScSPM algorithm. Experimental results show that JScSPM provides significant improvements as compared with the majority voting based ScSPM and the original ScSPM for color medical image classification. Copyright © 2014 Elsevier Ltd. All rights reserved.

Effects of atmospheric turbulence on the imaging performance of optical system

NASA Astrophysics Data System (ADS)

Al-Hamadani, Ali H.; Zainulabdeen, Faten Sh.; Karam, Ghada Sabah; Nasir, Eman Yousif; Al-Saedi, Abaas

2018-05-01

Turbulent effects are very complicated and still not entirely understood. Light waves from an astronomical object are distorted as they pass through the atmosphere. The refractive index fluctuations in the turbulent atmosphere induce an optical path difference (OPD) between different parts of the wavefront, distorted wavefronts produce low-quality images and degrade the image beyond the diffraction limit. In this paper the image degradation due to 2-D Gaussian atmospheric turbulence is considered in terms of the point spread function (PSF), and Strehl ratio as an image quality criteria for imaging systems with different apertures using the pupil function teqneque. A general expression for the degraded PSF in the case of circular and square apertures (with half diagonal = √{π/2 } , and 1) diffraction limited and defocused optical system is considered. Based on the derived formula, the effect of the Gaussian atmospheric turbulence on circular and square pupils has been studied with details. Numerical results show that the performance of optical systems with square aperture is more efficient at high levels of atmospheric turbulence than the other apertures.

Development of a Coded Aperture X-Ray Backscatter Imager for Explosive Device Detection

NASA Astrophysics Data System (ADS)

Faust, Anthony A.; Rothschild, Richard E.; Leblanc, Philippe; McFee, John Elton

2009-02-01

Defence R&D Canada has an active research and development program on detection of explosive devices using nuclear methods. One system under development is a coded aperture-based X-ray backscatter imaging detector designed to provide sufficient speed, contrast and spatial resolution to detect antipersonnel landmines and improvised explosive devices. The successful development of a hand-held imaging detector requires, among other things, a light-weight, ruggedized detector with low power requirements, supplying high spatial resolution. The University of California, San Diego-designed HEXIS detector provides a modern, large area, high-temperature CZT imaging surface, robustly packaged in a light-weight housing with sound mechanical properties. Based on the potential for the HEXIS detector to be incorporated as the detection element of a hand-held imaging detector, the authors initiated a collaborative effort to demonstrate the capability of a coded aperture-based X-ray backscatter imaging detector. This paper will discuss the landmine and IED detection problem and review the coded aperture technique. Results from initial proof-of-principle experiments will then be reported.

Medical Image Fusion Based on Feature Extraction and Sparse Representation

PubMed Central

Wei, Gao; Zongxi, Song

2017-01-01

As a novel multiscale geometric analysis tool, sparse representation has shown many advantages over the conventional image representation methods. However, the standard sparse representation does not take intrinsic structure and its time complexity into consideration. In this paper, a new fusion mechanism for multimodal medical images based on sparse representation and decision map is proposed to deal with these problems simultaneously. Three decision maps are designed including structure information map (SM) and energy information map (EM) as well as structure and energy map (SEM) to make the results reserve more energy and edge information. SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation. The decision map is added to the normal sparse representation based method to improve the speed of the algorithm. Proposed approach also improves the quality of the fused results by enhancing the contrast and reserving more structure and energy information from the source images. The experiment results of 36 groups of CT/MR, MR-T1/MR-T2, and CT/PET images demonstrate that the method based on SR and SEM outperforms five state-of-the-art methods. PMID:28321246

Fast and low-dose computed laminography using compressive sensing based technique

NASA Astrophysics Data System (ADS)

Abbas, Sajid; Park, Miran; Cho, Seungryong

2015-03-01

Computed laminography (CL) is well known for inspecting microstructures in the materials, weldments and soldering defects in high density packed components or multilayer printed circuit boards. The overload problem on x-ray tube and gross failure of the radio-sensitive electronics devices during a scan are among important issues in CL which needs to be addressed. The sparse-view CL can be one of the viable option to overcome such issues. In this work a numerical aluminum welding phantom was simulated to collect sparsely sampled projection data at only 40 views using a conventional CL scanning scheme i.e. oblique scan. A compressive-sensing inspired total-variation (TV) minimization algorithm was utilized to reconstruct the images. It is found that the images reconstructed using sparse view data are visually comparable with the images reconstructed using full scan data set i.e. at 360 views on regular interval. We have quantitatively confirmed that tiny structures such as copper and tungsten slags, and copper flakes in the reconstructed images from sparsely sampled data are comparable with the corresponding structure present in the fully sampled data case. A blurring effect can be seen near the edges of few pores at the bottom of the reconstructed images from sparsely sampled data, despite the overall image quality is reasonable for fast and low-dose NDT.

Detecting breast microcalcifications using super-resolution ultrasound imaging: a clinical study

NASA Astrophysics Data System (ADS)

Huang, Lianjie; Labyed, Yassin; Hanson, Kenneth; Sandoval, Daniel; Pohl, Jennifer; Williamson, Michael

2013-03-01

Imaging breast microcalcifications is crucial for early detection and diagnosis of breast cancer. It is challenging for current clinical ultrasound to image breast microcalcifications. However, new imaging techniques using data acquired with a synthetic-aperture ultrasound system have the potential to significantly improve ultrasound imaging. We recently developed a super-resolution ultrasound imaging method termed the phase-coherent multiple-signal classification (PC-MUSIC). This signal subspace method accounts for the phase response of transducer elements to improve image resolution. In this paper, we investigate the clinical feasibility of our super-resolution ultrasound imaging method for detecting breast microcalcifications. We use our custom-built, real-time synthetic-aperture ultrasound system to acquire breast ultrasound data for 40 patients whose mammograms show the presence of breast microcalcifications. We apply our super-resolution ultrasound imaging method to the patient data, and produce clear images of breast calcifications. Our super-resolution ultrasound PC-MUSIC imaging with synthetic-aperture ultrasound data can provide a new imaging modality for detecting breast microcalcifications in clinic without using ionizing radiation.

Interference Mitigation Effects on Synthetic Aperture Radar Coherent Data Products

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

Musgrove, Cameron

For synthetic aperture radars radio frequency interference from sources external to the radar system and techniques to mitigate the interference can degrade the quality of the image products. Usually the radar system designer will try to balance the amount of mitigation for an acceptable amount of interference to optimize the image quality. This dissertation examines the effect of interference mitigation upon coherent data products of fine resolution, high frequency synthetic aperture radars using stretch processing. Novel interference mitigation techniques are introduced that operate on single or multiple apertures of data that increase average coherence compared to existing techniques. New metricsmore » are applied to evaluate multiple mitigation techniques for image quality and average coherence. The underlying mechanism for interference mitigation techniques that affect coherence is revealed.« less

SU-G-IeP3-07: High-Resolution, High-Sensitivity Imaging and Quantification of Intratumoral Distributions of Gold Nanoparticles Using a Benchtop L-Shell XRF Imaging System

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

Manohar, N; Diagaradjane, P; Krishnan, S

2016-06-15

Purpose: To demonstrate the ability to perform high-resolution imaging and quantification of sparse distributions of gold nanoparticles (GNPs) within ex vivo tumor samples using a highly-sensitive benchtop L-shell x-ray fluorescence (XRF) imaging system. Methods: An optimized L-shell XRF imaging system was assembled using a tungsten-target x-ray source (operated at 62 kVp and 45 mA). The x-rays were filtered (copper: 0.08 mm & aluminum: 0.04 mm) and collimated (lead: 5 cm thickness, 3 cm aperture diameter) into a cone-beam in order to irradiate small samples or objects. A collimated (stainless steel: 4 cm thickness, 2 mm aperture diameter) silicon drift detector,more » capable of 2D translation, was placed at 90° with respect to the beam to acquire XRF/scatter spectra from regions of interest. Spectral processing involved extracting XRF signal from background, followed by attenuation correction using a Compton scatter-based normalization algorithm. Calibration phantoms with water/GNPs (0 and 0.00001–10 mg/cm{sup 3}) were used to determine the detection limit of the system at a 10-second acquisition time. The system was then used to map the distribution of GNPs within a 12×11×2 mm{sup 3} slice excised from the center of a GNP-loaded ex vivo murine tumor sample; a total of 110 voxels (2.65×10{sup −3} cm{sup 3}) were imaged with 1.3-mm spatial resolution. Results: The detection limit of the current cone-beam benchtop L-shell XRF system was 0.003 mg/cm{sup 3} (3 ppm). Intratumoral GNP concentrations ranging from 0.003 mg/cm{sup 3} (3 ppm) to a maximum of 0.055 mg/cm{sup 3} (55 ppm) and average of 0.0093 mg/cm{sup 3} (9.3 ppm) were imaged successfully within the ex vivo tumor slice. Conclusion: The developed cone-beam benchtop L-shell XRF imaging system can immediately be used for imaging of ex vivo tumor samples containing low concentrations of GNPs. With minor finetuning/optimization, the system can be directly adapted for performing routine preclinical in vivo imaging tasks. Supported by NIH/NCI grant R01CA155446 This investigation was supported by NIH/NCI grant R01CA155446.« less

Infrared moving small target detection based on saliency extraction and image sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Xiaomin; Ren, Kan; Gao, Jin; Li, Chaowei; Gu, Guohua; Wan, Minjie

2016-10-01

Moving small target detection in infrared image is a crucial technique of infrared search and tracking system. This paper present a novel small target detection technique based on frequency-domain saliency extraction and image sparse representation. First, we exploit the features of Fourier spectrum image and magnitude spectrum of Fourier transform to make a rough extract of saliency regions and use a threshold segmentation system to classify the regions which look salient from the background, which gives us a binary image as result. Second, a new patch-image model and over-complete dictionary were introduced to the detection system, then the infrared small target detection was converted into a problem solving and optimization process of patch-image information reconstruction based on sparse representation. More specifically, the test image and binary image can be decomposed into some image patches follow certain rules. We select the target potential area according to the binary patch-image which contains salient region information, then exploit the over-complete infrared small target dictionary to reconstruct the test image blocks which may contain targets. The coefficients of target image patch satisfy sparse features. Finally, for image sequence, Euclidean distance was used to reduce false alarm ratio and increase the detection accuracy of moving small targets in infrared images due to the target position correlation between frames.

Sparse aperture masking interferometry survey of transitional discs. Search for substellar-mass companions and asymmetries in their parent discs

NASA Astrophysics Data System (ADS)

Willson, M.; Kraus, S.; Kluska, J.; Monnier, J. D.; Ireland, M.; Aarnio, A.; Sitko, M. L.; Calvet, N.; Espaillat, C.; Wilner, D. J.

2016-10-01

Context. Transitional discs are a class of circumstellar discs around young stars with extensive clearing of dusty material within their inner regions on 10s of au scales. One of the primary candidates for this kind of clearing is the formation of planet(s) within the disc that then accrete or clear their immediate area as they migrate through the disc. Aims: The goal of this survey was to search for asymmetries in the brightness distribution around a selection of transitional disc targets. We then aimed to determine whether these asymmetries trace dynamically-induced structures in the disc or the gap-opening planets themselves. Methods: Our sample included eight transitional discs. Using the Keck/NIRC2 instrument we utilised the Sparse Aperture Masking (SAM) interferometry technique to search for asymmetries indicative of ongoing planet formation. We searched for close-in companions using both model fitting and interferometric image reconstruction techniques. Using simulated data, we derived diagnostics that helped us to distinguish between point sources and extended asymmetric disc emission. In addition, we investigated the degeneracy between the contrast and separation that appear for marginally resolved companions. Results: We found FP Tau to contain a previously unseen disc wall, and DM Tau, LkHα330, and TW Hya to contain an asymmetric signal indicative of point source-like emission. We placed upper limits on the contrast of a companion in RXJ 1842.9-3532 and V2246 Oph. We ruled the asymmetry signal in RXJ 1615.3-3255 and V2062 Oph to be false positives. In the cases where our data indicated a potential companion we computed estimates for the value of McṀc and found values in the range of . Conclusions: We found significant asymmetries in four targets. Of these, three were consistent with companions. We resolved a previously unseen gap in the disc of FP Tau extending inwards from approximately 10 au. Based on observations made with the Keck observatory (NASA program IDs N104N2 and N121N2).

Infrared and visible image fusion based on robust principal component analysis and compressed sensing

NASA Astrophysics Data System (ADS)

Li, Jun; Song, Minghui; Peng, Yuanxi

2018-03-01

Current infrared and visible image fusion methods do not achieve adequate information extraction, i.e., they cannot extract the target information from infrared images while retaining the background information from visible images. Moreover, most of them have high complexity and are time-consuming. This paper proposes an efficient image fusion framework for infrared and visible images on the basis of robust principal component analysis (RPCA) and compressed sensing (CS). The novel framework consists of three phases. First, RPCA decomposition is applied to the infrared and visible images to obtain their sparse and low-rank components, which represent the salient features and background information of the images, respectively. Second, the sparse and low-rank coefficients are fused by different strategies. On the one hand, the measurements of the sparse coefficients are obtained by the random Gaussian matrix, and they are then fused by the standard deviation (SD) based fusion rule. Next, the fused sparse component is obtained by reconstructing the result of the fused measurement using the fast continuous linearized augmented Lagrangian algorithm (FCLALM). On the other hand, the low-rank coefficients are fused using the max-absolute rule. Subsequently, the fused image is superposed by the fused sparse and low-rank components. For comparison, several popular fusion algorithms are tested experimentally. By comparing the fused results subjectively and objectively, we find that the proposed framework can extract the infrared targets while retaining the background information in the visible images. Thus, it exhibits state-of-the-art performance in terms of both fusion effects and timeliness.

Polarization-based compensation of astigmatism.

PubMed

Chowdhury, Dola Roy; Bhattacharya, Kallol; Chakraborty, Ajay K; Ghosh, Raja

2004-02-01

One approach to aberration compensation of an imaging system is to introduce a suitable phase mask at the aperture plane of an imaging system. We utilize this principle for the compensation of astigmatism. A suitable polarization mask used on the aperture plane together with a polarizer-retarder combination at the input of the imaging system provides the compensating polarization-induced phase steps at different quadrants of the apertures masked by different polarizers. The aberrant phase can be considerably compensated by the proper choice of a polarization mask and suitable selection of the polarization parameters involved. The results presented here bear out our theoretical expectation.

Learning Low-Rank Class-Specific Dictionary and Sparse Intra-Class Variant Dictionary for Face Recognition.

PubMed

Tang, Xin; Feng, Guo-Can; Li, Xiao-Xin; Cai, Jia-Xin

2015-01-01

Face recognition is challenging especially when the images from different persons are similar to each other due to variations in illumination, expression, and occlusion. If we have sufficient training images of each person which can span the facial variations of that person under testing conditions, sparse representation based classification (SRC) achieves very promising results. However, in many applications, face recognition often encounters the small sample size problem arising from the small number of available training images for each person. In this paper, we present a novel face recognition framework by utilizing low-rank and sparse error matrix decomposition, and sparse coding techniques (LRSE+SC). Firstly, the low-rank matrix recovery technique is applied to decompose the face images per class into a low-rank matrix and a sparse error matrix. The low-rank matrix of each individual is a class-specific dictionary and it captures the discriminative feature of this individual. The sparse error matrix represents the intra-class variations, such as illumination, expression changes. Secondly, we combine the low-rank part (representative basis) of each person into a supervised dictionary and integrate all the sparse error matrix of each individual into a within-individual variant dictionary which can be applied to represent the possible variations between the testing and training images. Then these two dictionaries are used to code the query image. The within-individual variant dictionary can be shared by all the subjects and only contribute to explain the lighting conditions, expressions, and occlusions of the query image rather than discrimination. At last, a reconstruction-based scheme is adopted for face recognition. Since the within-individual dictionary is introduced, LRSE+SC can handle the problem of the corrupted training data and the situation that not all subjects have enough samples for training. Experimental results show that our method achieves the state-of-the-art results on AR, FERET, FRGC and LFW databases.

Learning Low-Rank Class-Specific Dictionary and Sparse Intra-Class Variant Dictionary for Face Recognition

PubMed Central

Tang, Xin; Feng, Guo-can; Li, Xiao-xin; Cai, Jia-xin

2015-01-01

Face recognition is challenging especially when the images from different persons are similar to each other due to variations in illumination, expression, and occlusion. If we have sufficient training images of each person which can span the facial variations of that person under testing conditions, sparse representation based classification (SRC) achieves very promising results. However, in many applications, face recognition often encounters the small sample size problem arising from the small number of available training images for each person. In this paper, we present a novel face recognition framework by utilizing low-rank and sparse error matrix decomposition, and sparse coding techniques (LRSE+SC). Firstly, the low-rank matrix recovery technique is applied to decompose the face images per class into a low-rank matrix and a sparse error matrix. The low-rank matrix of each individual is a class-specific dictionary and it captures the discriminative feature of this individual. The sparse error matrix represents the intra-class variations, such as illumination, expression changes. Secondly, we combine the low-rank part (representative basis) of each person into a supervised dictionary and integrate all the sparse error matrix of each individual into a within-individual variant dictionary which can be applied to represent the possible variations between the testing and training images. Then these two dictionaries are used to code the query image. The within-individual variant dictionary can be shared by all the subjects and only contribute to explain the lighting conditions, expressions, and occlusions of the query image rather than discrimination. At last, a reconstruction-based scheme is adopted for face recognition. Since the within-individual dictionary is introduced, LRSE+SC can handle the problem of the corrupted training data and the situation that not all subjects have enough samples for training. Experimental results show that our method achieves the state-of-the-art results on AR, FERET, FRGC and LFW databases. PMID:26571112

Sparse-view photoacoustic tomography using virtual parallel-projections and spatially adaptive filtering

NASA Astrophysics Data System (ADS)

Wang, Yihan; Lu, Tong; Wan, Wenbo; Liu, Lingling; Zhang, Songhe; Li, Jiao; Zhao, Huijuan; Gao, Feng

2018-02-01

To fully realize the potential of photoacoustic tomography (PAT) in preclinical and clinical applications, rapid measurements and robust reconstructions are needed. Sparse-view measurements have been adopted effectively to accelerate the data acquisition. However, since the reconstruction from the sparse-view sampling data is challenging, both of the effective measurement and the appropriate reconstruction should be taken into account. In this study, we present an iterative sparse-view PAT reconstruction scheme where a virtual parallel-projection concept matching for the proposed measurement condition is introduced to help to achieve the "compressive sensing" procedure of the reconstruction, and meanwhile the spatially adaptive filtering fully considering the a priori information of the mutually similar blocks existing in natural images is introduced to effectively recover the partial unknown coefficients in the transformed domain. Therefore, the sparse-view PAT images can be reconstructed with higher quality compared with the results obtained by the universal back-projection (UBP) algorithm in the same sparse-view cases. The proposed approach has been validated by simulation experiments, which exhibits desirable performances in image fidelity even from a small number of measuring positions.

Numerical simulations of imaging satellites with optical interferometry

NASA Astrophysics Data System (ADS)

Ding, Yuanyuan; Wang, Chaoyan; Chen, Zhendong

2015-08-01

Optical interferometry imaging system, which is composed of multiple sub-apertures, is a type of sensor that can break through the aperture limit and realize the high resolution imaging. This technique can be utilized to precisely measure the shapes, sizes and position of astronomical objects and satellites, it also can realize to space exploration and space debris, satellite monitoring and survey. Fizeau-Type optical aperture synthesis telescope has the advantage of short baselines, common mount and multiple sub-apertures, so it is feasible for instantaneous direct imaging through focal plane combination.Since 2002, the researchers of Shanghai Astronomical Observatory have developed the study of optical interferometry technique. For array configurations, there are two optimal array configurations proposed instead of the symmetrical circular distribution: the asymmetrical circular distribution and the Y-type distribution. On this basis, two kinds of structure were proposed based on Fizeau interferometric telescope. One is Y-type independent sub-aperture telescope, the other one is segmented mirrors telescope with common secondary mirror.In this paper, we will give the description of interferometric telescope and image acquisition. Then we will mainly concerned the simulations of image restoration based on Y-type telescope and segmented mirrors telescope. The Richardson-Lucy (RL) method, Winner method and the Ordered Subsets Expectation Maximization (OS-EM) method are studied in this paper. We will analyze the influence of different stop rules too. At the last of the paper, we will present the reconstruction results of images of some satellites.

Edge detection based on adaptive threshold b-spline wavelet for optical sub-aperture measuring

NASA Astrophysics Data System (ADS)

Zhang, Shiqi; Hui, Mei; Liu, Ming; Zhao, Zhu; Dong, Liquan; Liu, Xiaohua; Zhao, Yuejin

2015-08-01

In the research of optical synthetic aperture imaging system, phase congruency is the main problem and it is necessary to detect sub-aperture phase. The edge of the sub-aperture system is more complex than that in the traditional optical imaging system. And with the existence of steep slope for large-aperture optical component, interference fringe may be quite dense when interference imaging. Deep phase gradient may cause a loss of phase information. Therefore, it's urgent to search for an efficient edge detection method. Wavelet analysis as a powerful tool is widely used in the fields of image processing. Based on its properties of multi-scale transform, edge region is detected with high precision in small scale. Longing with the increase of scale, noise is reduced in contrary. So it has a certain suppression effect on noise. Otherwise, adaptive threshold method which sets different thresholds in various regions can detect edge points from noise. Firstly, fringe pattern is obtained and cubic b-spline wavelet is adopted as the smoothing function. After the multi-scale wavelet decomposition of the whole image, we figure out the local modulus maxima in gradient directions. However, it also contains noise, and thus adaptive threshold method is used to select the modulus maxima. The point which greater than threshold value is boundary point. Finally, we use corrosion and expansion deal with the resulting image to get the consecutive boundary of image.

Sparse representation-based image restoration via nonlocal supervised coding

NASA Astrophysics Data System (ADS)

Li, Ao; Chen, Deyun; Sun, Guanglu; Lin, Kezheng

2016-10-01

Sparse representation (SR) and nonlocal technique (NLT) have shown great potential in low-level image processing. However, due to the degradation of the observed image, SR and NLT may not be accurate enough to obtain a faithful restoration results when they are used independently. To improve the performance, in this paper, a nonlocal supervised coding strategy-based NLT for image restoration is proposed. The novel method has three main contributions. First, to exploit the useful nonlocal patches, a nonnegative sparse representation is introduced, whose coefficients can be utilized as the supervised weights among patches. Second, a novel objective function is proposed, which integrated the supervised weights learning and the nonlocal sparse coding to guarantee a more promising solution. Finally, to make the minimization tractable and convergence, a numerical scheme based on iterative shrinkage thresholding is developed to solve the above underdetermined inverse problem. The extensive experiments validate the effectiveness of the proposed method.

Exploring Deep Learning and Sparse Matrix Format Selection

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

Zhao, Y.; Liao, C.; Shen, X.

We proposed to explore the use of Deep Neural Networks (DNN) for addressing the longstanding barriers. The recent rapid progress of DNN technology has created a large impact in many fields, which has significantly improved the prediction accuracy over traditional machine learning techniques in image classifications, speech recognitions, machine translations, and so on. To some degree, these tasks resemble the decision makings in many HPC tasks, including the aforementioned format selection for SpMV and linear solver selection. For instance, sparse matrix format selection is akin to image classification—such as, to tell whether an image contains a dog or a cat;more » in both problems, the right decisions are primarily determined by the spatial patterns of the elements in an input. For image classification, the patterns are of pixels, and for sparse matrix format selection, they are of non-zero elements. DNN could be naturally applied if we regard a sparse matrix as an image and the format selection or solver selection as classification problems.« less

Dimension-Factorized Range Migration Algorithm for Regularly Distributed Array Imaging

PubMed Central

Guo, Qijia; Wang, Jie; Chang, Tianying

2017-01-01

The two-dimensional planar MIMO array is a popular approach for millimeter wave imaging applications. As a promising practical alternative, sparse MIMO arrays have been devised to reduce the number of antenna elements and transmitting/receiving channels with predictable and acceptable loss in image quality. In this paper, a high precision three-dimensional imaging algorithm is proposed for MIMO arrays of the regularly distributed type, especially the sparse varieties. Termed the Dimension-Factorized Range Migration Algorithm, the new imaging approach factorizes the conventional MIMO Range Migration Algorithm into multiple operations across the sparse dimensions. The thinner the sparse dimensions of the array, the more efficient the new algorithm will be. Advantages of the proposed approach are demonstrated by comparison with the conventional MIMO Range Migration Algorithm and its non-uniform fast Fourier transform based variant in terms of all the important characteristics of the approaches, especially the anti-noise capability. The computation cost is analyzed as well to evaluate the efficiency quantitatively. PMID:29113083

Emotional textile image classification based on cross-domain convolutional sparse autoencoders with feature selection

NASA Astrophysics Data System (ADS)

Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin

2017-01-01

We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.

Sparse image reconstruction for molecular imaging.

PubMed

Ting, Michael; Raich, Raviv; Hero, Alfred O

2009-06-01

The application that motivates this paper is molecular imaging at the atomic level. When discretized at subatomic distances, the volume is inherently sparse. Noiseless measurements from an imaging technology can be modeled by convolution of the image with the system point spread function (psf). Such is the case with magnetic resonance force microscopy (MRFM), an emerging technology where imaging of an individual tobacco mosaic virus was recently demonstrated with nanometer resolution. We also consider additive white Gaussian noise (AWGN) in the measurements. Many prior works of sparse estimators have focused on the case when H has low coherence; however, the system matrix H in our application is the convolution matrix for the system psf. A typical convolution matrix has high coherence. This paper, therefore, does not assume a low coherence H. A discrete-continuous form of the Laplacian and atom at zero (LAZE) p.d.f. used by Johnstone and Silverman is formulated, and two sparse estimators derived by maximizing the joint p.d.f. of the observation and image conditioned on the hyperparameters. A thresholding rule that generalizes the hard and soft thresholding rule appears in the course of the derivation. This so-called hybrid thresholding rule, when used in the iterative thresholding framework, gives rise to the hybrid estimator, a generalization of the lasso. Estimates of the hyperparameters for the lasso and hybrid estimator are obtained via Stein's unbiased risk estimate (SURE). A numerical study with a Gaussian psf and two sparse images shows that the hybrid estimator outperforms the lasso.

Integrating polarimetric synthetic aperture radar and imaging spectrometry for wildland fuel mapping in southern California

Treesearch

P.E. Dennison; D.A. Roberts; J. Regelbrugge; S.L. Ustin

2000-01-01

Polarimetric synthetic aperture radar (SAR) and imaging spectrometry exemplify advanced technologies for mapping wildland fuels in chaparral ecosystems. In this study, we explore the potential of integrating polarimetric SAR and imaging spectrometry for mapping wildland fuels. P-band SAR and ratios containing P-band polarizations are sensitive to variations in stand...

Multibeam single frequency synthetic aperture radar processor for imaging separate range swaths

NASA Technical Reports Server (NTRS)

Jain, A. (Inventor)

1982-01-01

A single-frequency multibeam synthetic aperture radar for large swath imaging is disclosed. Each beam illuminates a separate ""footprint'' (i.e., range and azimuth interval). The distinct azimuth intervals for the separate beams produce a distinct Doppler frequency spectrum for each beam. After range correlation of raw data, an optical processor develops image data for the different beams by spatially separating the beams to place each beam of different Doppler frequency spectrum in a different location in the frequency plane as well as the imaging plane of the optical processor. Selection of a beam for imaging may be made in the frequency plane by adjusting the position of an aperture, or in the image plane by adjusting the position of a slit. The raw data may also be processed in digital form in an analogous manner.

Nonlinear spike-and-slab sparse coding for interpretable image encoding.

PubMed

Shelton, Jacquelyn A; Sheikh, Abdul-Saboor; Bornschein, Jörg; Sterne, Philip; Lücke, Jörg

2015-01-01

Sparse coding is a popular approach to model natural images but has faced two main challenges: modelling low-level image components (such as edge-like structures and their occlusions) and modelling varying pixel intensities. Traditionally, images are modelled as a sparse linear superposition of dictionary elements, where the probabilistic view of this problem is that the coefficients follow a Laplace or Cauchy prior distribution. We propose a novel model that instead uses a spike-and-slab prior and nonlinear combination of components. With the prior, our model can easily represent exact zeros for e.g. the absence of an image component, such as an edge, and a distribution over non-zero pixel intensities. With the nonlinearity (the nonlinear max combination rule), the idea is to target occlusions; dictionary elements correspond to image components that can occlude each other. There are major consequences of the model assumptions made by both (non)linear approaches, thus the main goal of this paper is to isolate and highlight differences between them. Parameter optimization is analytically and computationally intractable in our model, thus as a main contribution we design an exact Gibbs sampler for efficient inference which we can apply to higher dimensional data using latent variable preselection. Results on natural and artificial occlusion-rich data with controlled forms of sparse structure show that our model can extract a sparse set of edge-like components that closely match the generating process, which we refer to as interpretable components. Furthermore, the sparseness of the solution closely follows the ground-truth number of components/edges in the images. The linear model did not learn such edge-like components with any level of sparsity. This suggests that our model can adaptively well-approximate and characterize the meaningful generation process.

Nonlinear Spike-And-Slab Sparse Coding for Interpretable Image Encoding

PubMed Central

Shelton, Jacquelyn A.; Sheikh, Abdul-Saboor; Bornschein, Jörg; Sterne, Philip; Lücke, Jörg

2015-01-01

Sparse coding is a popular approach to model natural images but has faced two main challenges: modelling low-level image components (such as edge-like structures and their occlusions) and modelling varying pixel intensities. Traditionally, images are modelled as a sparse linear superposition of dictionary elements, where the probabilistic view of this problem is that the coefficients follow a Laplace or Cauchy prior distribution. We propose a novel model that instead uses a spike-and-slab prior and nonlinear combination of components. With the prior, our model can easily represent exact zeros for e.g. the absence of an image component, such as an edge, and a distribution over non-zero pixel intensities. With the nonlinearity (the nonlinear max combination rule), the idea is to target occlusions; dictionary elements correspond to image components that can occlude each other. There are major consequences of the model assumptions made by both (non)linear approaches, thus the main goal of this paper is to isolate and highlight differences between them. Parameter optimization is analytically and computationally intractable in our model, thus as a main contribution we design an exact Gibbs sampler for efficient inference which we can apply to higher dimensional data using latent variable preselection. Results on natural and artificial occlusion-rich data with controlled forms of sparse structure show that our model can extract a sparse set of edge-like components that closely match the generating process, which we refer to as interpretable components. Furthermore, the sparseness of the solution closely follows the ground-truth number of components/edges in the images. The linear model did not learn such edge-like components with any level of sparsity. This suggests that our model can adaptively well-approximate and characterize the meaningful generation process. PMID:25954947

Semi-blind sparse image reconstruction with application to MRFM.

PubMed

Park, Se Un; Dobigeon, Nicolas; Hero, Alfred O

2012-09-01

We propose a solution to the image deconvolution problem where the convolution kernel or point spread function (PSF) is assumed to be only partially known. Small perturbations generated from the model are exploited to produce a few principal components explaining the PSF uncertainty in a high-dimensional space. Unlike recent developments on blind deconvolution of natural images, we assume the image is sparse in the pixel basis, a natural sparsity arising in magnetic resonance force microscopy (MRFM). Our approach adopts a Bayesian Metropolis-within-Gibbs sampling framework. The performance of our Bayesian semi-blind algorithm for sparse images is superior to previously proposed semi-blind algorithms such as the alternating minimization algorithm and blind algorithms developed for natural images. We illustrate our myopic algorithm on real MRFM tobacco virus data.

Visual saliency detection based on in-depth analysis of sparse representation

NASA Astrophysics Data System (ADS)

Wang, Xin; Shen, Siqiu; Ning, Chen

2018-03-01

Visual saliency detection has been receiving great attention in recent years since it can facilitate a wide range of applications in computer vision. A variety of saliency models have been proposed based on different assumptions within which saliency detection via sparse representation is one of the newly arisen approaches. However, most existing sparse representation-based saliency detection methods utilize partial characteristics of sparse representation, lacking of in-depth analysis. Thus, they may have limited detection performance. Motivated by this, this paper proposes an algorithm for detecting visual saliency based on in-depth analysis of sparse representation. A number of discriminative dictionaries are first learned with randomly sampled image patches by means of inner product-based dictionary atom classification. Then, the input image is partitioned into many image patches, and these patches are classified into salient and nonsalient ones based on the in-depth analysis of sparse coding coefficients. Afterward, sparse reconstruction errors are calculated for the salient and nonsalient patch sets. By investigating the sparse reconstruction errors, the most salient atoms, which tend to be from the most salient region, are screened out and taken away from the discriminative dictionaries. Finally, an effective method is exploited for saliency map generation with the reduced dictionaries. Comprehensive evaluations on publicly available datasets and comparisons with some state-of-the-art approaches demonstrate the effectiveness of the proposed algorithm.

Spectral domain optical coherence tomography with extended depth-of-focus by aperture synthesis

NASA Astrophysics Data System (ADS)

Bo, En; Liu, Linbo

2016-10-01

We developed a spectral domain optical coherence tomography (SD-OCT) with an extended depth-of-focus (DOF) by synthetizing aperture. For a designated Gaussian-shape light source, the lateral resolution was determined by the numerical aperture (NA) of the objective lens and can be approximately maintained over the confocal parameter, which was defined as twice the Rayleigh range. However, the DOF was proportional to the square of the lateral resolution. Consequently, a trade-off existed between the DOF and lateral resolution, and researchers had to weigh and judge which was more important for their research reasonably. In this study, three distinct optical apertures were obtained by imbedding a circular phase spacer in the sample arm. Due to the optical path difference between three distinct apertures caused by the phase spacer, three images were aligned with equal spacing along z-axis vertically. By correcting the optical path difference (OPD) and defocus-induced wavefront curvature, three images with distinct depths were coherently summed together. This system digitally refocused the sample tissue and obtained a brand new image with higher lateral resolution over the confocal parameter when imaging the polystyrene calibration beads.

Sparse Representation for Color Image Restoration (PREPRINT)

DTIC Science & Technology

2006-10-01

as a universal denoiser of images, which learns the posterior from the given image in a way inspired by the Lempel - Ziv universal compression ...such as images, admit a sparse decomposition over a redundant dictionary leads to efficient algorithms for handling such sources of data . In...describe the data source. Such a model becomes paramount when developing algorithms for processing these signals. In this context, Markov-Random-Field

Three-dimensional image authentication scheme using sparse phase information in double random phase encoded integral imaging.

PubMed

Yi, Faliu; Jeoung, Yousun; Moon, Inkyu

2017-05-20

In recent years, many studies have focused on authentication of two-dimensional (2D) images using double random phase encryption techniques. However, there has been little research on three-dimensional (3D) imaging systems, such as integral imaging, for 3D image authentication. We propose a 3D image authentication scheme based on a double random phase integral imaging method. All of the 2D elemental images captured through integral imaging are encrypted with a double random phase encoding algorithm and only partial phase information is reserved. All the amplitude and other miscellaneous phase information in the encrypted elemental images is discarded. Nevertheless, we demonstrate that 3D images from integral imaging can be authenticated at different depths using a nonlinear correlation method. The proposed 3D image authentication algorithm can provide enhanced information security because the decrypted 2D elemental images from the sparse phase cannot be easily observed by the naked eye. Additionally, using sparse phase images without any amplitude information can greatly reduce data storage costs and aid in image compression and data transmission.

Fast and low-dose computed laminography using compressive sensing based technique

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

Abbas, Sajid, E-mail: scho@kaist.ac.kr; Park, Miran, E-mail: scho@kaist.ac.kr; Cho, Seungryong, E-mail: scho@kaist.ac.kr

2015-03-31

Computed laminography (CL) is well known for inspecting microstructures in the materials, weldments and soldering defects in high density packed components or multilayer printed circuit boards. The overload problem on x-ray tube and gross failure of the radio-sensitive electronics devices during a scan are among important issues in CL which needs to be addressed. The sparse-view CL can be one of the viable option to overcome such issues. In this work a numerical aluminum welding phantom was simulated to collect sparsely sampled projection data at only 40 views using a conventional CL scanning scheme i.e. oblique scan. A compressive-sensing inspiredmore » total-variation (TV) minimization algorithm was utilized to reconstruct the images. It is found that the images reconstructed using sparse view data are visually comparable with the images reconstructed using full scan data set i.e. at 360 views on regular interval. We have quantitatively confirmed that tiny structures such as copper and tungsten slags, and copper flakes in the reconstructed images from sparsely sampled data are comparable with the corresponding structure present in the fully sampled data case. A blurring effect can be seen near the edges of few pores at the bottom of the reconstructed images from sparsely sampled data, despite the overall image quality is reasonable for fast and low-dose NDT.« less

Large-scale two-photon imaging revealed super-sparse population codes in the V1 superficial layer of awake monkeys.

PubMed

Tang, Shiming; Zhang, Yimeng; Li, Zhihao; Li, Ming; Liu, Fang; Jiang, Hongfei; Lee, Tai Sing

2018-04-26

One general principle of sensory information processing is that the brain must optimize efficiency by reducing the number of neurons that process the same information. The sparseness of the sensory representations in a population of neurons reflects the efficiency of the neural code. Here, we employ large-scale two-photon calcium imaging to examine the responses of a large population of neurons within the superficial layers of area V1 with single-cell resolution, while simultaneously presenting a large set of natural visual stimuli, to provide the first direct measure of the population sparseness in awake primates. The results show that only 0.5% of neurons respond strongly to any given natural image - indicating a ten-fold increase in the inferred sparseness over previous measurements. These population activities are nevertheless necessary and sufficient to discriminate visual stimuli with high accuracy, suggesting that the neural code in the primary visual cortex is both super-sparse and highly efficient. © 2018, Tang et al.

Detection of dual-band infrared small target based on joint dynamic sparse representation

NASA Astrophysics Data System (ADS)

Zhou, Jinwei; Li, Jicheng; Shi, Zhiguang; Lu, Xiaowei; Ren, Dongwei

2015-10-01

Infrared small target detection is a crucial and yet still is a difficult issue in aeronautic and astronautic applications. Sparse representation is an important mathematic tool and has been used extensively in image processing in recent years. Joint sparse representation is applied in dual-band infrared dim target detection in this paper. Firstly, according to the characters of dim targets in dual-band infrared images, 2-dimension Gaussian intensity model was used to construct target dictionary, then the dictionary was classified into different sub-classes according to different positions of Gaussian function's center point in image block; The fact that dual-band small targets detection can use the same dictionary and the sparsity doesn't lie in atom-level but in sub-class level was utilized, hence the detection of targets in dual-band infrared images was converted to be a joint dynamic sparse representation problem. And the dynamic active sets were used to describe the sparse constraint of coefficients. Two modified sparsity concentration index (SCI) criteria was proposed to evaluate whether targets exist in the images. In experiments, it shows that the proposed algorithm can achieve better detecting performance and dual-band detection is much more robust to noise compared with single-band detection. Moreover, the proposed method can be expanded to multi-spectrum small target detection.

Adaptive coded aperture imaging in the infrared: towards a practical implementation

NASA Astrophysics Data System (ADS)

Slinger, Chris W.; Gilholm, Kevin; Gordon, Neil; McNie, Mark; Payne, Doug; Ridley, Kevin; Strens, Malcolm; Todd, Mike; De Villiers, Geoff; Watson, Philip; Wilson, Rebecca; Dyer, Gavin; Eismann, Mike; Meola, Joe; Rogers, Stanley

2008-08-01

An earlier paper [1] discussed the merits of adaptive coded apertures for use as lensless imaging systems in the thermal infrared and visible. It was shown how diffractive (rather than the more conventional geometric) coding could be used, and that 2D intensity measurements from multiple mask patterns could be combined and decoded to yield enhanced imagery. Initial experimental results in the visible band were presented. Unfortunately, radiosity calculations, also presented in that paper, indicated that the signal to noise performance of systems using this approach was likely to be compromised, especially in the infrared. This paper will discuss how such limitations can be overcome, and some of the tradeoffs involved. Experimental results showing tracking and imaging performance of these modified, diffractive, adaptive coded aperture systems in the visible and infrared will be presented. The subpixel imaging and tracking performance is compared to that of conventional imaging systems and shown to be superior. System size, weight and cost calculations indicate that the coded aperture approach, employing novel photonic MOEMS micro-shutter architectures, has significant merits for a given level of performance in the MWIR when compared to more conventional imaging approaches.

Design of crossed-mirror array to form floating 3D LED signs

NASA Astrophysics Data System (ADS)

Yamamoto, Hirotsugu; Bando, Hiroki; Kujime, Ryousuke; Suyama, Shiro

2012-03-01

3D representation of digital signage improves its significance and rapid notification of important points. Our goal is to realize floating 3D LED signs. The problem is there is no sufficient device to form floating 3D images from LEDs. LED lamp size is around 1 cm including wiring and substrates. Such large pitch increases display size and sometimes spoils image quality. The purpose of this paper is to develop optical device to meet the three requirements and to demonstrate floating 3D arrays of LEDs. We analytically investigate image formation by a crossed mirror structure with aerial aperture, called CMA (crossed-mirror array). CMA contains dihedral corner reflectors at each aperture. After double reflection, light rays emitted from an LED will converge into the corresponding image point. We have fabricated CMA for 3D array of LEDs. One CMA unit contains 20 x 20 apertures that are located diagonally. Floating image of LEDs was formed in wide range of incident angle. The image size of focused beam agreed to the apparent aperture size. When LEDs were located three-dimensionally (LEDs in three depths), the focused distances were the same as the distance between the real LED and the CMA.

Mobile, hybrid Compton/coded aperture imaging for detection, identification and localization of gamma-ray sources at stand-off distances

NASA Astrophysics Data System (ADS)

Tornga, Shawn R.

The Stand-off Radiation Detection System (SORDS) program is an Advanced Technology Demonstration (ATD) project through the Department of Homeland Security's Domestic Nuclear Detection Office (DNDO) with the goal of detection, identification and localization of weak radiological sources in the presence of large dynamic backgrounds. The Raytheon-SORDS Tri-Modal Imager (TMI) is a mobile truck-based, hybrid gamma-ray imaging system able to quickly detect, identify and localize, radiation sources at standoff distances through improved sensitivity while minimizing the false alarm rate. Reconstruction of gamma-ray sources is performed using a combination of two imaging modalities; coded aperture and Compton scatter imaging. The TMI consists of 35 sodium iodide (NaI) crystals 5x5x2 in3 each, arranged in a random coded aperture mask array (CA), followed by 30 position sensitive NaI bars each 24x2.5x3 in3 called the detection array (DA). The CA array acts as both a coded aperture mask and scattering detector for Compton events. The large-area DA array acts as a collection detector for both Compton scattered events and coded aperture events. In this thesis, developed coded aperture, Compton and hybrid imaging algorithms will be described along with their performance. It will be shown that multiple imaging modalities can be fused to improve detection sensitivity over a broader energy range than either alone. Since the TMI is a moving system, peripheral data, such as a Global Positioning System (GPS) and Inertial Navigation System (INS) must also be incorporated. A method of adapting static imaging algorithms to a moving platform has been developed. Also, algorithms were developed in parallel with detector hardware, through the use of extensive simulations performed with the Geometry and Tracking Toolkit v4 (GEANT4). Simulations have been well validated against measured data. Results of image reconstruction algorithms at various speeds and distances will be presented as well as localization capability. Utilizing imaging information will show signal-to-noise gains over spectroscopic algorithms alone.

TRIPPy: Python-based Trailed Source Photometry

NASA Astrophysics Data System (ADS)

Fraser, Wesley C.; Alexandersen, Mike; Schwamb, Megan E.; Marsset, Michael E.; Pike, Rosemary E.; Kavelaars, JJ; Bannister, Michele T.; Benecchi, Susan; Delsanti, Audrey

2016-05-01

TRIPPy (TRailed Image Photometry in Python) uses a pill-shaped aperture, a rectangle described by three parameters (trail length, angle, and radius) to improve photometry of moving sources over that done with circular apertures. It can generate accurate model and trailed point-spread functions from stationary background sources in sidereally tracked images. Appropriate aperture correction provides accurate, unbiased flux measurement. TRIPPy requires numpy, scipy, matplotlib, Astropy (ascl:1304.002), and stsci.numdisplay; emcee (ascl:1303.002) and SExtractor (ascl:1010.064) are optional.

Simulation of Locking Space Truss Deployments for a Large Deployable Sparse Aperture Reflector

DTIC Science & Technology

2015-03-01

Dr. Alan Jennings, for his unending patience with my struggles through this entire process . Without his expertise, guidance, and trust I would have...engineer since they are not automatically meshed. Fortunately, the mesh process is quite swift. Figure 13 shows both a linear hexahedral element as well...less than that of the serial process . Therefore, COMSOL’s partially parallelized algorithms will not be sped up as a function of cores added and is

A surgical confocal microlaparoscope for real-time optical biopsies

NASA Astrophysics Data System (ADS)

Tanbakuchi, Anthony Amir

The first real-time fluorescence confocal microlaparoscope has been developed that provides instant in vivo cellular images, comparable to those provided by histology, through a nondestructive procedure. The device includes an integrated contrast agent delivery mechanism and a computerized depth scan system. The instrument uses a fiber bundle to relay the image plane of a slit-scan confocal microlaparoscope into tissue. The confocal laparoscope was used to image the ovaries of twenty-one patients in vivo using fluorescein sodium and acridine orange as the fluorescent contrast agents. The results indicate that the device is safe and functions as designed. A Monte Carlo model was developed to characterize the system performance in a scattering media representative of human tissues. The results indicate that a slit aperture has limited ability to image below the surface of tissue. In contrast, the results show that multi-pinhole apertures such as a Nipkow disk or a linear pinhole array can achieve nearly the same depth performance as a single pinhole aperture. The model was used to determine the optimal aperture spacing for the multi-pinhole apertures. The confocal microlaparoscope represents a new type of in vivo imaging device. With its ability to image cellular details in real time, it has the potential to aid in the early diagnosis of cancer. Initially, the device may be used to locate unusual regions for guided biopsies. In the long term, the device may be able to supplant traditional biopsies and allow the surgeon to identify early stage cancer in vivo.

First video rate imagery from a 32-channel 22-GHz aperture synthesis passive millimetre wave imager

NASA Astrophysics Data System (ADS)

Salmon, Neil A.; Macpherson, Rod; Harvey, Andy; Hall, Peter; Hayward, Steve; Wilkinson, Peter; Taylor, Chris

2011-11-01

The first video rate imagery from a proof-of-concept 32-channel 22 GHz aperture synthesis imager is reported. This imager has been brought into operation over the first half of year 2011. Receiver noise temperatures have been measured to be ~453 K, close to original specifications, and the measured radiometric sensitivity agrees with the theoretical predictions for aperture synthesis imagers (2 K for a 40 ms integration time). The short term (few seconds) magnitude stability in the cross-correlations expressed as a fraction was measured to have a mean of 3.45×10-4 with a standard deviation of ~2.30×10-4, whilst the figure for the phase was found to have a mean of essentially zero with a standard deviation of 0.0181°. The susceptibility of the system to aliasing for point sources in the scene was examined and found to be well understood. The system was calibrated and security-relevant indoor near-field and out-door far-field imagery was created, at frame rates ranging from 1 to 200 frames per second. The results prove that an aperture synthesis imager can generate imagery in the near-field regime, successfully coping with the curved wave-fronts. The original objective of the project, to deliver a Technology Readiness Level (TRL) 4 laboratory demonstrator for aperture synthesis passive millimetre wave (PMMW) imaging, has been achieved. The project was co-funded by the Technology Strategy Board and the Royal Society of the United Kingdom.

Preliminary study of synthetic aperture tissue harmonic imaging on in-vivo data

NASA Astrophysics Data System (ADS)

Rasmussen, Joachim H.; Hemmsen, Martin C.; Madsen, Signe S.; Hansen, Peter M.; Nielsen, Michael B.; Jensen, Jørgen A.

2013-03-01

A method for synthetic aperture tissue harmonic imaging is investigated. It combines synthetic aperture sequen- tial beamforming (SASB) with tissue harmonic imaging (THI) to produce an increased and more uniform spatial resolution and improved side lobe reduction compared to conventional B-mode imaging. Synthetic aperture sequential beamforming tissue harmonic imaging (SASB-THI) was implemented on a commercially available BK 2202 Pro Focus UltraView ultrasound system and compared to dynamic receive focused tissue harmonic imag- ing (DRF-THI) in clinical scans. The scan sequence that was implemented on the UltraView system acquires both SASB-THI and DRF-THI simultaneously. Twenty-four simultaneously acquired video sequences of in-vivo abdominal SASB-THI and DRF-THI scans on 3 volunteers of 4 different sections of liver and kidney tissues were created. Videos of the in-vivo scans were presented in double blinded studies to two radiologists for image quality performance scoring. Limitations to the systems transmit stage prevented user defined transmit apodization to be applied. Field II simulations showed that side lobes in SASB could be improved by using Hanning transmit apodization. Results from the image quality study show, that in the current configuration on the UltraView system, where no transmit apodization was applied, SASB-THI and DRF-THI produced equally good images. It is expected that given the use of transmit apodization, SASB-THI could be further improved.

Medicine, material science and security: the versatility of the coded-aperture approach.

PubMed

Munro, P R T; Endrizzi, M; Diemoz, P C; Hagen, C K; Szafraniec, M B; Millard, T P; Zapata, C E; Speller, R D; Olivo, A

2014-03-06

The principal limitation to the widespread deployment of X-ray phase imaging in a variety of applications is probably versatility. A versatile X-ray phase imaging system must be able to work with polychromatic and non-microfocus sources (for example, those currently used in medical and industrial applications), have physical dimensions sufficiently large to accommodate samples of interest, be insensitive to environmental disturbances (such as vibrations and temperature variations), require only simple system set-up and maintenance, and be able to perform quantitative imaging. The coded-aperture technique, based upon the edge illumination principle, satisfies each of these criteria. To date, we have applied the technique to mammography, materials science, small-animal imaging, non-destructive testing and security. In this paper, we outline the theory of coded-aperture phase imaging and show an example of how the technique may be applied to imaging samples with a practically important scale.

Accelerated High-Dimensional MR Imaging with Sparse Sampling Using Low-Rank Tensors

PubMed Central

He, Jingfei; Liu, Qiegen; Christodoulou, Anthony G.; Ma, Chao; Lam, Fan

2017-01-01

High-dimensional MR imaging often requires long data acquisition time, thereby limiting its practical applications. This paper presents a low-rank tensor based method for accelerated high-dimensional MR imaging using sparse sampling. This method represents high-dimensional images as low-rank tensors (or partially separable functions) and uses this mathematical structure for sparse sampling of the data space and for image reconstruction from highly undersampled data. More specifically, the proposed method acquires two datasets with complementary sampling patterns, one for subspace estimation and the other for image reconstruction; image reconstruction from highly undersampled data is accomplished by fitting the measured data with a sparsity constraint on the core tensor and a group sparsity constraint on the spatial coefficients jointly using the alternating direction method of multipliers. The usefulness of the proposed method is demonstrated in MRI applications; it may also have applications beyond MRI. PMID:27093543

Infrared and visible image fusion method based on saliency detection in sparse domain

NASA Astrophysics Data System (ADS)

Liu, C. H.; Qi, Y.; Ding, W. R.

2017-06-01

Infrared and visible image fusion is a key problem in the field of multi-sensor image fusion. To better preserve the significant information of the infrared and visible images in the final fused image, the saliency maps of the source images is introduced into the fusion procedure. Firstly, under the framework of the joint sparse representation (JSR) model, the global and local saliency maps of the source images are obtained based on sparse coefficients. Then, a saliency detection model is proposed, which combines the global and local saliency maps to generate an integrated saliency map. Finally, a weighted fusion algorithm based on the integrated saliency map is developed to achieve the fusion progress. The experimental results show that our method is superior to the state-of-the-art methods in terms of several universal quality evaluation indexes, as well as in the visual quality.

Towards breaking the spatial resolution barriers: An optical flow and super-resolution approach for sea ice motion estimation

NASA Astrophysics Data System (ADS)

Petrou, Zisis I.; Xian, Yang; Tian, YingLi

2018-04-01

Estimation of sea ice motion at fine scales is important for a number of regional and local level applications, including modeling of sea ice distribution, ocean-atmosphere and climate dynamics, as well as safe navigation and sea operations. In this study, we propose an optical flow and super-resolution approach to accurately estimate motion from remote sensing images at a higher spatial resolution than the original data. First, an external example learning-based super-resolution method is applied on the original images to generate higher resolution versions. Then, an optical flow approach is applied on the higher resolution images, identifying sparse correspondences and interpolating them to extract a dense motion vector field with continuous values and subpixel accuracies. Our proposed approach is successfully evaluated on passive microwave, optical, and Synthetic Aperture Radar data, proving appropriate for multi-sensor applications and different spatial resolutions. The approach estimates motion with similar or higher accuracy than the original data, while increasing the spatial resolution of up to eight times. In addition, the adopted optical flow component outperforms a state-of-the-art pattern matching method. Overall, the proposed approach results in accurate motion vectors with unprecedented spatial resolutions of up to 1.5 km for passive microwave data covering the entire Arctic and 20 m for radar data, and proves promising for numerous scientific and operational applications.

Coarse Resolution SAR Imagery to Support Flood Inundation Models in Near Real Time

NASA Astrophysics Data System (ADS)

Di Baldassarre, Giuliano; Schumann, Guy; Brandimarte, Luigia; Bates, Paul

2009-11-01

In recent years, the availability of new emerging data (e.g. remote sensing, intelligent wireless sensors, etc) has led to a sudden shift from a data-sparse to a data-rich environment for hydrological and hydraulic modelling. Furthermore, the increased socioeconomic relevance of river flood studies has motivated the development of complex methodologies for the simulation of the hydraulic behaviour of river systems. In this context, this study aims at assessing the capability of coarse resolution SAR (Synthetic Aperture Radar) imagery to support and quickly validate flood inundation models in near real time. A hydraulic model of a 98km reach of the River Po (Italy), previously calibrated on a high-magnitude flood event with extensive and high quality field data, is tested using a SAR flood image, acquired and processed in near real time, during the June 2008 low-magnitude event. Specifically, the image is an acquisition by the ENVISAT-ASAR sensor in wide swath mode and has been provided through ESA (European Space Agency) Fast Registration system at no cost 24 hours after the acquisition. The study shows that the SAR image enables validation and improvement of the model in a time shorter than the flood travel time. This increases the reliability of model predictions (e.g. water elevation and inundation width along the river reach) and, consequently, assists flood management authorities in undertaking the necessary prevention activities.

Microwave and Millimeter Wave Imaging of the Space Shuttle External Fuel Tank Spray on Foam Insulation (SOFI) Using Synthetic Aperture Focusing Techniques (SAFT)

NASA Technical Reports Server (NTRS)

Case, J. T.; Robbins, J.; Kharkovshy, S.; Hepburn, F. L.; Zoughi, R.

2005-01-01

The Space Shuttle Columbia's catastrophic failure is thought to have been caused by a dislodged piece of external tank SOFI (Spray On Foam Insulation) striking the left wing of the orbiter causing significant damage to some of the reinforced carbodcarbon leading edge wing panels. Microwave and millimeter wave nondestructive evaluation methods, have shown great potential for inspecting the SOFI for the purpose of detecting anomalies such as small voids that may cause separation of the foam from the external tank during the launch. These methods are capable of producing relatively high-resolution images of the interior of SOH particularly when advanced imaging algorithms are incorporated into the overall system. To this end, synthetic aperture focusing techniques are being deveioped for this purpose. These iechniqiies pradiice high-resolution images that are independent of the distance of the imaging probe to the SOFI with spatial resolution in the order of the half size of imaging probe aperture. At microwave and millimeter wave frequencies these apertures are inherently small resulting in high-resolution images. This paper provides the results of this investigation using 2D and 3D SAF based methods and holography. The attributes of these methods and a full discussion of the results will also be provided.

Three-Dimensional Microwave Imaging for Indoor Environments

NASA Astrophysics Data System (ADS)

Scott, Simon

Microwave imaging involves the use of antenna arrays, operating at microwave and millimeter-wave frequencies, for capturing images of real-world objects. Typically, one or more antennas in the array illuminate the scene with a radio-frequency (RF) signal. Part of this signal reflects back to the other antennas, which record both the amplitude and phase of the reflected signal. These reflected RF signals are then processed to form an image of the scene. This work focuses on using planar antenna arrays, operating between 17 and 26 GHz, to capture three-dimensional images of people and other objects inside a room. Such an imaging system enables applications such as indoor positioning and tracking, health monitoring and hand gesture recognition. Microwave imaging techniques based on beamforming cannot be used for indoor imaging, as most objects lie within the array near-field. Therefore, the range-migration algorithm (RMA) is used instead, as it compensates for the curvature of the reflected wavefronts, hence enabling near-field imaging. It is also based on fast-Fourier transforms and is therefore computationally efficient. A number of novel RMA variants were developed to support a wider variety of antenna array configurations, as well as to generate 3-D velocity maps of objects moving around a room. The choice of antenna array configuration, microwave transceiver components and transmit power has a significant effect on both the energy consumed by the imaging system and the quality of the resulting images. A generic microwave imaging testbed was therefore built to characterize the effect of these antenna array parameters on image quality in the 20 GHz band. All variants of the RMA were compared and found to produce good quality three-dimensional images with transmit power levels as low as 1 muW. With an array size of 80x80 antennas, most of the imaging algorithms were able to image objects at 0.5 m range with 12.5 mm resolution, although some were only able to achieve 20 mm resolution. Increasing the size of the antenna array further results in a proportional improvement in image resolution and image SNR, until the resolution reaches the half-wavelength limit. While microwave imaging is not a new technology, it has seen little commercial success due to the cost and power consumption of the large number of antennas and radio transceivers required to build such a system. The cost and power consumption can be reduced by using low-power and low-cost components in both the transmit and receive RF chains, even if these components have poor noise figures. Alternatively, the cost and power consumption can be reduced by decreasing the number of antennas in the array, while keeping the aperture constant. This reduction in antenna count is achieved by randomly depopulating the array, resulting in a sparse antenna array. A novel compressive sensing algorithm, coupled with the wavelet transform, is used to process the samples collected by the sparse array and form a 3-D image of the scene. This algorithm works well for antenna arrays that are up to 96% sparse, equating to a 25 times reduction in the number of required antennas. For microwave imaging to be useful, it needs to capture images of the scene in real time. The architecture of a system capable of capturing real-time 3-D microwave images is therefore designed. The system consists of a modular antenna array, constructed by plugging RF daughtercards into a carrier board. Each daughtercard is a self-contained radio system, containing an antenna, RF transceiver baseband signal chain, and analog-to-digital converters. A small number of daughtercards have been built, and proven to be suitable for real-time microwave imaging. By arranging these daughtercards in different ways, any antenna array pattern can be built. This architecture allows real-time microwave imaging systems to be rapidly prototyped, while still being able to generate images at video frame rates.

Analysis and design of wedge projection display system based on ray retracing method.

PubMed

Lee, Chang-Kun; Lee, Taewon; Sung, Hyunsik; Min, Sung-Wook

2013-06-10

A design method for the wedge projection display system based on the ray retracing method is proposed. To analyze the principle of image formation on the inclined surface of the wedge-shaped waveguide, the bundle of rays is retraced from an imaging point on the inclined surface to the aperture of the waveguide. In consequence of ray retracing, we obtain the incident conditions of the ray, such as the position and the angle at the aperture, which provide clues for image formation. To illuminate the image formation, the concept of the equivalent imaging point is proposed, which is the intersection where the incident rays are extended over the space regardless of the refraction and reflection in the waveguide. Since the initial value of the rays arriving at the equivalent imaging point corresponds to that of the rays converging into the imaging point on the inclined surface, the image formation can be visualized by calculating the equivalent imaging point over the entire inclined surface. Then, we can find image characteristics, such as their size and position, and their degree of blur--by analyzing the distribution of the equivalent imaging point--and design the optimized wedge projection system by attaching the prism structure at the aperture. The simulation results show the feasibility of the ray retracing analysis and characterize the numerical relation between the waveguide parameters and the aperture structure for on-axis configuration. The experimental results verify the designed system based on the proposed method.

Multi scales based sparse matrix spectral clustering image segmentation

NASA Astrophysics Data System (ADS)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

Variation of ultrasound image lateral spectrum with assumed speed of sound and true scatterer density.

PubMed

Gyöngy, Miklós; Kollár, Sára

2015-02-01

One method of estimating sound speed in diagnostic ultrasound imaging consists of choosing the speed of sound that generates the sharpest image, as evaluated by the lateral frequency spectrum of the squared B-mode image. In the current work, simulated and experimental data on a typical (47 mm aperture, 3.3-10.0 MHz response) linear array transducer are used to investigate the accuracy of this method. A range of candidate speeds of sound (1240-1740 m/s) was used, with a true speed of sound of 1490 m/s in simulations and 1488 m/s in experiments. Simulations of single point scatterers and two interfering point scatterers at various locations with respect to each other gave estimate errors of 0.0-2.0%. Simulations and experiments of scatterer distributions with a mean scatterer spacing of at least 0.5 mm gave estimate errors of 0.1-4.0%. In the case of lower scatterer spacing, the speed of sound estimates become unreliable due to a decrease in contrast of the sharpness measure between different candidate speeds of sound. This suggests that in estimating speed of sound in tissue, the region of interest should be dominated by a few, sparsely spaced scatterers. Conversely, the decreasing sensitivity of the sharpness measure to speed of sound errors for higher scatterer concentrations suggests a potential method for estimating mean scatterer spacing. Copyright © 2014 Elsevier B.V. All rights reserved.

RESOLVING THE PLANET-HOSTING INNER REGIONS OF THE LkCa 15 DISK

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

Thalmann, C.; Garufi, A.; Quanz, S. P.

2016-09-10

LkCa 15 hosts a pre-transitional disk as well as at least one accreting protoplanet orbiting in its gap. Previous disk observations have focused mainly on the outer disk, which is cleared inward of ∼50 au. The planet candidates, on the other hand, reside at orbital radii around 15 au, where disk observations have been unreliable until recently. Here, we present new J -band imaging polarimetry of LkCa 15 with SPHERE IRDIS, yielding the most accurate and detailed scattered-light images of the disk to date down to the planet-hosting inner regions. We find what appear to be persistent asymmetric structures inmore » the scattering material at the location of the planet candidates, which could be responsible at least for parts of the signals measured with sparse-aperture masking. These images further allow us to trace the gap edge in scattered light at all position angles and search the inner and outer disks for morphological substructure. The outer disk appears smooth with slight azimuthal variations in polarized surface brightness, which may be due to shadowing from the inner disk or a two-peaked polarized phase function. We find that the near-side gap edge revealed by polarimetry matches the sharp crescent seen in previous ADI imaging very well. Finally, the ratio of polarized disk to stellar flux is more than six times larger in the J -band than in the RI bands.« less

Sparsity-promoting orthogonal dictionary updating for image reconstruction from highly undersampled magnetic resonance data.

PubMed

Huang, Jinhong; Guo, Li; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu

2015-07-21

Image reconstruction from undersampled k-space data accelerates magnetic resonance imaging (MRI) by exploiting image sparseness in certain transform domains. Employing image patch representation over a learned dictionary has the advantage of being adaptive to local image structures and thus can better sparsify images than using fixed transforms (e.g. wavelets and total variations). Dictionary learning methods have recently been introduced to MRI reconstruction, and these methods demonstrate significantly reduced reconstruction errors compared to sparse MRI reconstruction using fixed transforms. However, the synthesis sparse coding problem in dictionary learning is NP-hard and computationally expensive. In this paper, we present a novel sparsity-promoting orthogonal dictionary updating method for efficient image reconstruction from highly undersampled MRI data. The orthogonality imposed on the learned dictionary enables the minimization problem in the reconstruction to be solved by an efficient optimization algorithm which alternately updates representation coefficients, orthogonal dictionary, and missing k-space data. Moreover, both sparsity level and sparse representation contribution using updated dictionaries gradually increase during iterations to recover more details, assuming the progressively improved quality of the dictionary. Simulation and real data experimental results both demonstrate that the proposed method is approximately 10 to 100 times faster than the K-SVD-based dictionary learning MRI method and simultaneously improves reconstruction accuracy.

Schlieren System and method for moving objects

NASA Technical Reports Server (NTRS)

Weinstein, Leonard M. (Inventor)

1995-01-01

A system and method are provided for recording density changes in a flow field surrounding a moving object. A mask having an aperture for regulating the passage of images is placed in front of an image recording medium. An optical system is placed in front of the mask. A transition having a light field-of-view and a dark field-of-view is located beyond the test object. The optical system focuses an image of the transition at the mask such that the aperture causes a band of light to be defined on the image recording medium. The optical system further focuses an image of the object through the aperture of the mask so that the image of the object appears on the image recording medium. Relative motion is minimized between the mask and the transition. Relative motion is also minimized between the image recording medium and the image of the object. In this way, the image of the object and density changes in a flow field surrounding the object are recorded on the image recording medium when the object crosses the transition in front of the optical system.

Ionospheric effects on synthetic aperture radar at VHF

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

Fitzgerald, T.J.

1997-02-01

Synthetic aperture radars (SAR) operated from airplanes have been used at VHF because of their enhanced foliage and ground penetration compared to radars operated at UHF. A satellite-borne VHF SAR would have considerable utility but in order to operate with high resolution it would have to use both a large relative bandwidth and a large aperture. The presence of the ionosphere in the propagation path of the radar will cause a deterioration of the imaging because of dispersion over the bandwidth and group path changes in the imaged area over the collection aperture. In this paper we present calculations ofmore » the effects of a deterministic ionosphere on SAR imaging for a radar operated with a 100 MHz bandwidth centered at 250 MHz and over an angular aperture of 23{degrees}. The ionosphere induces a point spread function with an approximate half-width of 150 m in the slant-range direction and of 25 m in the cross-range direction compared to the nominal resolution of 1.5 m in both directions.« less

Multiplexed two in-line holographic recordings for flow characterization in a flexible vessel

NASA Astrophysics Data System (ADS)

Lobera, Julia; Palero, Virginia; Roche, Eva M.; Gómez Climente, Marina; López Torres, Ana M.; Andrés, Nieves; Arroyo, M. Pilar

2017-06-01

The simultaneous presence of the real and virtual images in the hologram reconstruction is inherent in the in-line holography. This drawback can be overcome with a shifted knife-edge aperture at the focal plane of the imaging lens. The shifted aperture DIH produces holograms where the real and virtual images are completely separated. In this paper we propose a modification of the shifted aperture DIH that allows recording two holograms simultaneously using one camera, while retaining the simplicity of the in-line configuration and the advantage of the shifted-aperture strategy. As in typical stereoscopy, the advantage of this configuration is limited by the angle between the two illuminating beams, and therefore the aperture size. Some improvement on the out-of-plane resolution can be expected from a combined analysis of the multiplexed holograms. In order to compare this technique with other in-line holographic configurations, several experiments have been performed to study the spatial resolution along the optical axis. The capabilities of the different techniques for characterizing the flow in a flexible and transparent model of a carotid bifurcation are also investigated.

Automatic correction of intensity nonuniformity from sparseness of gradient distribution in medical images.

PubMed

Zheng, Yuanjie; Grossman, Murray; Awate, Suyash P; Gee, James C

2009-01-01

We propose to use the sparseness property of the gradient probability distribution to estimate the intensity nonuniformity in medical images, resulting in two novel automatic methods: a non-parametric method and a parametric method. Our methods are easy to implement because they both solve an iteratively re-weighted least squares problem. They are remarkably accurate as shown by our experiments on images of different imaged objects and from different imaging modalities.

Automatic Correction of Intensity Nonuniformity from Sparseness of Gradient Distribution in Medical Images

PubMed Central

Zheng, Yuanjie; Grossman, Murray; Awate, Suyash P.; Gee, James C.

2013-01-01

We propose to use the sparseness property of the gradient probability distribution to estimate the intensity nonuniformity in medical images, resulting in two novel automatic methods: a non-parametric method and a parametric method. Our methods are easy to implement because they both solve an iteratively re-weighted least squares problem. They are remarkably accurate as shown by our experiments on images of different imaged objects and from different imaging modalities. PMID:20426191

Multi-frame linear regressive filter for the measurement of infrared pixel spatial response and MTF from sparse data.

PubMed

Huard, Edouard; Derelle, Sophie; Jaeck, Julien; Nghiem, Jean; Haïdar, Riad; Primot, Jérôme

2018-03-05

A challenging point in the prediction of the image quality of infrared imaging systems is the evaluation of the detector modulation transfer function (MTF). In this paper, we present a linear method to get a 2D continuous MTF from sparse spectral data. Within the method, an object with a predictable sparse spatial spectrum is imaged by the focal plane array. The sparse data is then treated to return the 2D continuous MTF with the hypothesis that all the pixels have an identical spatial response. The linearity of the treatment is a key point to estimate directly the error bars of the resulting detector MTF. The test bench will be presented along with measurement tests on a 25 μm pitch InGaAs detector.

ExSPO: A Discovery Class Apodized Square Aperture (ASA) Expo-Planet Imaging Space Telescope Concept

NASA Technical Reports Server (NTRS)

Gezari, D.; Harwit, M.; Lyon, R.; Melnick, G.; Papaliolos, G.; Ridgeway, S.; Woodruff, R.; Nisenson, P.; Oegerle, William (Technical Monitor)

2002-01-01

ExSPO is a Discovery Class (approx. 4 meter) apodized square aperture (ASA) space telescope mission designed for direct imaging of extrasolar Earth-like planets, as a precursor to TPF. The ASA telescope concept, instrument design, capabilities, mission plan and science goals are described.

Hyperspectral Image Classification via Kernel Sparse Representation

DTIC Science & Technology

2013-01-01

classification algorithms. Moreover, the spatial coherency across neighboring pixels is also incorporated through a kernelized joint sparsity model , where...joint sparsity model , where all of the pixels within a small neighborhood are jointly represented in the feature space by selecting a few common training...hyperspectral imagery, joint spar- sity model , kernel methods, sparse representation. I. INTRODUCTION HYPERSPECTRAL imaging sensors capture images

A coarse-to-fine approach for medical hyperspectral image classification with sparse representation

NASA Astrophysics Data System (ADS)

Chang, Lan; Zhang, Mengmeng; Li, Wei

2017-10-01

A coarse-to-fine approach with sparse representation is proposed for medical hyperspectral image classification in this work. Segmentation technique with different scales is employed to exploit edges of the input image, where coarse super-pixel patches provide global classification information while fine ones further provide detail information. Different from common RGB image, hyperspectral image has multi bands to adjust the cluster center with more high precision. After segmentation, each super pixel is classified by recently-developed sparse representation-based classification (SRC), which assigns label for testing samples in one local patch by means of sparse linear combination of all the training samples. Furthermore, segmentation with multiple scales is employed because single scale is not suitable for complicate distribution of medical hyperspectral imagery. Finally, classification results for different sizes of super pixel are fused by some fusion strategy, offering at least two benefits: (1) the final result is obviously superior to that of segmentation with single scale, and (2) the fusion process significantly simplifies the choice of scales. Experimental results using real medical hyperspectral images demonstrate that the proposed method outperforms the state-of-the-art SRC.

Adaptive structured dictionary learning for image fusion based on group-sparse-representation

NASA Astrophysics Data System (ADS)

Yang, Jiajie; Sun, Bin; Luo, Chengwei; Wu, Yuzhong; Xu, Limei

2018-04-01

Dictionary learning is the key process of sparse representation which is one of the most widely used image representation theories in image fusion. The existing dictionary learning method does not use the group structure information and the sparse coefficients well. In this paper, we propose a new adaptive structured dictionary learning algorithm and a l1-norm maximum fusion rule that innovatively utilizes grouped sparse coefficients to merge the images. In the dictionary learning algorithm, we do not need prior knowledge about any group structure of the dictionary. By using the characteristics of the dictionary in expressing the signal, our algorithm can automatically find the desired potential structure information that hidden in the dictionary. The fusion rule takes the physical meaning of the group structure dictionary, and makes activity-level judgement on the structure information when the images are being merged. Therefore, the fused image can retain more significant information. Comparisons have been made with several state-of-the-art dictionary learning methods and fusion rules. The experimental results demonstrate that, the dictionary learning algorithm and the fusion rule both outperform others in terms of several objective evaluation metrics.

Information extraction and transmission techniques for spaceborne synthetic aperture radar images

NASA Technical Reports Server (NTRS)

Frost, V. S.; Yurovsky, L.; Watson, E.; Townsend, K.; Gardner, S.; Boberg, D.; Watson, J.; Minden, G. J.; Shanmugan, K. S.

1984-01-01

Information extraction and transmission techniques for synthetic aperture radar (SAR) imagery were investigated. Four interrelated problems were addressed. An optimal tonal SAR image classification algorithm was developed and evaluated. A data compression technique was developed for SAR imagery which is simple and provides a 5:1 compression with acceptable image quality. An optimal textural edge detector was developed. Several SAR image enhancement algorithms have been proposed. The effectiveness of each algorithm was compared quantitatively.

A data compression technique for synthetic aperture radar images

NASA Technical Reports Server (NTRS)

Frost, V. S.; Minden, G. J.

1986-01-01

A data compression technique is developed for synthetic aperture radar (SAR) imagery. The technique is based on an SAR image model and is designed to preserve the local statistics in the image by an adaptive variable rate modification of block truncation coding (BTC). A data rate of approximately 1.6 bit/pixel is achieved with the technique while maintaining the image quality and cultural (pointlike) targets. The algorithm requires no large data storage and is computationally simple.

Accurate sparse-projection image reconstruction via nonlocal TV regularization.

PubMed

Zhang, Yi; Zhang, Weihua; Zhou, Jiliu

2014-01-01

Sparse-projection image reconstruction is a useful approach to lower the radiation dose; however, the incompleteness of projection data will cause degeneration of imaging quality. As a typical compressive sensing method, total variation has obtained great attention on this problem. Suffering from the theoretical imperfection, total variation will produce blocky effect on smooth regions and blur edges. To overcome this problem, in this paper, we introduce the nonlocal total variation into sparse-projection image reconstruction and formulate the minimization problem with new nonlocal total variation norm. The qualitative and quantitative analyses of numerical as well as clinical results demonstrate the validity of the proposed method. Comparing to other existing methods, our method more efficiently suppresses artifacts caused by low-rank reconstruction and reserves structure information better.

NIAC Phase II Orbiting Rainbows: Future Space Imaging with Granular Systems

NASA Technical Reports Server (NTRS)

Quadrelli, Marco B.; Basinger, Scott; Arumugam, Darmindra; Swartzlander, Grover

2017-01-01

Inspired by the light scattering and focusing properties of distributed optical assemblies in Nature, such as rainbows and aerosols, and by recent laboratory successes in optical trapping and manipulation, we propose a unique combination of space optics and autonomous robotic system technology, to enable a new vision of space system architecture with applications to ultra-lightweight space optics and, ultimately, in-situ space system fabrication. Typically, the cost of an optical system is driven by the size and mass of the primary aperture. The ideal system is a cloud of spatially disordered dust-like objects that can be optically manipulated: it is highly reconfigurable, fault-tolerant, and allows very large aperture sizes at low cost. This new concept is based on recent understandings in the physics of optical manipulation of small particles in the laboratory and the engineering of distributed ensembles of spacecraft swarms to shape an orbiting cloud of micron-sized objects. In the same way that optical tweezers have revolutionized micro- and nano-manipulation of objects, our breakthrough concept will enable new large scale NASA mission applications and develop new technology in the areas of Astrophysical Imaging Systems and Remote Sensing because the cloud can operate as an adaptive optical imaging sensor. While achieving the feasibility of constructing one single aperture out of the cloud is the main topic of this work, it is clear that multiple orbiting aerosol lenses could also combine their power to synthesize a much larger aperture in space to enable challenging goals such as exo-planet detection. Furthermore, this effort could establish feasibility of key issues related to material properties, remote manipulation, and autonomy characteristics of cloud in orbit. There are several types of endeavors (science missions) that could be enabled by this type of approach, i.e. it can enable new astrophysical imaging systems, exo-planet search, large apertures allow for unprecedented high resolution to discern continents and important features of other planets, hyperspectral imaging, adaptive systems, spectroscopy imaging through limb, and stable optical systems from Lagrange-points. Furthermore, future micro-miniaturization might hold promise of a further extension of our dust aperture concept to other more exciting smart dust concepts with other associated capabilities. Our objective in Phase II was to experimentally and numerically investigate how to optically manipulate and maintain the shape of an orbiting cloud of dust-like matter so that it can function as an adaptable ultra-lightweight surface. Our solution is based on the aperture being an engineered granular medium, instead of a conventional monolithic aperture. This allows building of apertures at a reduced cost, enables extremely fault-tolerant apertures that cannot otherwise be made, and directly enables classes of missions for exoplanet detection based on Fourier spectroscopy with tight angular resolution and innovative radar systems for remote sensing. In this task, we have examined the advanced feasibility of a crosscutting concept that contributes new technological approaches for space imaging systems, autonomous systems, and space applications of optical manipulation. The proposed investigation has matured the concept that we started in Phase I to TRL 3, identifying technology gaps and candidate system architectures for the space-borne cloud as an aperture.

Near-Space TOPSAR Large-Scene Full-Aperture Imaging Scheme Based on Two-Step Processing

PubMed Central

Zhang, Qianghui; Wu, Junjie; Li, Wenchao; Huang, Yulin; Yang, Jianyu; Yang, Haiguang

2016-01-01

Free of the constraints of orbit mechanisms, weather conditions and minimum antenna area, synthetic aperture radar (SAR) equipped on near-space platform is more suitable for sustained large-scene imaging compared with the spaceborne and airborne counterparts. Terrain observation by progressive scans (TOPS), which is a novel wide-swath imaging mode and allows the beam of SAR to scan along the azimuth, can reduce the time of echo acquisition for large scene. Thus, near-space TOPS-mode SAR (NS-TOPSAR) provides a new opportunity for sustained large-scene imaging. An efficient full-aperture imaging scheme for NS-TOPSAR is proposed in this paper. In this scheme, firstly, two-step processing (TSP) is adopted to eliminate the Doppler aliasing of the echo. Then, the data is focused in two-dimensional frequency domain (FD) based on Stolt interpolation. Finally, a modified TSP (MTSP) is performed to remove the azimuth aliasing. Simulations are presented to demonstrate the validity of the proposed imaging scheme for near-space large-scene imaging application. PMID:27472341

Apparatus and method to achieve high-resolution microscopy with non-diffracting or refracting radiation

DOEpatents

Tobin, Jr., Kenneth W.; Bingham, Philip R.; Hawari, Ayman I.

2012-11-06

An imaging system employing a coded aperture mask having multiple pinholes is provided. The coded aperture mask is placed at a radiation source to pass the radiation through. The radiation impinges on, and passes through an object, which alters the radiation by absorption and/or scattering. Upon passing through the object, the radiation is detected at a detector plane to form an encoded image, which includes information on the absorption and/or scattering caused by the material and structural attributes of the object. The encoded image is decoded to provide a reconstructed image of the object. Because the coded aperture mask includes multiple pinholes, the radiation intensity is greater than a comparable system employing a single pinhole, thereby enabling a higher resolution. Further, the decoding of the encoded image can be performed to generate multiple images of the object at different distances from the detector plane. Methods and programs for operating the imaging system are also disclosed.

Superresolving Black Hole Images with Full-Closure Sparse Modeling

NASA Astrophysics Data System (ADS)

Crowley, Chelsea; Akiyama, Kazunori; Fish, Vincent

2018-01-01

It is believed that almost all galaxies have black holes at their centers. Imaging a black hole is a primary objective to answer scientific questions relating to relativistic accretion and jet formation. The Event Horizon Telescope (EHT) is set to capture images of two nearby black holes, Sagittarius A* at the center of the Milky Way galaxy roughly 26,000 light years away and the other M87 which is in Virgo A, a large elliptical galaxy that is 50 million light years away. Sparse imaging techniques have shown great promise for reconstructing high-fidelity superresolved images of black holes from simulated data. Previous work has included the effects of atmospheric phase errors and thermal noise, but not systematic amplitude errors that arise due to miscalibration. We explore a full-closure imaging technique with sparse modeling that uses closure amplitudes and closure phases to improve the imaging process. This new technique can successfully handle data with systematic amplitude errors. Applying our technique to synthetic EHT data of M87, we find that full-closure sparse modeling can reconstruct images better than traditional methods and recover key structural information on the source, such as the shape and size of the predicted photon ring. These results suggest that our new approach will provide superior imaging performance for data from the EHT and other interferometric arrays.

Efficient image enhancement using sparse source separation in the Retinex theory

NASA Astrophysics Data System (ADS)

Yoon, Jongsu; Choi, Jangwon; Choe, Yoonsik

2017-11-01

Color constancy is the feature of the human vision system (HVS) that ensures the relative constancy of the perceived color of objects under varying illumination conditions. The Retinex theory of machine vision systems is based on the HVS. Among Retinex algorithms, the physics-based algorithms are efficient; however, they generally do not satisfy the local characteristics of the original Retinex theory because they eliminate global illumination from their optimization. We apply the sparse source separation technique to the Retinex theory to present a physics-based algorithm that satisfies the locality characteristic of the original Retinex theory. Previous Retinex algorithms have limited use in image enhancement because the total variation Retinex results in an overly enhanced image and the sparse source separation Retinex cannot completely restore the original image. In contrast, our proposed method preserves the image edge and can very nearly replicate the original image without any special operation.

Incoherent dictionary learning for reducing crosstalk noise in least-squares reverse time migration

NASA Astrophysics Data System (ADS)

Wu, Juan; Bai, Min

2018-05-01

We propose to apply a novel incoherent dictionary learning (IDL) algorithm for regularizing the least-squares inversion in seismic imaging. The IDL is proposed to overcome the drawback of traditional dictionary learning algorithm in losing partial texture information. Firstly, the noisy image is divided into overlapped image patches, and some random patches are extracted for dictionary learning. Then, we apply the IDL technology to minimize the coherency between atoms during dictionary learning. Finally, the sparse representation problem is solved by a sparse coding algorithm, and image is restored by those sparse coefficients. By reducing the correlation among atoms, it is possible to preserve most of the small-scale features in the image while removing much of the long-wavelength noise. The application of the IDL method to regularization of seismic images from least-squares reverse time migration shows successful performance.

The Research on Denoising of SAR Image Based on Improved K-SVD Algorithm

NASA Astrophysics Data System (ADS)

Tan, Linglong; Li, Changkai; Wang, Yueqin

2018-04-01

SAR images often receive noise interference in the process of acquisition and transmission, which can greatly reduce the quality of images and cause great difficulties for image processing. The existing complete DCT dictionary algorithm is fast in processing speed, but its denoising effect is poor. In this paper, the problem of poor denoising, proposed K-SVD (K-means and singular value decomposition) algorithm is applied to the image noise suppression. Firstly, the sparse dictionary structure is introduced in detail. The dictionary has a compact representation and can effectively train the image signal. Then, the sparse dictionary is trained by K-SVD algorithm according to the sparse representation of the dictionary. The algorithm has more advantages in high dimensional data processing. Experimental results show that the proposed algorithm can remove the speckle noise more effectively than the complete DCT dictionary and retain the edge details better.

Hard X-ray imaging from Explorer

NASA Technical Reports Server (NTRS)

Grindlay, J. E.; Murray, S. S.

1981-01-01

Coded aperture X-ray detectors were applied to obtain large increases in sensitivity as well as angular resolution. A hard X-ray coded aperture detector concept is described which enables very high sensitivity studies persistent hard X-ray sources and gamma ray bursts. Coded aperture imaging is employed so that approx. 2 min source locations can be derived within a 3 deg field of view. Gamma bursts were located initially to within approx. 2 deg and X-ray/hard X-ray spectra and timing, as well as precise locations, derived for possible burst afterglow emission. It is suggested that hard X-ray imaging should be conducted from an Explorer mission where long exposure times are possible.

Calibration of scintillation-light filters for neutron time-of-flight spectrometers at the National Ignition Facility.

PubMed

Sayre, D B; Barbosa, F; Caggiano, J A; DiPuccio, V N; Eckart, M J; Grim, G P; Hartouni, E P; Hatarik, R; Weber, F A

2016-11-01

Sixty-four neutral density filters constructed of metal plates with 88 apertures of varying diameter have been radiographed with a soft x-ray source and CCD camera at National Security Technologies, Livermore. An analysis of the radiographs fits the radial dependence of the apertures' image intensities to sigmoid functions, which can describe the rapidly decreasing intensity towards the apertures' edges. The fitted image intensities determine the relative attenuation value of each filter. Absolute attenuation values of several imaged filters, measured in situ during calibration experiments, normalize the relative quantities which are now used in analyses of neutron spectrometer data at the National Ignition Facility.

Sparse Adaptive Iteratively-Weighted Thresholding Algorithm (SAITA) for Lp-Regularization Using the Multiple Sub-Dictionary Representation

PubMed Central

Zhang, Jie; Fan, Shangang; Xiong, Jian; Cheng, Xiefeng; Sari, Hikmet; Adachi, Fumiyuki

2017-01-01

Both L1/2 and L2/3 are two typical non-convex regularizations of Lp (0

Sparse Adaptive Iteratively-Weighted Thresholding Algorithm (SAITA) for Lp-Regularization Using the Multiple Sub-Dictionary Representation.

PubMed

Li, Yunyi; Zhang, Jie; Fan, Shangang; Yang, Jie; Xiong, Jian; Cheng, Xiefeng; Sari, Hikmet; Adachi, Fumiyuki; Gui, Guan

2017-12-15

Both L 1/2 and L 2/3 are two typical non-convex regularizations of L p (0

Blind compressed sensing image reconstruction based on alternating direction method

NASA Astrophysics Data System (ADS)

Liu, Qinan; Guo, Shuxu

2018-04-01

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

Generating Artificial Reference Images for Open Loop Correlation Wavefront Sensors

NASA Astrophysics Data System (ADS)

Townson, M. J.; Love, G. D.; Saunter, C. D.

2018-05-01

Shack-Hartmann wavefront sensors for both solar and laser guide star adaptive optics (with elongated spots) need to observe extended objects. Correlation techniques have been successfully employed to measure the wavefront gradient in solar adaptive optics systems and have been proposed for laser guide star systems. In this paper we describe a method for synthesising reference images for correlation Shack-Hartmann wavefront sensors with a larger field of view than individual sub-apertures. We then show how these supersized reference images can increase the performance of correlation wavefront sensors in regimes where large relative shifts are induced between sub-apertures, such as those observed in open-loop wavefront sensors. The technique we describe requires no external knowledge outside of the wavefront-sensor images, making it available as an entirely "software" upgrade to an existing adaptive optics system. For solar adaptive optics we show the supersized reference images extend the magnitude of shifts which can be accurately measured from 12% to 50% of the field of view of a sub-aperture and in laser guide star wavefront sensors the magnitude of centroids that can be accurately measured is increased from 12% to 25% of the total field of view of the sub-aperture.

Carotid lesion characterization by synthetic-aperture-imaging techniques with multioffset ultrasonic probes

NASA Astrophysics Data System (ADS)

Capineri, Lorenzo; Castellini, Guido; Masotti, Leonardo F.; Rocchi, Santina

1992-06-01

This paper explores the applications of a high-resolution imaging technique to vascular ultrasound diagnosis, with emphasis on investigation of the carotid vessel. With the present diagnostic systems, it is difficult to measure quantitatively the extension of the lesions and to characterize the tissue; quantitative images require enough spatial resolution and dynamic to reveal fine high-risk pathologies. A broadband synthetic aperture technique with multi-offset probes is developed to improve the lesion characterization by the evaluation of local scattering parameters. This technique works with weak scatterers embedded in a constant velocity medium, large aperture, and isotropic sources and receivers. The features of this technique are: axial and lateral spatial resolution of the order of the wavelength, high dynamic range, quantitative measurements of the size and scattering intensity of the inhomogeneities, and capabilities of investigation of inclined layer. The evaluation of the performances in real condition is carried out by a software simulator in which different experimental situations can be reproduced. Images of simulated anatomic test-objects are presented. The images are obtained with an inversion process of the synthesized ultrasonic signals, collected on the linear aperture by a limited number of finite size transducers.

Three dimensional fracture aperture and porosity distribution using computerized tomography

NASA Astrophysics Data System (ADS)

Wenning, Q.; Madonna, C.; Joss, L.; Pini, R.

2017-12-01

A wide range of geologic processes and geo-engineered applications are governed by coupled hydromechanical properties in the subsurface. In geothermal energy reservoirs, quantifying the rate of heat transfer is directly linked with the transport properties of fractures, underscoring the importance of fracture aperture characterization for achieving optimal heat production. In this context, coupled core-flooding experiments with non-invasive imaging techniques (e.g., X-Ray Computed Tomography - X-Ray CT) provide a powerful method to make observations of these properties under representative geologic conditions. This study focuses on quantifying fracture aperture distribution in a fractured westerly granite core by using a recently developed calibration-free method [Huo et al., 2016]. Porosity is also estimated with the X-ray saturation technique using helium and krypton gases as saturating fluids, chosen for their high transmissibility and high CT contrast [e.g., Vega et al., 2014]. The westerly granite sample (diameter: 5 cm, length: 10 cm) with a single through-going rough-walled fracture was mounted in a high-pressure aluminum core-holder and placed inside a medical CT scanner for imaging. During scanning the pore fluid pressure was undrained and constant, and the confining pressure was regulated to have the desired effective pressure (0.5, 5, 7 and 10 MPa) under loading and unloading conditions. 3D reconstructions of the sample have been prepared in terms of fracture aperture and porosity at a maximum resolution of (0.24×0.24×1) mm3. Fracture aperture maps obtained independently using helium and krypton for the whole core depict a similar heterogeneous aperture field, which is also dependent on confining pressure. Estimates of the average hydraulic aperture from CT scans are in quantitative agreement with results from fluid flow experiments. However, the latter lack of the level of observational detail achieved through imaging, which further evidence the presence of strong heterogeneities in fracture aperture at the mm-scale. These results exemplify the use of non-destructive imaging to determine fracture aperture maps, which can be used to address flow channelization and heat transfer that cannot be obtained from core-flooding experiments alone.

Hexagonal Uniformly Redundant Arrays (HURAs) for scintillator based coded aperture neutron imaging

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

Gamage, K.A.A.; Zhou, Q.

2015-07-01

A series of Monte Carlo simulations have been conducted, making use of the EJ-426 neutron scintillator detector, to investigate the potential of using hexagonal uniformly redundant arrays (HURAs) for scintillator based coded aperture neutron imaging. This type of scintillator material has a low sensitivity to gamma rays, therefore, is of particular use in a system with a source that emits both neutrons and gamma rays. The simulations used an AmBe source, neutron images have been produced using different coded-aperture materials (boron- 10, cadmium-113 and gadolinium-157) and location error has also been estimated. In each case the neutron image clearly showsmore » the location of the source with a relatively small location error. Neutron images with high resolution can be easily used to identify and locate nuclear materials precisely in nuclear security and nuclear decommissioning applications. (authors)« less

Large-field-of-view, modular, stabilized, adaptive-optics-based scanning laser ophthalmoscope.

PubMed

Burns, Stephen A; Tumbar, Remy; Elsner, Ann E; Ferguson, Daniel; Hammer, Daniel X

2007-05-01

We describe the design and performance of an adaptive optics retinal imager that is optimized for use during dynamic correction for eye movements. The system incorporates a retinal tracker and stabilizer, a wide-field line scan scanning laser ophthalmoscope (SLO), and a high-resolution microelectromechanical-systems-based adaptive optics SLO. The detection system incorporates selection and positioning of confocal apertures, allowing measurement of images arising from different portions of the double pass retinal point-spread function (psf). System performance was excellent. The adaptive optics increased the brightness and contrast for small confocal apertures by more than 2x and decreased the brightness of images obtained with displaced apertures, confirming the ability of the adaptive optics system to improve the psf. The retinal image was stabilized to within 18 microm 90% of the time. Stabilization was sufficient for cross-correlation techniques to automatically align the images.

Large Field of View, Modular, Stabilized, Adaptive-Optics-Based Scanning Laser Ophthalmoscope

PubMed Central

Burns, Stephen A.; Tumbar, Remy; Elsner, Ann E.; Ferguson, Daniel; Hammer, Daniel X.

2007-01-01

We describe the design and performance of an adaptive optics retinal imager that is optimized for use during dynamic correction for eye movements. The system incorporates a retinal tracker and stabilizer, a wide field line scan Scanning Laser Ophthalmocsope (SLO), and a high resolution MEMS based adaptive optics SLO. The detection system incorporates selection and positioning of confocal apertures, allowing measurement of images arising from different portions of the double pass retinal point spread function (psf). System performance was excellent. The adaptive optics increased the brightness and contrast for small confocal apertures by more than 2x, and decreased the brightness of images obtained with displaced apertures, confirming the ability of the adaptive optics system to improve the pointspread function. The retinal image was stabilized to within 18 microns 90% of the time. Stabilization was sufficient for cross-correlation techniques to automatically align the images. PMID:17429477

A novel lightweight Fizeau infrared interferometric imaging system

NASA Astrophysics Data System (ADS)

Hope, Douglas A.; Hart, Michael; Warner, Steve; Durney, Oli; Romeo, Robert

2016-05-01

Aperture synthesis imaging techniques using an interferometer provide a means to achieve imagery with spatial resolution equivalent to a conventional filled aperture telescope at a significantly reduced size, weight and cost, an important implication for air- and space-borne persistent observing platforms. These concepts have been realized in SIRII (Space-based IR-imaging interferometer), a new light-weight, compact SWIR and MWIR imaging interferometer designed for space-based surveillance. The sensor design is configured as a six-element Fizeau interferometer; it is scalable, light-weight, and uses structural components and main optics made of carbon fiber replicated polymer (CFRP) that are easy to fabricate and inexpensive. A three-element prototype of the SIRII imager has been constructed. The optics, detectors, and interferometric signal processing principles draw on experience developed in ground-based astronomical applications designed to yield the highest sensitivity and resolution with cost-effective optical solutions. SIRII is being designed for technical intelligence from geo-stationary orbit. It has an instantaneous 6 x 6 mrad FOV and the ability to rapidly scan a 6x6 deg FOV, with a minimal SNR. The interferometric design can be scaled to larger equivalent filled aperture, while minimizing weight and costs when compared to a filled aperture telescope with equivalent resolution. This scalability in SIRII allows it address a range of IR-imaging scenarios.

Multi-layer sparse representation for weighted LBP-patches based facial expression recognition.

PubMed

Jia, Qi; Gao, Xinkai; Guo, He; Luo, Zhongxuan; Wang, Yi

2015-03-19

In this paper, a novel facial expression recognition method based on sparse representation is proposed. Most contemporary facial expression recognition systems suffer from limited ability to handle image nuisances such as low resolution and noise. Especially for low intensity expression, most of the existing training methods have quite low recognition rates. Motivated by sparse representation, the problem can be solved by finding sparse coefficients of the test image by the whole training set. Deriving an effective facial representation from original face images is a vital step for successful facial expression recognition. We evaluate facial representation based on weighted local binary patterns, and Fisher separation criterion is used to calculate the weighs of patches. A multi-layer sparse representation framework is proposed for multi-intensity facial expression recognition, especially for low-intensity expressions and noisy expressions in reality, which is a critical problem but seldom addressed in the existing works. To this end, several experiments based on low-resolution and multi-intensity expressions are carried out. Promising results on publicly available databases demonstrate the potential of the proposed approach.

Enhanced retinal vasculature imaging with a rapidly configurable aperture

PubMed Central

Sapoznik, Kaitlyn A.; Luo, Ting; de Castro, Alberto; Sawides, Lucie; Warner, Raymond L.; Burns, Stephen A.

2018-01-01

In adaptive optics scanning laser ophthalmoscope (AOSLO) systems, capturing multiply scattered light can increase the contrast of the retinal microvasculature structure, cone inner segments, and retinal ganglion cells. Current systems generally use either a split detector or offset aperture approach to collect this light. We tested the ability of a spatial light modulator (SLM) as a rapidly configurable aperture to use more complex shapes to enhance the contrast of retinal structure. Particularly, we varied the orientation of a split detector aperture and explored the use of a more complex shape, the half annulus, to enhance the contrast of the retinal vasculature. We used the new approach to investigate the influence of scattering distance and orientation on vascular imaging. PMID:29541524

SEASAT views oceans and sea ice with synthetic aperture radar

NASA Technical Reports Server (NTRS)

Fu, L. L.; Holt, B.

1982-01-01

Fifty-one SEASAT synthetic aperture radar (SAR) images of the oceans and sea ice are presented. Surface and internal waves, the Gulf Stream system and its rings and eddies, the eastern North Pacific, coastal phenomena, bathymetric features, atmospheric phenomena, and ship wakes are represented. Images of arctic pack and shore-fast ice are presented. The characteristics of the SEASAT SAR system and its image are described. Maps showing the area covered, and tables of key orbital information, and listing digitally processed images are provided.

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR

PubMed Central

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-01-01

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner. PMID:29439447

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.

PubMed

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-02-11

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.

Characterization of fracture aperture for groundwater flow and transport

NASA Astrophysics Data System (ADS)

Sawada, A.; Sato, H.; Tetsu, K.; Sakamoto, K.

2007-12-01

This paper presents experiments and numerical analyses of flow and transport carried out on natural fractures and transparent replica of fractures. The purpose of this study was to improve the understanding of the role of heterogeneous aperture patterns on channelization of groundwater flow and dispersion in solute transport. The research proceeded as follows: First, a precision plane grinder was applied perpendicular to the fracture plane to characterize the aperture distribution on a natural fracture with 1 mm of increment size. Although both time and labor were intensive, this approach provided a detailed, three dimensional picture of the pattern of fracture aperture. This information was analyzed to provide quantitative measures for the fracture aperture distribution, including JRC (Joint Roughness Coefficient) and fracture contact area ratio. These parameters were used to develop numerical models with corresponding synthetic aperture patterns. The transparent fracture replica and numerical models were then used to study how transport is affected by the aperture spatial pattern. In the transparent replica, transmitted light intensity measured by a CCD camera was used to image channeling and dispersion due to the fracture aperture spatial pattern. The CCD image data was analyzed to obtain the quantitative fracture aperture and tracer concentration data according to Lambert-Beer's law. The experimental results were analyzed using the numerical models. Comparison of the numerical models to the transparent replica provided information about the nature of channeling and dispersion due to aperture spatial patterns. These results support to develop a methodology for defining representative fracture aperture of a simplified parallel fracture model for flow and transport in heterogeneous fractures for contaminant transport analysis.

Dictionary Pair Learning on Grassmann Manifolds for Image Denoising.

PubMed

Zeng, Xianhua; Bian, Wei; Liu, Wei; Shen, Jialie; Tao, Dacheng

2015-11-01

Image denoising is a fundamental problem in computer vision and image processing that holds considerable practical importance for real-world applications. The traditional patch-based and sparse coding-driven image denoising methods convert 2D image patches into 1D vectors for further processing. Thus, these methods inevitably break down the inherent 2D geometric structure of natural images. To overcome this limitation pertaining to the previous image denoising methods, we propose a 2D image denoising model, namely, the dictionary pair learning (DPL) model, and we design a corresponding algorithm called the DPL on the Grassmann-manifold (DPLG) algorithm. The DPLG algorithm first learns an initial dictionary pair (i.e., the left and right dictionaries) by employing a subspace partition technique on the Grassmann manifold, wherein the refined dictionary pair is obtained through a sub-dictionary pair merging. The DPLG obtains a sparse representation by encoding each image patch only with the selected sub-dictionary pair. The non-zero elements of the sparse representation are further smoothed by the graph Laplacian operator to remove the noise. Consequently, the DPLG algorithm not only preserves the inherent 2D geometric structure of natural images but also performs manifold smoothing in the 2D sparse coding space. We demonstrate that the DPLG algorithm also improves the structural SIMilarity values of the perceptual visual quality for denoised images using the experimental evaluations on the benchmark images and Berkeley segmentation data sets. Moreover, the DPLG also produces the competitive peak signal-to-noise ratio values from popular image denoising algorithms.

Low-rank Atlas Image Analyses in the Presence of Pathologies

PubMed Central

Liu, Xiaoxiao; Niethammer, Marc; Kwitt, Roland; Singh, Nikhil; McCormick, Matt; Aylward, Stephen

2015-01-01

We present a common framework, for registering images to an atlas and for forming an unbiased atlas, that tolerates the presence of pathologies such as tumors and traumatic brain injury lesions. This common framework is particularly useful when a sufficient number of protocol-matched scans from healthy subjects cannot be easily acquired for atlas formation and when the pathologies in a patient cause large appearance changes. Our framework combines a low-rank-plus-sparse image decomposition technique with an iterative, diffeomorphic, group-wise image registration method. At each iteration of image registration, the decomposition technique estimates a “healthy” version of each image as its low-rank component and estimates the pathologies in each image as its sparse component. The healthy version of each image is used for the next iteration of image registration. The low-rank and sparse estimates are refined as the image registrations iteratively improve. When that framework is applied to image-to-atlas registration, the low-rank image is registered to a pre-defined atlas, to establish correspondence that is independent of the pathologies in the sparse component of each image. Ultimately, image-to-atlas registrations can be used to define spatial priors for tissue segmentation and to map information across subjects. When that framework is applied to unbiased atlas formation, at each iteration, the average of the low-rank images from the patients is used as the atlas image for the next iteration, until convergence. Since each iteration’s atlas is comprised of low-rank components, it provides a population-consistent, pathology-free appearance. Evaluations of the proposed methodology are presented using synthetic data as well as simulated and clinical tumor MRI images from the brain tumor segmentation (BRATS) challenge from MICCAI 2012. PMID:26111390

High resolution depth reconstruction from monocular images and sparse point clouds using deep convolutional neural network

NASA Astrophysics Data System (ADS)

Dimitrievski, Martin; Goossens, Bart; Veelaert, Peter; Philips, Wilfried

2017-09-01

Understanding the 3D structure of the environment is advantageous for many tasks in the field of robotics and autonomous vehicles. From the robot's point of view, 3D perception is often formulated as a depth image reconstruction problem. In the literature, dense depth images are often recovered deterministically from stereo image disparities. Other systems use an expensive LiDAR sensor to produce accurate, but semi-sparse depth images. With the advent of deep learning there have also been attempts to estimate depth by only using monocular images. In this paper we combine the best of the two worlds, focusing on a combination of monocular images and low cost LiDAR point clouds. We explore the idea that very sparse depth information accurately captures the global scene structure while variations in image patches can be used to reconstruct local depth to a high resolution. The main contribution of this paper is a supervised learning depth reconstruction system based on a deep convolutional neural network. The network is trained on RGB image patches reinforced with sparse depth information and the output is a depth estimate for each pixel. Using image and point cloud data from the KITTI vision dataset we are able to learn a correspondence between local RGB information and local depth, while at the same time preserving the global scene structure. Our results are evaluated on sequences from the KITTI dataset and our own recordings using a low cost camera and LiDAR setup.

Low-rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging

PubMed Central

Ravishankar, Saiprasad; Moore, Brian E.; Nadakuditi, Raj Rao; Fessler, Jeffrey A.

2017-01-01

Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery from undersampled measurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamic magnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method. PMID:28092528

Low-Rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging.

PubMed

Ravishankar, Saiprasad; Moore, Brian E; Nadakuditi, Raj Rao; Fessler, Jeffrey A

2017-05-01

Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery fromundersampledmeasurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamicmagnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method.

Sparse modeling applied to patient identification for safety in medical physics applications

NASA Astrophysics Data System (ADS)

Lewkowitz, Stephanie

Every scheduled treatment at a radiation therapy clinic involves a series of safety protocol to ensure the utmost patient care. Despite safety protocol, on a rare occasion an entirely preventable medical event, an accident, may occur. Delivering a treatment plan to the wrong patient is preventable, yet still is a clinically documented error. This research describes a computational method to identify patients with a novel machine learning technique to combat misadministration. The patient identification program stores face and fingerprint data for each patient. New, unlabeled data from those patients are categorized according to the library. The categorization of data by this face-fingerprint detector is accomplished with new machine learning algorithms based on Sparse Modeling that have already begun transforming the foundation of Computer Vision. Previous patient recognition software required special subroutines for faces and different tailored subroutines for fingerprints. In this research, the same exact model is used for both fingerprints and faces, without any additional subroutines and even without adjusting the two hyperparameters. Sparse modeling is a powerful tool, already shown utility in the areas of super-resolution, denoising, inpainting, demosaicing, and sub-nyquist sampling, i.e. compressed sensing. Sparse Modeling is possible because natural images are inherently sparse in some bases, due to their inherent structure. This research chooses datasets of face and fingerprint images to test the patient identification model. The model stores the images of each dataset as a basis (library). One image at a time is removed from the library, and is classified by a sparse code in terms of the remaining library. The Locally Competitive Algorithm, a truly neural inspired Artificial Neural Network, solves the computationally difficult task of finding the sparse code for the test image. The components of the sparse representation vector are summed by ℓ1 pooling, and correct patient identification is consistently achieved 100% over 1000 trials, when either the face data or fingerprint data are implemented as a classification basis. The algorithm gets 100% classification when faces and fingerprints are concatenated into multimodal datasets. This suggests that 100% patient identification will be achievable in the clinal setting.

Fast-neutron, coded-aperture imager

NASA Astrophysics Data System (ADS)

Woolf, Richard S.; Phlips, Bernard F.; Hutcheson, Anthony L.; Wulf, Eric A.

2015-06-01

This work discusses a large-scale, coded-aperture imager for fast neutrons, building off a proof-of concept instrument developed at the U.S. Naval Research Laboratory (NRL). The Space Science Division at the NRL has a heritage of developing large-scale, mobile systems, using coded-aperture imaging, for long-range γ-ray detection and localization. The fast-neutron, coded-aperture imaging instrument, designed for a mobile unit (20 ft. ISO container), consists of a 32-element array of 15 cm×15 cm×15 cm liquid scintillation detectors (EJ-309) mounted behind a 12×12 pseudorandom coded aperture. The elements of the aperture are composed of 15 cm×15 cm×10 cm blocks of high-density polyethylene (HDPE). The arrangement of the aperture elements produces a shadow pattern on the detector array behind the mask. By measuring of the number of neutron counts per masked and unmasked detector, and with knowledge of the mask pattern, a source image can be deconvolved to obtain a 2-d location. The number of neutrons per detector was obtained by processing the fast signal from each PMT in flash digitizing electronics. Digital pulse shape discrimination (PSD) was performed to filter out the fast-neutron signal from the γ background. The prototype instrument was tested at an indoor facility at the NRL with a 1.8-μCi and 13-μCi 252Cf neutron/γ source at three standoff distances of 9, 15 and 26 m (maximum allowed in the facility) over a 15-min integration time. The imaging and detection capabilities of the instrument were tested by moving the source in half- and one-pixel increments across the image plane. We show a representative sample of the results obtained at one-pixel increments for a standoff distance of 9 m. The 1.8-μCi source was not detected at the 26-m standoff. In order to increase the sensitivity of the instrument, we reduced the fastneutron background by shielding the top, sides and back of the detector array with 10-cm-thick HDPE. This shielding configuration led to a reduction in the background by a factor of 1.7 and thus allowed for the detection and localization of the 1.8 μCi. The detection significance for each source at different standoff distances will be discussed.

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

Matsutani, Takaomi; Taya, Masaki; Ikuta, Takashi

A parallel image detection system using an annular pupil for electron optics were developed to realize an increase in the depth of focus, aberration-free imaging and separation of amplitude and phase images under scanning transmission electron microscopy (STEM). Apertures for annular pupils able to suppress high-energy electron scattering were developed using a focused ion beam (FIB) technique. The annular apertures were designed with outer diameter of oe 40 {mu}m and inner diameter of oe32 {mu}m. A taper angle varying from 20 deg. to 1 deg. was applied to the slits of the annular apertures to suppress the influence of high-energymore » electron scattering. Each azimuth angle image on scintillator was detected by a multi-anode photomultiplier tube assembly through 40 optical fibers bundled in a ring shape. To focus the image appearing on the scintillator on optical fibers, an optical lens relay system attached with CCD camera was developed. The system enables the taking of 40 images simultaneously from different scattered directions.« less

Interferometric inverse synthetic aperture radar imaging for space targets based on wideband direct sampling using two antennas

NASA Astrophysics Data System (ADS)

Tian, Biao; Liu, Yang; Xu, Shiyou; Chen, Zengping

2014-01-01

Interferometric inverse synthetic aperture radar (InISAR) imaging provides complementary information to monostatic inverse synthetic aperture radar (ISAR) imaging. This paper proposes a new InISAR imaging system for space targets based on wideband direct sampling using two antennas. The system is easy to realize in engineering since the motion trajectory of space targets can be known in advance, which is simpler than that of three receivers. In the preprocessing step, high speed movement compensation is carried out by designing an adaptive matched filter containing speed that is obtained from the narrow band information. Then, the coherent processing and keystone transform for ISAR imaging are adopted to reserve the phase history of each antenna. Through appropriate collocation of the system, image registration and phase unwrapping can be avoided. Considering the situation not to be satisfied, the influence of baseline variance is analyzed and compensation method is adopted. The corresponding size can be achieved by interferometric processing of the two complex ISAR images. Experimental results prove the validity of the analysis and the three-dimensional imaging algorithm.

SYNMAG PHOTOMETRY: A FAST TOOL FOR CATALOG-LEVEL MATCHED COLORS OF EXTENDED SOURCES

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

Bundy, Kevin; Yasuda, Naoki; Hogg, David W.

2012-12-01

Obtaining reliable, matched photometry for galaxies imaged by different observatories represents a key challenge in the era of wide-field surveys spanning more than several hundred square degrees. Methods such as flux fitting, profile fitting, and PSF homogenization followed by matched-aperture photometry are all computationally expensive. We present an alternative solution called 'synthetic aperture photometry' that exploits galaxy profile fits in one band to efficiently model the observed, point-spread-function-convolved light profile in other bands and predict the flux in arbitrarily sized apertures. Because aperture magnitudes are the most widely tabulated flux measurements in survey catalogs, producing synthetic aperture magnitudes (SYNMAGs) enablesmore » very fast matched photometry at the catalog level, without reprocessing imaging data. We make our code public and apply it to obtain matched photometry between Sloan Digital Sky Survey ugriz and UKIDSS YJHK imaging, recovering red-sequence colors and photometric redshifts with a scatter and accuracy as good as if not better than FWHM-homogenized photometry from the GAMA Survey. Finally, we list some specific measurements that upcoming surveys could make available to facilitate and ease the use of SYNMAGs.« less

Functional Form of the Radiometric Equation for the SNPP VIIRS Reflective Solar Bands: An Initial Study

NASA Technical Reports Server (NTRS)

Lei, Ning; Xiong, Xiaoxiong

2016-01-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite is a passive scanning radiometer and an imager, observing radiative energy from the Earth in 22 spectral bands from 0.41 to 12 microns which include 14 reflective solar bands (RSBs). Extending the formula used by the Moderate Resolution Imaging Spectroradiometer instruments, currently the VIIRS determines the sensor aperture spectral radiance through a quadratic polynomial of its detector digital count. It has been known that for the RSBs the quadratic polynomial is not adequate in the design specified spectral radiance region and using a quadratic polynomial could drastically increase the errors in the polynomial coefficients, leading to possible large errors in the determined aperture spectral radiance. In addition, it is very desirable to be able to extend the radiance calculation formula to correctly retrieve the aperture spectral radiance with the level beyond the design specified range. In order to more accurately determine the aperture spectral radiance from the observed digital count, we examine a few polynomials of the detector digital count to calculate the sensor aperture spectral radiance.

Design of an integrated aerial image sensor

NASA Astrophysics Data System (ADS)

Xue, Jing; Spanos, Costas J.

2005-05-01

The subject of this paper is a novel integrated aerial image sensor (IAIS) system suitable for integration within the surface of an autonomous test wafer. The IAIS could be used as a lithography processing monitor, affording a "wafer's eye view" of the process, and therefore facilitating advanced process control and diagnostics without integrating (and dedicating) the sensor to the processing equipment. The IAIS is composed of an aperture mask and an array of photo-detectors. In order to retrieve nanometer scale resolution of the aerial image with a practical photo-detector pixel size, we propose a design of an aperture mask involving a series of spatial phase "moving" aperture groups. We demonstrate a design example aimed at the 65nm technology node through TEMPEST simulation. The optimized, key design parameters include an aperture width in the range of 30nm, aperture thickness in the range of 70nm, and offer a spatial resolution of about 5nm, all with comfortable fabrication tolerances. Our preliminary simulation work indicates the possibility of the IAIS being applied to the immersion lithography. A bench-top far-field experiment verifies that our approach of the spatial frequency down-shift through forming large Moire patterns is feasible.

Synthetic aperture radar images of ocean waves, theories of imaging physics and experimental tests

NASA Technical Reports Server (NTRS)

Vesecky, J. F.; Durden, S. L.; Smith, M. P.; Napolitano, D. A.

1984-01-01

The physical mechanism for the synthetic Aperture Radar (SAR) imaging of ocean waves is investigated through the use of analytical models. The models are tested by comparison with data sets from the SEASAT mission and airborne SAR's. Dominant ocean wavelengths from SAR estimates are biased towards longer wavelengths. The quasispecular scattering mechanism agrees with experimental data. The Doppler shift for ship wakes is that of the mean sea surface.

Sparse imaging for fast electron microscopy

NASA Astrophysics Data System (ADS)

Anderson, Hyrum S.; Ilic-Helms, Jovana; Rohrer, Brandon; Wheeler, Jason; Larson, Kurt

2013-02-01

Scanning electron microscopes (SEMs) are used in neuroscience and materials science to image centimeters of sample area at nanometer scales. Since imaging rates are in large part SNR-limited, large collections can lead to weeks of around-the-clock imaging time. To increase data collection speed, we propose and demonstrate on an operational SEM a fast method to sparsely sample and reconstruct smooth images. To accurately localize the electron probe position at fast scan rates, we model the dynamics of the scan coils, and use the model to rapidly and accurately visit a randomly selected subset of pixel locations. Images are reconstructed from the undersampled data by compressed sensing inversion using image smoothness as a prior. We report image fidelity as a function of acquisition speed by comparing traditional raster to sparse imaging modes. Our approach is equally applicable to other domains of nanometer microscopy in which the time to position a probe is a limiting factor (e.g., atomic force microscopy), or in which excessive electron doses might otherwise alter the sample being observed (e.g., scanning transmission electron microscopy).

Method and apparatus for distinguishing actual sparse events from sparse event false alarms

DOEpatents

Spalding, Richard E.; Grotbeck, Carter L.

2000-01-01

Remote sensing method and apparatus wherein sparse optical events are distinguished from false events. "Ghost" images of actual optical phenomena are generated using an optical beam splitter and optics configured to direct split beams to a single sensor or segmented sensor. True optical signals are distinguished from false signals or noise based on whether the ghost image is presence or absent. The invention obviates the need for dual sensor systems to effect a false target detection capability, thus significantly reducing system complexity and cost.

Implicit kernel sparse shape representation: a sparse-neighbors-based objection segmentation framework.

PubMed

Yao, Jincao; Yu, Huimin; Hu, Roland

2017-01-01

This paper introduces a new implicit-kernel-sparse-shape-representation-based object segmentation framework. Given an input object whose shape is similar to some of the elements in the training set, the proposed model can automatically find a cluster of implicit kernel sparse neighbors to approximately represent the input shape and guide the segmentation. A distance-constrained probabilistic definition together with a dualization energy term is developed to connect high-level shape representation and low-level image information. We theoretically prove that our model not only derives from two projected convex sets but is also equivalent to a sparse-reconstruction-error-based representation in the Hilbert space. Finally, a "wake-sleep"-based segmentation framework is applied to drive the evolutionary curve to recover the original shape of the object. We test our model on two public datasets. Numerical experiments on both synthetic images and real applications show the superior capabilities of the proposed framework.

Robust Single Image Super-Resolution via Deep Networks With Sparse Prior.

PubMed

Liu, Ding; Wang, Zhaowen; Wen, Bihan; Yang, Jianchao; Han, Wei; Huang, Thomas S

2016-07-01

Single image super-resolution (SR) is an ill-posed problem, which tries to recover a high-resolution image from its low-resolution observation. To regularize the solution of the problem, previous methods have focused on designing good priors for natural images, such as sparse representation, or directly learning the priors from a large data set with models, such as deep neural networks. In this paper, we argue that domain expertise from the conventional sparse coding model can be combined with the key ingredients of deep learning to achieve further improved results. We demonstrate that a sparse coding model particularly designed for SR can be incarnated as a neural network with the merit of end-to-end optimization over training data. The network has a cascaded structure, which boosts the SR performance for both fixed and incremental scaling factors. The proposed training and testing schemes can be extended for robust handling of images with additional degradation, such as noise and blurring. A subjective assessment is conducted and analyzed in order to thoroughly evaluate various SR techniques. Our proposed model is tested on a wide range of images, and it significantly outperforms the existing state-of-the-art methods for various scaling factors both quantitatively and perceptually.

EIT Imaging Regularization Based on Spectral Graph Wavelets.

PubMed

Gong, Bo; Schullcke, Benjamin; Krueger-Ziolek, Sabine; Vauhkonen, Marko; Wolf, Gerhard; Mueller-Lisse, Ullrich; Moeller, Knut

2017-09-01

The objective of electrical impedance tomographic reconstruction is to identify the distribution of tissue conductivity from electrical boundary conditions. This is an ill-posed inverse problem usually solved under the finite-element method framework. In previous studies, standard sparse regularization was used for difference electrical impedance tomography to achieve a sparse solution. However, regarding elementwise sparsity, standard sparse regularization interferes with the smoothness of conductivity distribution between neighboring elements and is sensitive to noise. As an effect, the reconstructed images are spiky and depict a lack of smoothness. Such unexpected artifacts are not realistic and may lead to misinterpretation in clinical applications. To eliminate such artifacts, we present a novel sparse regularization method that uses spectral graph wavelet transforms. Single-scale or multiscale graph wavelet transforms are employed to introduce local smoothness on different scales into the reconstructed images. The proposed approach relies on viewing finite-element meshes as undirected graphs and applying wavelet transforms derived from spectral graph theory. Reconstruction results from simulations, a phantom experiment, and patient data suggest that our algorithm is more robust to noise and produces more reliable images.

Time-gated ballistic imaging using a large aperture switching beam.

PubMed

Mathieu, Florian; Reddemann, Manuel A; Palmer, Johannes; Kneer, Reinhold

2014-03-24

Ballistic imaging commonly denotes the formation of line-of-sight shadowgraphs through turbid media by suppression of multiply scattered photons. The technique relies on a femtosecond laser acting as light source for the images and as switch for an optical Kerr gate that separates ballistic photons from multiply scattered ones. The achievable image resolution is one major limitation for the investigation of small objects. In this study, practical influences on the optical Kerr gate and image quality are discussed theoretically and experimentally applying a switching beam with large aperture (D = 19 mm). It is shown how switching pulse energy and synchronization of switching and imaging pulse in the Kerr cell influence the gate's transmission. Image quality of ballistic imaging and standard shadowgraphy is evaluated and compared, showing that the present ballistic imaging setup is advantageous for optical densities in the range of 8 < OD < 13. Owing to the spatial transmission characteristics of the optical Kerr gate, a rectangular aperture stop is formed, which leads to different resolution limits for vertical and horizontal structures in the object. Furthermore, it is reported how to convert the ballistic imaging setup into a schlieren-type system with an optical schlieren edge.

Sparse representations via learned dictionaries for x-ray angiogram image denoising

NASA Astrophysics Data System (ADS)

Shang, Jingfan; Huang, Zhenghua; Li, Qian; Zhang, Tianxu

2018-03-01

X-ray angiogram image denoising is always an active research topic in the field of computer vision. In particular, the denoising performance of many existing methods had been greatly improved by the widely use of nonlocal similar patches. However, the only nonlocal self-similar (NSS) patch-based methods can be still be improved and extended. In this paper, we propose an image denoising model based on the sparsity of the NSS patches to obtain high denoising performance and high-quality image. In order to represent the sparsely NSS patches in every location of the image well and solve the image denoising model more efficiently, we obtain dictionaries as a global image prior by the K-SVD algorithm over the processing image; Then the single and effectively alternating directions method of multipliers (ADMM) method is used to solve the image denoising model. The results of widely synthetic experiments demonstrate that, owing to learned dictionaries by K-SVD algorithm, a sparsely augmented lagrangian image denoising (SALID) model, which perform effectively, obtains a state-of-the-art denoising performance and better high-quality images. Moreover, we also give some denoising results of clinical X-ray angiogram images.

A LIKELY CLOSE-IN LOW-MASS STELLAR COMPANION TO THE TRANSITIONAL DISK STAR HD 142527

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

Biller, Beth; Benisty, Myriam; Chauvin, Gael

2012-07-10

With the uniquely high contrast within 0.''1 ({Delta}mag(L') = 5-6.5 mag) available using Sparse Aperture Masking with NACO at Very Large Telescope, we detected asymmetry in the flux from the Herbig Fe star HD 142527 with a barycenter emission situated at a projected separation of 88 {+-} 5 mas (12.8 {+-} 1.5 AU at 145 pc) and flux ratios in H, K, and L' of 0.016 {+-} 0.007, 0.012 {+-} 0.008, and 0.0086 {+-} 0.0011, respectively (3{sigma} errors), relative to the primary star and disk. After extensive closure-phase modeling, we interpret this detection as a close-in, low-mass stellar companion withmore » an estimated mass of {approx}0.1-0.4 M{sub Sun }. HD 142527 has a complex disk structure, with an inner gap imaged in both the near and mid-IR as well as a spiral feature in the outer disk in the near-IR. This newly detected low-mass stellar companion may provide a critical explanation of the observed disk structure.« less

Regularized learning of linear ordered-statistic constant false alarm rate filters (Conference Presentation)

NASA Astrophysics Data System (ADS)

Havens, Timothy C.; Cummings, Ian; Botts, Jonathan; Summers, Jason E.

2017-05-01

The linear ordered statistic (LOS) is a parameterized ordered statistic (OS) that is a weighted average of a rank-ordered sample. LOS operators are useful generalizations of aggregation as they can represent any linear aggregation, from minimum to maximum, including conventional aggregations, such as mean and median. In the fuzzy logic field, these aggregations are called ordered weighted averages (OWAs). Here, we present a method for learning LOS operators from training data, viz., data for which you know the output of the desired LOS. We then extend the learning process with regularization, such that a lower complexity or sparse LOS can be learned. Hence, we discuss what 'lower complexity' means in this context and how to represent that in the optimization procedure. Finally, we apply our learning methods to the well-known constant-false-alarm-rate (CFAR) detection problem, specifically for the case of background levels modeled by long-tailed distributions, such as the K-distribution. These backgrounds arise in several pertinent imaging problems, including the modeling of clutter in synthetic aperture radar and sonar (SAR and SAS) and in wireless communications.

Single shot, three-dimensional fluorescence microscopy with a spatially rotating point spread function

PubMed Central

Wang, Zhaojun; Cai, Yanan; Liang, Yansheng; Zhou, Xing; Yan, Shaohui; Dan, Dan; Bianco, Piero R.; Lei, Ming; Yao, Baoli

2017-01-01

A wide-field fluorescence microscope with a double-helix point spread function (PSF) is constructed to obtain the specimen’s three-dimensional distribution with a single snapshot. Spiral-phase-based computer-generated holograms (CGHs) are adopted to make the depth-of-field of the microscope adjustable. The impact of system aberrations on the double-helix PSF at high numerical aperture is analyzed to reveal the necessity of the aberration correction. A modified cepstrum-based reconstruction scheme is promoted in accordance with properties of the new double-helix PSF. The extended depth-of-field images and the corresponding depth maps for both a simulated sample and a tilted section slice of bovine pulmonary artery endothelial (BPAE) cells are recovered, respectively, verifying that the depth-of-field is properly extended and the depth of the specimen can be estimated at a precision of 23.4nm. This three-dimensional fluorescence microscope with a framerate-rank time resolution is suitable for studying the fast developing process of thin and sparsely distributed micron-scale cells in extended depth-of-field. PMID:29296483

Sub-aperture switching based ptychographic iterative engine (sasPIE) method for quantitative imaging

NASA Astrophysics Data System (ADS)

Sun, Aihui; Kong, Yan; Jiang, Zhilong; Yu, Wei; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng

2018-03-01

Though ptychographic iterative engine (PIE) has been widely adopted in the quantitative micro-imaging with various illuminations as visible light, X-ray and electron beam, the mechanical inaccuracy in the raster scanning of the sample relative to the illumination always degrades the reconstruction quality seriously and makes the resolution reached much lower than that determined by the numerical aperture of the optical system. To overcome this disadvantage, the sub-aperture switching based PIE method is proposed: the mechanical scanning in the common PIE is replaced by the sub-aperture switching, and the reconstruction error related to the positioning inaccuracy is completely avoided. The proposed technique remarkably improves the reconstruction quality, reduces the complexity of the experimental setup and fundamentally accelerates the data acquisition and reconstruction.

A novel structured dictionary for fast processing of 3D medical images, with application to computed tomography restoration and denoising

NASA Astrophysics Data System (ADS)

Karimi, Davood; Ward, Rabab K.

2016-03-01

Sparse representation of signals in learned overcomplete dictionaries has proven to be a powerful tool with applications in denoising, restoration, compression, reconstruction, and more. Recent research has shown that learned overcomplete dictionaries can lead to better results than analytical dictionaries such as wavelets in almost all image processing applications. However, a major disadvantage of these dictionaries is that their learning and usage is very computationally intensive. In particular, finding the sparse representation of a signal in these dictionaries requires solving an optimization problem that leads to very long computational times, especially in 3D image processing. Moreover, the sparse representation found by greedy algorithms is usually sub-optimal. In this paper, we propose a novel two-level dictionary structure that improves the performance and the speed of standard greedy sparse coding methods. The first (i.e., the top) level in our dictionary is a fixed orthonormal basis, whereas the second level includes the atoms that are learned from the training data. We explain how such a dictionary can be learned from the training data and how the sparse representation of a new signal in this dictionary can be computed. As an application, we use the proposed dictionary structure for removing the noise and artifacts in 3D computed tomography (CT) images. Our experiments with real CT images show that the proposed method achieves results that are comparable with standard dictionary-based methods while substantially reducing the computational time.

Remote sensing image segmentation using local sparse structure constrained latent low rank representation

NASA Astrophysics Data System (ADS)

Tian, Shu; Zhang, Ye; Yan, Yimin; Su, Nan; Zhang, Junping

2016-09-01

Latent low-rank representation (LatLRR) has been attached considerable attention in the field of remote sensing image segmentation, due to its effectiveness in exploring the multiple subspace structures of data. However, the increasingly heterogeneous texture information in the high spatial resolution remote sensing images, leads to more severe interference of pixels in local neighborhood, and the LatLRR fails to capture the local complex structure information. Therefore, we present a local sparse structure constrainted latent low-rank representation (LSSLatLRR) segmentation method, which explicitly imposes the local sparse structure constraint on LatLRR to capture the intrinsic local structure in manifold structure feature subspaces. The whole segmentation framework can be viewed as two stages in cascade. In the first stage, we use the local histogram transform to extract the texture local histogram features (LHOG) at each pixel, which can efficiently capture the complex and micro-texture pattern. In the second stage, a local sparse structure (LSS) formulation is established on LHOG, which aims to preserve the local intrinsic structure and enhance the relationship between pixels having similar local characteristics. Meanwhile, by integrating the LSS and the LatLRR, we can efficiently capture the local sparse and low-rank structure in the mixture of feature subspace, and we adopt the subspace segmentation method to improve the segmentation accuracy. Experimental results on the remote sensing images with different spatial resolution show that, compared with three state-of-the-art image segmentation methods, the proposed method achieves more accurate segmentation results.

The sonar aperture and its neural representation in bats.

PubMed

Heinrich, Melina; Warmbold, Alexander; Hoffmann, Susanne; Firzlaff, Uwe; Wiegrebe, Lutz

2011-10-26

As opposed to visual imaging, biosonar imaging of spatial object properties represents a challenge for the auditory system because its sensory epithelium is not arranged along space axes. For echolocating bats, object width is encoded by the amplitude of its echo (echo intensity) but also by the naturally covarying spread of angles of incidence from which the echoes impinge on the bat's ears (sonar aperture). It is unclear whether bats use the echo intensity and/or the sonar aperture to estimate an object's width. We addressed this question in a combined psychophysical and electrophysiological approach. In three virtual-object playback experiments, bats of the species Phyllostomus discolor had to discriminate simple reflections of their own echolocation calls differing in echo intensity, sonar aperture, or both. Discrimination performance for objects with physically correct covariation of sonar aperture and echo intensity ("object width") did not differ from discrimination performances when only the sonar aperture was varied. Thus, the bats were able to detect changes in object width in the absence of intensity cues. The psychophysical results are reflected in the responses of a population of units in the auditory midbrain and cortex that responded strongest to echoes from objects with a specific sonar aperture, regardless of variations in echo intensity. Neurometric functions obtained from cortical units encoding the sonar aperture are sufficient to explain the behavioral performance of the bats. These current data show that the sonar aperture is a behaviorally relevant and reliably encoded cue for object size in bat sonar.

Compressive sensing imaging through a drywall barrier at sub-THz and THz frequencies in transmission and reflection modes

NASA Astrophysics Data System (ADS)

Takan, Taylan; Özkan, Vedat A.; Idikut, Fırat; Yildirim, Ihsan Ozan; Şahin, Asaf B.; Altan, Hakan

2014-10-01

In this work sub-terahertz imaging using Compressive Sensing (CS) techniques for targets placed behind a visibly opaque barrier is demonstrated both experimentally and theoretically. Using a multiplied Schottky diode based millimeter wave source working at 118 GHz, metal cutout targets were illuminated in both reflection and transmission configurations with and without barriers which were made out of drywall. In both modes the image is spatially discretized using laser machined, 10 × 10 pixel metal apertures to demonstrate the technique of compressive sensing. The images were collected by modulating the source and measuring the transmitted flux through the apertures using a Golay cell. Experimental results were compared to simulations of the expected transmission through the metal apertures. Image quality decreases as expected when going from the non-obscured transmission case to the obscured transmission case and finally to the obscured reflection case. However, in all instances the image appears below the Nyquist rate which demonstrates that this technique is a viable option for Through the Wall Reflection Imaging (TWRI) applications.

Real-time multiple-look synthetic aperture radar processor for spacecraft applications

NASA Technical Reports Server (NTRS)

Wu, C.; Tyree, V. C. (Inventor)

1981-01-01

A spaceborne synthetic aperture radar (SAR) having pipeline multiple-look data processing is described which makes use of excessive azimuth bandwidth in radar echo signals to produce multiple-looking images. Time multiplexed single-look image lines from an azimuth correlator go through an energy analyzer which analyzes the mean energy in each separate look to determine the radar antenna electric boresight for use in generating the correct reference functions for the production of high quality SAR images. The multiplexed single look image lines also go through a registration delay to produce multi-look images.

A panoramic coded aperture gamma camera for radioactive hotspots localization

NASA Astrophysics Data System (ADS)

Paradiso, V.; Amgarou, K.; Blanc De Lanaute, N.; Schoepff, V.; Amoyal, G.; Mahe, C.; Beltramello, O.; Liénard, E.

2017-11-01

A known disadvantage of the coded aperture imaging approach is its limited field-of-view (FOV), which often results insufficient when analysing complex dismantling scenes such as post-accidental scenarios, where multiple measurements are needed to fully characterize the scene. In order to overcome this limitation, a panoramic coded aperture γ-camera prototype has been developed. The system is based on a 1 mm thick CdTe detector directly bump-bonded to a Timepix readout chip, developed by the Medipix2 collaboration (256 × 256 pixels, 55 μm pitch, 14.08 × 14.08 mm2 sensitive area). A MURA pattern coded aperture is used, allowing for background subtraction without the use of heavy shielding. Such system is then combined with a USB color camera. The output of each measurement is a semi-spherical image covering a FOV of 360 degrees horizontally and 80 degrees vertically, rendered in spherical coordinates (θ,phi). The geometrical shapes of the radiation-emitting objects are preserved by first registering and stitching the optical images captured by the prototype, and applying, subsequently, the same transformations to their corresponding radiation images. Panoramic gamma images generated by using the technique proposed in this paper are described and discussed, along with the main experimental results obtained in laboratories campaigns.

Similarity regularized sparse group lasso for cup to disc ratio computation.

PubMed

Cheng, Jun; Zhang, Zhuo; Tao, Dacheng; Wong, Damon Wing Kee; Liu, Jiang; Baskaran, Mani; Aung, Tin; Wong, Tien Yin

2017-08-01

Automatic cup to disc ratio (CDR) computation from color fundus images has shown to be promising for glaucoma detection. Over the past decade, many algorithms have been proposed. In this paper, we first review the recent work in the area and then present a novel similarity-regularized sparse group lasso method for automated CDR estimation. The proposed method reconstructs the testing disc image based on a set of reference disc images by integrating the similarity between testing and the reference disc images with the sparse group lasso constraints. The reconstruction coefficients are then used to estimate the CDR of the testing image. The proposed method has been validated using 650 images with manually annotated CDRs. Experimental results show an average CDR error of 0.0616 and a correlation coefficient of 0.7, outperforming other methods. The areas under curve in the diagnostic test reach 0.843 and 0.837 when manual and automatically segmented discs are used respectively, better than other methods as well.

Phase correction system for automatic focusing of synthetic aperture radar

DOEpatents

Eichel, Paul H.; Ghiglia, Dennis C.; Jakowatz, Jr., Charles V.

1990-01-01

A phase gradient autofocus system for use in synthetic aperture imaging accurately compensates for arbitrary phase errors in each imaged frame by locating highlighted areas and determining the phase disturbance or image spread associated with each of these highlight areas. An estimate of the image spread for each highlighted area in a line in the case of one dimensional processing or in a sector, in the case of two-dimensional processing, is determined. The phase error is determined using phase gradient processing. The phase error is then removed from the uncorrected image and the process is iteratively performed to substantially eliminate phase errors which can degrade the image.

Synthetic aperture radar target detection, feature extraction, and image formation techniques

NASA Technical Reports Server (NTRS)

Li, Jian

1994-01-01

This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

Coupled dictionary learning for joint MR image restoration and segmentation

NASA Astrophysics Data System (ADS)

Yang, Xuesong; Fan, Yong

2018-03-01

To achieve better segmentation of MR images, image restoration is typically used as a preprocessing step, especially for low-quality MR images. Recent studies have demonstrated that dictionary learning methods could achieve promising performance for both image restoration and image segmentation. These methods typically learn paired dictionaries of image patches from different sources and use a common sparse representation to characterize paired image patches, such as low-quality image patches and their corresponding high quality counterparts for the image restoration, and image patches and their corresponding segmentation labels for the image segmentation. Since learning these dictionaries jointly in a unified framework may improve the image restoration and segmentation simultaneously, we propose a coupled dictionary learning method to concurrently learn dictionaries for joint image restoration and image segmentation based on sparse representations in a multi-atlas image segmentation framework. Particularly, three dictionaries, including a dictionary of low quality image patches, a dictionary of high quality image patches, and a dictionary of segmentation label patches, are learned in a unified framework so that the learned dictionaries of image restoration and segmentation can benefit each other. Our method has been evaluated for segmenting the hippocampus in MR T1 images collected with scanners of different magnetic field strengths. The experimental results have demonstrated that our method achieved better image restoration and segmentation performance than state of the art dictionary learning and sparse representation based image restoration and image segmentation methods.

Large-aperture space optical system testing based on the scanning Hartmann.

PubMed

Wei, Haisong; Yan, Feng; Chen, Xindong; Zhang, Hao; Cheng, Qiang; Xue, Donglin; Zeng, Xuefeng; Zhang, Xuejun

2017-03-10

Based on the Hartmann testing principle, this paper proposes a novel image quality testing technology which applies to a large-aperture space optical system. Compared with the traditional testing method through a large-aperture collimator, the scanning Hartmann testing technology has great advantages due to its simple structure, low cost, and ability to perform wavefront measurement of an optical system. The basic testing principle of the scanning Hartmann testing technology, data processing method, and simulation process are presented in this paper. Certain simulation results are also given to verify the feasibility of this technology. Furthermore, a measuring system is developed to conduct a wavefront measurement experiment for a 200 mm aperture optical system. The small deviation (6.3%) of root mean square (RMS) between experimental results and interferometric results indicates that the testing system can measure low-order aberration correctly, which means that the scanning Hartmann testing technology has the ability to test the imaging quality of a large-aperture space optical system.

Target Transformation Constrained Sparse Unmixing (ttcsu) Algorithm for Retrieving Hydrous Minerals on Mars: Application to Southwest Melas Chasma

NASA Astrophysics Data System (ADS)

Lin, H.; Zhang, X.; Wu, X.; Tarnas, J. D.; Mustard, J. F.

2018-04-01

Quantitative analysis of hydrated minerals from hyperspectral remote sensing data is fundamental for understanding Martian geologic process. Because of the difficulties for selecting endmembers from hyperspectral images, a sparse unmixing algorithm has been proposed to be applied to CRISM data on Mars. However, it's challenge when the endmember library increases dramatically. Here, we proposed a new methodology termed Target Transformation Constrained Sparse Unmixing (TTCSU) to accurately detect hydrous minerals on Mars. A new version of target transformation technique proposed in our recent work was used to obtain the potential detections from CRISM data. Sparse unmixing constrained with these detections as prior information was applied to CRISM single-scattering albedo images, which were calculated using a Hapke radiative transfer model. This methodology increases success rate of the automatic endmember selection of sparse unmixing and could get more accurate abundances. CRISM images with well analyzed in Southwest Melas Chasma was used to validate our methodology in this study. The sulfates jarosite was detected from Southwest Melas Chasma, the distribution is consistent with previous work and the abundance is comparable. More validations will be done in our future work.

Deep feature representation with stacked sparse auto-encoder and convolutional neural network for hyperspectral imaging-based detection of cucumber defects

USDA-ARS?s Scientific Manuscript database

It is challenging to achieve rapid and accurate processing of large amounts of hyperspectral image data. This research was aimed to develop a novel classification method by employing deep feature representation with the stacked sparse auto-encoder (SSAE) and the SSAE combined with convolutional neur...

Conception and realization of a semiconductor based 240 GHz full 3D MIMO imaging system

NASA Astrophysics Data System (ADS)

Weisenstein, Christian; Kahl, Matthias; Friederich, Fabian; Haring Bolívar, Peter

2017-02-01

Multiple-input multiple-output (MIMO) imaging systems in the terahertz frequency range have a high potential in the field of non-destructive testing (NDT). With such systems it is possible to detect defects in composite materials, for example cracks or delaminations in fiber composites. To investigate mass-produced products it is necessary to study the objects in close to real-time on a conveyor without affecting the production cycle time. In this work we present the conception and realization of a 3D MIMO imaging system for in-line investigation of composite materials and structures. To achieve a lateral resolution of 1 mm, in order to detect such small defects in composite materials with a moderate number of elements, precise sensor design is crucial. In our approach we use the effective aperture concept. The designed sparse array consists of 32 transmitters and 30 receivers based on planar semiconductor components. High range resolution is achieved by an operating frequency between 220 GHz and 260 GHz in a stepped frequency continuous wave (SFCW) setup. A matched filter approach is used to simulate the reconstructed 3D image through the array. This allows the evaluation of the designed array geometry in regard of resolution and side lobe level. In contrast to earlier demonstrations, in which synthetic reconstruction is only performed in a 2D plane, an optics-free full 3D recon- struction has been implemented in our concept. Based on this simulation we designed an array geometry that enables to resolve objects with a resolution smaller than 1mm and moderate side lobe level.

Examples of current radar technology and applications, chapter 5, part B

NASA Technical Reports Server (NTRS)

1975-01-01

Basic principles and tradeoff considerations for SLAR are summarized. There are two fundamental types of SLAR sensors available to the remote sensing user: real aperture and synthetic aperture. The primary difference between the two types is that a synthetic aperture system is capable of significant improvements in target resolution but requires equally significant added complexity and cost. The advantages of real aperture SLAR include long range coverage, all-weather operation, in-flight processing and image viewing, and lower cost. The fundamental limitation of the real aperture approach is target resolution. Synthetic aperture processing is the most practical approach for remote sensing problems that require resolution higher than 30 to 40 m.

Insights from Classifying Visual Concepts with Multiple Kernel Learning

PubMed Central

Binder, Alexander; Nakajima, Shinichi; Kloft, Marius; Müller, Christina; Samek, Wojciech; Brefeld, Ulf; Müller, Klaus-Robert; Kawanabe, Motoaki

2012-01-01

Combining information from various image features has become a standard technique in concept recognition tasks. However, the optimal way of fusing the resulting kernel functions is usually unknown in practical applications. Multiple kernel learning (MKL) techniques allow to determine an optimal linear combination of such similarity matrices. Classical approaches to MKL promote sparse mixtures. Unfortunately, 1-norm regularized MKL variants are often observed to be outperformed by an unweighted sum kernel. The main contributions of this paper are the following: we apply a recently developed non-sparse MKL variant to state-of-the-art concept recognition tasks from the application domain of computer vision. We provide insights on benefits and limits of non-sparse MKL and compare it against its direct competitors, the sum-kernel SVM and sparse MKL. We report empirical results for the PASCAL VOC 2009 Classification and ImageCLEF2010 Photo Annotation challenge data sets. Data sets (kernel matrices) as well as further information are available at http://doc.ml.tu-berlin.de/image_mkl/(Accessed 2012 Jun 25). PMID:22936970

Spatiotemporal variations of radar glacier zones in the Karakoram Mountains

NASA Astrophysics Data System (ADS)

Lund, Jewell

2017-04-01

Glaciers of the Karakoram Mountains are important climate indicators for densely populated South Central Asia. Glacial meltwater is a significant source of runoff in the Indus River Basin, upon which 60 million people rely for food security, economy and hydropower in Pakistan and India. Contrary to worldwide and also Himalayan trends, Karakoram glaciers have recently been verified in near balance, with some glaciers even gaining mass or surging. This 'Karakoram anomaly' is of interest, and many hypotheses exist for its causes. Complex climatology, coupled with the challenges of field study in this region, illicit notable uncertainties both in observation and prediction of glacial status. Constraining spatiotemporal variations in glacial mass balance will elucidate the extent and possible longevity of this anomaly, and its implications for water resources, as climate continues to change. Depending on snowpack conditions during image acquisition, different snow and ice zones on a glacier are identifiable in synthetic aperture radar (SAR) images. The identification and monitoring of radar glacier zones over time can provide indicators of relative glacial mass balance to compliment field studies in a region with sparse field measurement. We will present spatiotemporal evolution of basic radar glacier zones such as wet snow, bare ice, percolation, and firn for glaciers feeding into the Upper Indus Basin. We will incorporate both ascending and descending passes of Sentinel-1 series C -band sensors, and possibly ALOS-2 PALSAR-2 L-band images. We may also explore the impacts of these variations on timing and intensity of runoff.

A SEASAT-A synthetic aperture imaging radar system

NASA Technical Reports Server (NTRS)

Jordan, R. L.; Rodgers, D. H.

1975-01-01

The SEASAT, a synthetic aperture imaging radar system is the first radar system of its kind designed for the study of ocean wave patterns from orbit. The basic requirement of this system is to generate continuous radar imagery with a 100 km swath with 25m resolution from an orbital altitude of 800 km. These requirements impose unique system design problems. The end to end data system described including interactions of the spacecraft, antenna, sensor, telemetry link, and data processor. The synthetic aperture radar system generates a large quantity of data requiring the use of an analog link with stable local oscillator encoding. The problems associated in telemetering the radar information with sufficient fidelity to synthesize an image on the ground is described as well as the selected solutions to the problems.

Design and simulation of high resolution optical imaging system based on near-field using solid immersion lens with NA = 2.2

NASA Astrophysics Data System (ADS)

Abbasian, Karim; Sadeghi, Rasool; Sadeghi, Parvin

2014-03-01

In this work, by changing annular aperture zones transmittance, we could get a spot size smaller than any reported one by utilizing annular aperture. Where, by dividing the annular aperture to more than three zones and utilizing of Sony corporation Produced SIL that has NA higher than 2, we could improve imaging resolution for radial polarization (RP); also we could decrease the FWHM from around ? to near ?. Here, the FWHM variation, according to the refractive index changing, has decreased to zero for RP. After that, circular polarization (CP) has been introduced to get a spot size less than ?. This image resolution improving can be applied to enhance optical data storage, microscopes and lithographic and other high accurate optical systems.

Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms

NASA Astrophysics Data System (ADS)

Rui, Xue; Cheng, Lishui; Long, Yong; Fu, Lin; Alessio, Adam M.; Asma, Evren; Kinahan, Paul E.; De Man, Bruno

2015-09-01

For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition. We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 s. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.043 75 mAs, were investigated. Both the analytical Feldkamp, Davis and Kress (FDK) algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality. With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose levels simulated, sparse view protocols with 41 and 24 views best balanced the tradeoff between electronic noise and aliasing artifacts. In terms of lesion activity error and ensemble RMSE of the PET images, these two protocols, when combined with MBIR, are able to provide results that are comparable to the baseline full dose CT scan. View interpolation significantly improves the performance of FDK reconstruction but was not necessary for MBIR. With the more technically feasible continuous exposure data acquisition, the CT images show an increase in azimuthal blur compared to tube pulsing. However, this blurring generally does not have a measureable impact on PET reconstructed images. Our simulations demonstrated that ultra-low-dose CT-based attenuation correction can be achieved at dose levels on the order of 0.044 mAs with little impact on PET image quality. Highly sparse 41- or 24- view ultra-low dose CT scans are feasible for PET attenuation correction, providing the best tradeoff between electronic noise and view aliasing artifacts. The continuous exposure acquisition mode could potentially be implemented in current commercially available scanners, thus enabling sparse view data acquisition without requiring x-ray tubes capable of operating in a pulsing mode.

Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms

PubMed Central

Rui, Xue; Cheng, Lishui; Long, Yong; Fu, Lin; Alessio, Adam M.; Asma, Evren; Kinahan, Paul E.; De Man, Bruno

2015-01-01

For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition. Methods We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 seconds. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.04375 mAs, were investigated. Both the analytical FDK algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality. Results With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose levels simulated, sparse view protocols with 41 and 24 views best balanced the tradeoff between electronic noise and aliasing artifacts. In terms of lesion activity error and ensemble RMSE of the PET images, these two protocols, when combined with MBIR, are able to provide results that are comparable to the baseline full dose CT scan. View interpolation significantly improves the performance of FDK reconstruction but was not necessary for MBIR. With the more technically feasible continuous exposure data acquisition, the CT images show an increase in azimuthal blur compared to tube pulsing. However, this blurring generally does not have a measureable impact on PET reconstructed images. Conclusions Our simulations demonstrated that ultra-low-dose CT-based attenuation correction can be achieved at dose levels on the order of 0.044 mAs with little impact on PET image quality. Highly sparse 41- or 24- view ultra-low dose CT scans are feasible for PET attenuation correction, providing the best tradeoff between electronic noise and view aliasing artifacts. The continuous exposure acquisition mode could potentially be implemented in current commercially available scanners, thus enabling sparse view data acquisition without requiring x-ray tubes capable of operating in a pulsing mode. PMID:26352168

Optical computing.

NASA Technical Reports Server (NTRS)

Stroke, G. W.

1972-01-01

Applications of the optical computer include an approach for increasing the sharpness of images obtained from the most powerful electron microscopes and fingerprint/credit card identification. The information-handling capability of the various optical computing processes is very great. Modern synthetic-aperture radars scan upward of 100,000 resolvable elements per second. Fields which have assumed major importance on the basis of optical computing principles are optical image deblurring, coherent side-looking synthetic-aperture radar, and correlative pattern recognition. Some examples of the most dramatic image deblurring results are shown.

Quality parameters analysis of optical imaging systems with enhanced focal depth using the Wigner distribution function

PubMed

Zalvidea; Colautti; Sicre

2000-05-01

An analysis of the Strehl ratio and the optical transfer function as imaging quality parameters of optical elements with enhanced focal length is carried out by employing the Wigner distribution function. To this end, we use four different pupil functions: a full circular aperture, a hyper-Gaussian aperture, a quartic phase plate, and a logarithmic phase mask. A comparison is performed between the quality parameters and test images formed by these pupil functions at different defocus distances.

High Resolution Full-Aperture ISAR Processing through Modified Doppler History Based Motion Compensation

PubMed Central

Song, Jung-Hwan; Lee, Kee-Woong; Lee, Woo-Kyung; Jung, Chul-Ho

2017-01-01

A high resolution inverse synthetic aperture radar (ISAR) technique is presented using modified Doppler history based motion compensation. To this purpose, a novel wideband ISAR system is developed that accommodates parametric processing over extended aperture length. The proposed method is derived from an ISAR-to-SAR approach that makes use of high resolution spotlight SAR and sub-aperture recombination. It is dedicated to wide aperture ISAR imaging and exhibits robust performance against unstable targets having non-linear motions. We demonstrate that the Doppler histories of the full aperture ISAR echoes from disturbed targets are efficiently retrieved with good fitting models. Experiments have been conducted on real aircraft targets and the feasibility of the full aperture ISAR processing is verified through the acquisition of high resolution ISAR imagery. PMID:28555036

Imaging through strong turbulence with a light field approach.

PubMed

Wu, Chensheng; Ko, Jonathan; Davis, Christopher C

2016-05-30

Under strong turbulence conditions, object's images can be severely distorted and become unrecognizable throughout the observing time. Conventional image restoring algorithms do not perform effectively in these circumstances due to the loss of good references on the object. We propose the use a plenoptic sensor as a light field camera to map a conventional camera image onto a cell image array in the image's sub-angular spaces. Accordingly, each cell image on the plenoptic sensor is equivalent to the image acquired by a sub-aperture of the imaging lens. The wavefront distortion over the lens aperture can be analyzed by comparing cell images in the plenoptic sensor. By using a modified "Laplacian" metric, we can identify a good cell image in a plenoptic image sequence. The good cell image corresponds with the time and sub-aperture area on the imaging lens where wavefront distortion becomes relatively and momentarily "flat". As a result, it will reveal the fundamental truths of the object that would be severely distorted on normal cameras. In this paper, we will introduce the underlying physics principles and mechanisms of our approach and experimentally demonstrate its effectiveness under strong turbulence conditions. In application, our approach can be used to provide a good reference for conventional image restoring approaches under strong turbulence conditions. This approach can also be used as an independent device to perform object recognition tasks through severe turbulence distortions.

Temporally-Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer’s Disease

PubMed Central

Jie, Biao; Liu, Mingxia; Liu, Jun

2016-01-01

Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer’s disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). However, most existing sparse learning-based studies only adopt cross-sectional analysis methods, where the sparse model is learned using data from a single time-point. Actually, multiple time-points of data are often available in brain imaging applications, which can be used in some longitudinal analysis methods to better uncover the disease progression patterns. Accordingly, in this paper we propose a novel temporally-constrained group sparse learning method aiming for longitudinal analysis with multiple time-points of data. Specifically, we learn a sparse linear regression model by using the imaging data from multiple time-points, where a group regularization term is first employed to group the weights for the same brain region across different time-points together. Furthermore, to reflect the smooth changes between data derived from adjacent time-points, we incorporate two smoothness regularization terms into the objective function, i.e., one fused smoothness term which requires that the differences between two successive weight vectors from adjacent time-points should be small, and another output smoothness term which requires the differences between outputs of two successive models from adjacent time-points should also be small. We develop an efficient optimization algorithm to solve the proposed objective function. Experimental results on ADNI database demonstrate that, compared with conventional sparse learning-based methods, our proposed method can achieve improved regression performance and also help in discovering disease-related biomarkers. PMID:27093313

ℓ0 -based sparse hyperspectral unmixing using spectral information and a multi-objectives formulation

NASA Astrophysics Data System (ADS)

Xu, Xia; Shi, Zhenwei; Pan, Bin

2018-07-01

Sparse unmixing aims at recovering pure materials from hyperpspectral images and estimating their abundance fractions. Sparse unmixing is actually ℓ0 problem which is NP-h ard, and a relaxation is often used. In this paper, we attempt to deal with ℓ0 problem directly via a multi-objective based method, which is a non-convex manner. The characteristics of hyperspectral images are integrated into the proposed method, which leads to a new spectra and multi-objective based sparse unmixing method (SMoSU). In order to solve the ℓ0 norm optimization problem, the spectral library is encoded in a binary vector, and a bit-wise flipping strategy is used to generate new individuals in the evolution process. However, a multi-objective method usually produces a number of non-dominated solutions, while sparse unmixing requires a single solution. How to make the final decision for sparse unmixing is challenging. To handle this problem, we integrate the spectral characteristic of hyperspectral images into SMoSU. By considering the spectral correlation in hyperspectral data, we improve the Tchebycheff decomposition function in SMoSU via a new regularization item. This regularization item is able to enforce the individual divergence in the evolution process of SMoSU. In this way, the diversity and convergence of population is further balanced, which is beneficial to the concentration of individuals. In the experiments part, three synthetic datasets and one real-world data are used to analyse the effectiveness of SMoSU, and several state-of-art sparse unmixing algorithms are compared.

Optical aperture synthesis: limitations and interest for the earth observation

NASA Astrophysics Data System (ADS)

Brouard, Laurent; Safa, Frederic; Crombez, Vincent; Laubier, David

2017-11-01

For very large telescope diameters, typically above 4 meters, monolithic telescopes can hardly be envisaged for space applications. Optical aperture synthesis can be envisaged in the future for improving the image resolution from high altitude orbits by co-phasing several individual telescopes of smaller size and reconstituting an aperture of large surface. The telescopes can be deployed on a single spacecraft or distributed on several spacecrafts in free flying formation. Several future projects are based on optical aperture synthesis for science or earth observation. This paper specifically discusses the limitations and interest of aperture synthesis technique for Earth observation from high altitude orbits, in particular geostationary orbit. Classical Fizeau and Michelson configurations are recalled, and system design aspects are investigated: synthesis of the Modulation Transfer Function (MTF), integration time and imaging procedure are first discussed then co-phasing strategies and instrument metrology are developed. The discussion is supported by specific designs made at EADS Astrium. As example, a telescope design is presented with a surface of only 6.6 m2 for the primary mirror for an external diameter of 10.6 m allowing a theoretical resolution of 1.2 m from geostationary orbit with a surface lower than 10% of the overall surface. The impact is that the integration time is increasing leading to stringent satellite attitude requirements. Image simulation results are presented. The practical implementation of the concept is evaluated in terms of system impacts in particular spacecraft attitude control, spacecraft operations and imaging capability limitations.

Imaging Analysis of the Hard X-Ray Telescope ProtoEXIST2 and New Techniques for High-Resolution Coded-Aperture Telescopes

NASA Technical Reports Server (NTRS)

Hong, Jaesub; Allen, Branden; Grindlay, Jonathan; Barthelmy, Scott D.

2016-01-01

Wide-field (greater than or approximately equal to 100 degrees squared) hard X-ray coded-aperture telescopes with high angular resolution (greater than or approximately equal to 2 minutes) will enable a wide range of time domain astrophysics. For instance, transient sources such as gamma-ray bursts can be precisely localized without the assistance of secondary focusing X-ray telescopes to enable rapid followup studies. On the other hand, high angular resolution in coded-aperture imaging introduces a new challenge in handling the systematic uncertainty: the average photon count per pixel is often too small to establish a proper background pattern or model the systematic uncertainty in a timescale where the model remains invariant. We introduce two new techniques to improve detection sensitivity, which are designed for, but not limited to, a high-resolution coded-aperture system: a self-background modeling scheme which utilizes continuous scan or dithering operations, and a Poisson-statistics based probabilistic approach to evaluate the significance of source detection without subtraction in handling the background. We illustrate these new imaging analysis techniques in high resolution coded-aperture telescope using the data acquired by the wide-field hard X-ray telescope ProtoEXIST2 during a high-altitude balloon flight in fall 2012. We review the imaging sensitivity of ProtoEXIST2 during the flight, and demonstrate the performance of the new techniques using our balloon flight data in comparison with a simulated ideal Poisson background.

Holographic metasurface systems for beam-forming and imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Smith, David R.

2016-09-01

Metamaterials offer an alternative perspective for the design of new materials and devices. The advantage of the metamaterial description is that certain device solutions can more easily be recognized. Here, we discuss broadly the impact of the metamaterial design philosophy on quasi-optical apertures based on patterned holographic metasurfaces. In a guided wave format, in which radiating complementary metamaterial irises are patterned on the upper plate of a microstrip or parallel plate waveguide, the reference wave is equivalent to the guided wave and the entire structure becomes a compact, efficient holographic, aperture antenna. We have developed a millimeter-wave imaging system that makes use of a set of complementary metamaterial waveguide panels to form a frequency-diverse aperture. In this context, the metamaterial aperture produces a complex radiation pattern that varies spatially as a function of the driving frequency; a frequency sweep over a selected bandwidth thus illuminates a region of space with a set of distinct radiation patterns. Collecting the returned signal reflected by illuminated objects within the scene, a set of measurements can be made from which an image of the scene can be reconstructed. This imaging application provides a useful example of the introduction, integration and optimization of a metamaterial aperture into a complete system, where all other aspects of the system—including algorithms, calibration, software and electronics—must be tailored for the particulars of the metamaterial component. As metamaterials transition from science to technology, these aspects may prove just as challenging and interesting as the underlying metamaterial components.

Automatic segmentation of right ventricle on ultrasound images using sparse matrix transform and level set

NASA Astrophysics Data System (ADS)

Qin, Xulei; Cong, Zhibin; Halig, Luma V.; Fei, Baowei

2013-03-01

An automatic framework is proposed to segment right ventricle on ultrasound images. This method can automatically segment both epicardial and endocardial boundaries from a continuous echocardiography series by combining sparse matrix transform (SMT), a training model, and a localized region based level set. First, the sparse matrix transform extracts main motion regions of myocardium as eigenimages by analyzing statistical information of these images. Second, a training model of right ventricle is registered to the extracted eigenimages in order to automatically detect the main location of the right ventricle and the corresponding transform relationship between the training model and the SMT-extracted results in the series. Third, the training model is then adjusted as an adapted initialization for the segmentation of each image in the series. Finally, based on the adapted initializations, a localized region based level set algorithm is applied to segment both epicardial and endocardial boundaries of the right ventricle from the whole series. Experimental results from real subject data validated the performance of the proposed framework in segmenting right ventricle from echocardiography. The mean Dice scores for both epicardial and endocardial boundaries are 89.1%+/-2.3% and 83.6+/-7.3%, respectively. The automatic segmentation method based on sparse matrix transform and level set can provide a useful tool for quantitative cardiac imaging.

Mosaic of coded aperture arrays

DOEpatents

Fenimore, Edward E.; Cannon, Thomas M.

1980-01-01

The present invention pertains to a mosaic of coded aperture arrays which is capable of imaging off-axis sources with minimum detector size. Mosaics of the basic array pattern create a circular on periodic correlation of the object on a section of the picture plane. This section consists of elements of the central basic pattern as well as elements from neighboring patterns and is a cyclic version of the basic pattern. Since all object points contribute a complete cyclic version of the basic pattern, a section of the picture, which is the size of the basic aperture pattern, contains all the information necessary to image the object with no artifacts.

Compressive hyperspectral and multispectral imaging fusion

NASA Astrophysics Data System (ADS)

Espitia, Óscar; Castillo, Sergio; Arguello, Henry

2016-05-01

Image fusion is a valuable framework which combines two or more images of the same scene from one or multiple sensors, allowing to improve the resolution of the images and increase the interpretable content. In remote sensing a common fusion problem consists of merging hyperspectral (HS) and multispectral (MS) images that involve large amount of redundant data, which ignores the highly correlated structure of the datacube along the spatial and spectral dimensions. Compressive HS and MS systems compress the spectral data in the acquisition step allowing to reduce the data redundancy by using different sampling patterns. This work presents a compressed HS and MS image fusion approach, which uses a high dimensional joint sparse model. The joint sparse model is formulated by combining HS and MS compressive acquisition models. The high spectral and spatial resolution image is reconstructed by using sparse optimization algorithms. Different fusion spectral image scenarios are used to explore the performance of the proposed scheme. Several simulations with synthetic and real datacubes show promising results as the reliable reconstruction of a high spectral and spatial resolution image can be achieved by using as few as just the 50% of the datacube.

High-Resolution X-Ray Telescopes

NASA Technical Reports Server (NTRS)

ODell, Stephen L.; Brissenden, Roger J.; Davis, William; Elsner, Ronald F.; Elvis, Martin; Freeman, Mark; Gaetz, Terry; Gorenstein, Paul; Gubarev, Mikhail V.

2010-01-01

Fundamental needs for future x-ray telescopes: a) Sharp images => excellent angular resolution. b) High throughput => large aperture areas. Generation-X optics technical challenges: a) High resolution => precision mirrors & alignment. b) Large apertures => lots of lightweight mirrors. Innovation needed for technical readiness: a) 4 top-level error terms contribute to image size. b) There are approaches to controlling those errors. Innovation needed for manufacturing readiness. Programmatic issues are comparably challenging.

Sparse models for correlative and integrative analysis of imaging and genetic data

PubMed Central

Lin, Dongdong; Cao, Hongbao; Calhoun, Vince D.

2014-01-01

The development of advanced medical imaging technologies and high-throughput genomic measurements has enhanced our ability to understand their interplay as well as their relationship with human behavior by integrating these two types of datasets. However, the high dimensionality and heterogeneity of these datasets presents a challenge to conventional statistical methods; there is a high demand for the development of both correlative and integrative analysis approaches. Here, we review our recent work on developing sparse representation based approaches to address this challenge. We show how sparse models are applied to the correlation and integration of imaging and genetic data for biomarker identification. We present examples on how these approaches are used for the detection of risk genes and classification of complex diseases such as schizophrenia. Finally, we discuss future directions on the integration of multiple imaging and genomic datasets including their interactions such as epistasis. PMID:25218561

Color Sparse Representations for Image Processing: Review, Models, and Prospects.

PubMed

Barthélemy, Quentin; Larue, Anthony; Mars, Jérôme I

2015-11-01

Sparse representations have been extended to deal with color images composed of three channels. A review of dictionary-learning-based sparse representations for color images is made here, detailing the differences between the models, and comparing their results on the real and simulated data. These models are considered in a unifying framework that is based on the degrees of freedom of the linear filtering/transformation of the color channels. Moreover, this allows it to be shown that the scalar quaternionic linear model is equivalent to constrained matrix-based color filtering, which highlights the filtering implicitly applied through this model. Based on this reformulation, the new color filtering model is introduced, using unconstrained filters. In this model, spatial morphologies of color images are encoded by atoms, and colors are encoded by color filters. Color variability is no longer captured in increasing the dictionary size, but with color filters, this gives an efficient color representation.

Sparse representation based image interpolation with nonlocal autoregressive modeling.

PubMed

Dong, Weisheng; Zhang, Lei; Lukac, Rastislav; Shi, Guangming

2013-04-01

Sparse representation is proven to be a promising approach to image super-resolution, where the low-resolution (LR) image is usually modeled as the down-sampled version of its high-resolution (HR) counterpart after blurring. When the blurring kernel is the Dirac delta function, i.e., the LR image is directly down-sampled from its HR counterpart without blurring, the super-resolution problem becomes an image interpolation problem. In such cases, however, the conventional sparse representation models (SRM) become less effective, because the data fidelity term fails to constrain the image local structures. In natural images, fortunately, many nonlocal similar patches to a given patch could provide nonlocal constraint to the local structure. In this paper, we incorporate the image nonlocal self-similarity into SRM for image interpolation. More specifically, a nonlocal autoregressive model (NARM) is proposed and taken as the data fidelity term in SRM. We show that the NARM-induced sampling matrix is less coherent with the representation dictionary, and consequently makes SRM more effective for image interpolation. Our extensive experimental results demonstrate that the proposed NARM-based image interpolation method can effectively reconstruct the edge structures and suppress the jaggy/ringing artifacts, achieving the best image interpolation results so far in terms of PSNR as well as perceptual quality metrics such as SSIM and FSIM.

An efficient dictionary learning algorithm and its application to 3-D medical image denoising.

PubMed

Li, Shutao; Fang, Leyuan; Yin, Haitao

2012-02-01

In this paper, we propose an efficient dictionary learning algorithm for sparse representation of given data and suggest a way to apply this algorithm to 3-D medical image denoising. Our learning approach is composed of two main parts: sparse coding and dictionary updating. On the sparse coding stage, an efficient algorithm named multiple clusters pursuit (MCP) is proposed. The MCP first applies a dictionary structuring strategy to cluster the atoms with high coherence together, and then employs a multiple-selection strategy to select several competitive atoms at each iteration. These two strategies can greatly reduce the computation complexity of the MCP and assist it to obtain better sparse solution. On the dictionary updating stage, the alternating optimization that efficiently approximates the singular value decomposition is introduced. Furthermore, in the 3-D medical image denoising application, a joint 3-D operation is proposed for taking the learning capabilities of the presented algorithm to simultaneously capture the correlations within each slice and correlations across the nearby slices, thereby obtaining better denoising results. The experiments on both synthetically generated data and real 3-D medical images demonstrate that the proposed approach has superior performance compared to some well-known methods. © 2011 IEEE

Nonlocal low-rank and sparse matrix decomposition for spectral CT reconstruction

NASA Astrophysics Data System (ADS)

Niu, Shanzhou; Yu, Gaohang; Ma, Jianhua; Wang, Jing

2018-02-01

Spectral computed tomography (CT) has been a promising technique in research and clinics because of its ability to produce improved energy resolution images with narrow energy bins. However, the narrow energy bin image is often affected by serious quantum noise because of the limited number of photons used in the corresponding energy bin. To address this problem, we present an iterative reconstruction method for spectral CT using nonlocal low-rank and sparse matrix decomposition (NLSMD), which exploits the self-similarity of patches that are collected in multi-energy images. Specifically, each set of patches can be decomposed into a low-rank component and a sparse component, and the low-rank component represents the stationary background over different energy bins, while the sparse component represents the rest of the different spectral features in individual energy bins. Subsequently, an effective alternating optimization algorithm was developed to minimize the associated objective function. To validate and evaluate the NLSMD method, qualitative and quantitative studies were conducted by using simulated and real spectral CT data. Experimental results show that the NLSMD method improves spectral CT images in terms of noise reduction, artifact suppression and resolution preservation.

Optimal apodization design for medical ultrasound using constrained least squares part I: theory.

PubMed

Guenther, Drake A; Walker, William F

2007-02-01

Aperture weighting functions are critical design parameters in the development of ultrasound systems because beam characteristics affect the contrast and point resolution of the final output image. In previous work by our group, we developed a metric that quantifies a broadband imaging system's contrast resolution performance. We now use this metric to formulate a novel general ultrasound beamformer design method. In our algorithm, we use constrained least squares (CLS) techniques and a linear algebra formulation to describe the system point spread function (PSF) as a function of the aperture weightings. In one approach, we minimize the energy of the PSF outside a certain boundary and impose a linear constraint on the aperture weights. In a second approach, we minimize the energy of the PSF outside a certain boundary while imposing a quadratic constraint on the energy of the PSF inside the boundary. We present detailed analysis for an arbitrary ultrasound imaging system and discuss several possible applications of the CLS techniques, such as designing aperture weightings to maximize contrast resolution and improve the system depth of field.

A user's manual for the NASA/JPL synthetic aperture radar and the NASA/JPL L and C band scatterometers

NASA Technical Reports Server (NTRS)

Thompson, T. W.

1983-01-01

Airborne synthetic aperture radars and scatterometers are operated with the goals of acquiring data to support shuttle imaging radars and support ongoing basic active microwave remote sensing research. The aircraft synthetic aperture radar is an L-band system at the 25-cm wavelength and normally operates on the CV-990 research aircraft. This radar system will be upgraded to operate at both the L-band and C-band. The aircraft scatterometers are two independent radar systems that operate at 6.3-cm and 18.8-cm wavelengths. They are normally flown on the C-130 research aircraft. These radars will be operated on 10 data flights each year to provide data to NASA-approved users. Data flights will be devoted to Shuttle Imaging Radar-B (SIR-B) underflights. Standard data products for the synthetic aperture radars include both optical and digital images. Standard data products for the scatterometers include computer compatible tapes with listings of radar cross sections (sigma-nought) versus angle of incidence. An overview of these radars and their operational procedures is provided by this user's manual.

Stabilizing laser energy density on a target during pulsed laser deposition of thin films

DOEpatents

Dowden, Paul C.; Jia, Quanxi

2016-05-31

A process for stabilizing laser energy density on a target surface during pulsed laser deposition of thin films controls the focused laser spot on the target. The process involves imaging an image-aperture positioned in the beamline. This eliminates changes in the beam dimensions of the laser. A continuously variable attenuator located in between the output of the laser and the imaged image-aperture adjusts the energy to a desired level by running the laser in a "constant voltage" mode. The process provides reproducibility and controllability for deposition of electronic thin films by pulsed laser deposition.

Attitude-error compensation for airborne down-looking synthetic-aperture imaging lidar

NASA Astrophysics Data System (ADS)

Li, Guang-yuan; Sun, Jian-feng; Zhou, Yu; Lu, Zhi-yong; Zhang, Guo; Cai, Guang-yu; Liu, Li-ren

2017-11-01

Target-coordinate transformation in the lidar spot of the down-looking synthetic-aperture imaging lidar (SAIL) was performed, and the attitude errors were deduced in the process of imaging, according to the principle of the airborne down-looking SAIL. The influence of the attitude errors on the imaging quality was analyzed theoretically. A compensation method for the attitude errors was proposed and theoretically verified. An airborne down-looking SAIL experiment was performed and yielded the same results. A point-by-point error-compensation method for solving the azimuthal-direction space-dependent attitude errors was also proposed.

In vivo imaging of retinal pigment epithelium cells in age related macular degeneration

PubMed Central

Rossi, Ethan A.; Rangel-Fonseca, Piero; Parkins, Keith; Fischer, William; Latchney, Lisa R.; Folwell, Margaret A.; Williams, David R.; Dubra, Alfredo; Chung, Mina M.

2013-01-01

Morgan and colleagues demonstrated that the RPE cell mosaic can be resolved in the living human eye non-invasively by imaging the short-wavelength autofluorescence using an adaptive optics (AO) ophthalmoscope. This method, based on the assumption that all subjects have the same longitudinal chromatic aberration (LCA) correction, has proved difficult to use in diseased eyes, and in particular those affected by age-related macular degeneration (AMD). In this work, we improve Morgan’s method by accounting for chromatic aberration variations by optimizing the confocal aperture axial and transverse placement through an automated iterative maximization of image intensity. The increase in image intensity after algorithmic aperture placement varied depending upon patient and aperture position prior to optimization but increases as large as a factor of 10 were observed. When using a confocal aperture of 3.4 Airy disks in diameter, images were obtained using retinal radiant exposures of less than 2.44 J/cm2, which is ~22 times below the current ANSI maximum permissible exposure. RPE cell morphologies that were strikingly similar to those seen in postmortem histological studies were observed in AMD eyes, even in areas where the pattern of fluorescence appeared normal in commercial fundus autofluorescence (FAF) images. This new method can be used to study RPE morphology in AMD and other diseases, providing a powerful tool for understanding disease pathogenesis and progression, and offering a new means to assess the efficacy of treatments designed to restore RPE health. PMID:24298413

Advances in combined endoscopic fluorescence confocal microscopy and optical coherence tomography

NASA Astrophysics Data System (ADS)

Risi, Matthew D.

Confocal microendoscopy provides real-time high resolution cellular level images via a minimally invasive procedure. Results from an ongoing clinical study to detect ovarian cancer with a novel confocal fluorescent microendoscope are presented. As an imaging modality, confocal fluorescence microendoscopy typically requires exogenous fluorophores, has a relatively limited penetration depth (100 μm), and often employs specialized aperture configurations to achieve real-time imaging in vivo. Two primary research directions designed to overcome these limitations and improve diagnostic capability are presented. Ideal confocal imaging performance is obtained with a scanning point illumination and confocal aperture, but this approach is often unsuitable for real-time, in vivo biomedical imaging. By scanning a slit aperture in one direction, image acquisition speeds are greatly increased, but at the cost of a reduction in image quality. The design, implementation, and experimental verification of a custom multi-point-scanning modification to a slit-scanning multi-spectral confocal microendoscope is presented. This new design improves the axial resolution while maintaining real-time imaging rates. In addition, the multi-point aperture geometry greatly reduces the effects of tissue scatter on imaging performance. Optical coherence tomography (OCT) has seen wide acceptance and FDA approval as a technique for ophthalmic retinal imaging, and has been adapted for endoscopic use. As a minimally invasive imaging technique, it provides morphological characteristics of tissues at a cellular level without requiring the use of exogenous fluorophores. OCT is capable of imaging deeper into biological tissue (˜1-2 mm) than confocal fluorescence microscopy. A theoretical analysis of the use of a fiber-bundle in spectral-domain OCT systems is presented. The fiber-bundle enables a flexible endoscopic design and provides fast, parallelized acquisition of the optical coherence tomography data. However, the multi-mode characteristic of the fibers in the fiber-bundle affects the depth sensitivity of the imaging system. A description of light interference in a multi-mode fiber is presented along with numerical simulations and experimental studies to illustrate the theoretical analysis.

Ultra-low dose quantitative CT myocardial perfusion imaging with sparse-view dynamic acquisition and image reconstruction: A feasibility study.

PubMed

Enjilela, Esmaeil; Lee, Ting-Yim; Hsieh, Jiang; Wisenberg, Gerald; Teefy, Patrick; Yadegari, Andrew; Bagur, Rodrigo; Islam, Ali; Branch, Kelley; So, Aaron

2018-03-01

We implemented and validated a compressed sensing (CS) based algorithm for reconstructing dynamic contrast-enhanced (DCE) CT images of the heart from sparsely sampled X-ray projections. DCE CT imaging of the heart was performed on five normal and ischemic pigs after contrast injection. DCE images were reconstructed with filtered backprojection (FBP) and CS from all projections (984-view) and 1/3 of all projections (328-view), and with CS from 1/4 of all projections (246-view). Myocardial perfusion (MP) measurements with each protocol were compared to those with the reference 984-view FBP protocol. Both the 984-view CS and 328-view CS protocols were in good agreements with the reference protocol. The Pearson correlation coefficients of 984-view CS and 328-view CS determined from linear regression analyses were 0.98 and 0.99 respectively. The corresponding mean biases of MP measurement determined from Bland-Altman analyses were 2.7 and 1.2ml/min/100g. When only 328 projections were used for image reconstruction, CS was more accurate than FBP for MP measurement with respect to 984-view FBP. However, CS failed to generate MP maps comparable to those with 984-view FBP when only 246 projections were used for image reconstruction. DCE heart images reconstructed from one-third of a full projection set with CS were minimally affected by aliasing artifacts, leading to accurate MP measurements with the effective dose reduced to just 33% of conventional full-view FBP method. The proposed CS sparse-view image reconstruction method could facilitate the implementation of sparse-view dynamic acquisition for ultra-low dose CT MP imaging. Copyright © 2017 Elsevier B.V. All rights reserved.

Ultra-compact imaging system based on multi-aperture architecture

NASA Astrophysics Data System (ADS)

Meyer, Julia; Brückner, Andreas; Leitel, Robert; Dannberg, Peter; Bräuer, Andreas; Tünnermann, Andreas

2011-03-01

As a matter of course, cameras are integrated in the field of information and communication technology. It can be observed, that there is a trend that those cameras get smaller and at the same time cheaper. Because single aperture have a limit of miniaturization, while simultaneously keeping the same space-bandwidth-product and transmitting a wide field of view, there is a need of new ideas like the multi aperture optical systems. In the proposed camera system the image is formed with many different channels each consisting of four microlenses which are arranged one after another in different microlens arrays. A partial image which fits together with the neighbouring one is formed in every single channel, so that a real erect image is generated and a conventional image sensor can be used. The microoptical fabrication process and the assembly are well established and can be carried out on wafer-level. Laser writing is used for the fabrication of the masks. UV-lithography, a reflow process and UV-molding is needed for the fabrication of the apertures and the lenses. The developed system is very small in terms of both length and lateral dimensions and has a VGA resolution and a diagonal field of view of 65 degrees. This microoptical vision system is appropriate for being implemented in electronic devices such as webcams integrated in notebookdisplays.

Embedded electronics for a video-rate distributed aperture passive millimeter-wave imager

NASA Astrophysics Data System (ADS)

Curt, Petersen F.; Bonnett, James; Schuetz, Christopher A.; Martin, Richard D.

2013-05-01

Optical upconversion for a distributed aperture millimeter wave imaging system is highly beneficial due to its superior bandwidth and limited susceptibility to EMI. These features mean the same technology can be used to collect information across a wide spectrum, as well as in harsh environments. Some practical uses of this technology include safety of flight in degraded visual environments (DVE), imaging through smoke and fog, and even electronic warfare. Using fiber-optics in the distributed aperture poses a particularly challenging problem with respect to maintaining coherence of the information between channels. In order to capture an image, the antenna aperture must be electronically steered and focused to a particular distance. Further, the state of the phased array must be maintained, even as environmental factors such as vibration, temperature and humidity adversely affect the propagation of the signals through the optical fibers. This phenomenon cannot be avoided or mitigated, but rather must be compensated for using a closed-loop control system. In this paper, we present an implementation of embedded electronics designed specifically for this purpose. This novel architecture is efficiently small, scalable to many simultaneously operating channels and sufficiently robust. We present our results, which include integration into a 220 channel imager and phase stability measurements as the system is stressed according to MIL-STD-810F vibration profiles of an H-53E heavy-lift helicopter.

Design quadrilateral apertures in binary computer-generated holograms of large space bandwidth product.

PubMed

Wang, Jing; Sheng, Yunlong

2016-09-20

A new approach for designing the binary computer-generated hologram (CGH) of a very large number of pixels is proposed. Diffraction of the CGH apertures is computed by the analytical Abbe transform and by considering the aperture edges as the basic diffracting elements. The computation cost is independent of the CGH size. The arbitrary-shaped polygonal apertures in the CGH consist of quadrilateral apertures, which are designed by assigning the binary phases using the parallel genetic algorithm with a local search, followed by optimizing the locations of the co-vertices with a direct search. The design results in high performance with low image reconstruction error.

Multiple-image encryption via lifting wavelet transform and XOR operation based on compressive ghost imaging scheme

NASA Astrophysics Data System (ADS)

Li, Xianye; Meng, Xiangfeng; Yang, Xiulun; Wang, Yurong; Yin, Yongkai; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2018-03-01

A multiple-image encryption method via lifting wavelet transform (LWT) and XOR operation is proposed, which is based on a row scanning compressive ghost imaging scheme. In the encryption process, the scrambling operation is implemented for the sparse images transformed by LWT, then the XOR operation is performed on the scrambled images, and the resulting XOR images are compressed in the row scanning compressive ghost imaging, through which the ciphertext images can be detected by bucket detector arrays. During decryption, the participant who possesses his/her correct key-group, can successfully reconstruct the corresponding plaintext image by measurement key regeneration, compression algorithm reconstruction, XOR operation, sparse images recovery, and inverse LWT (iLWT). Theoretical analysis and numerical simulations validate the feasibility of the proposed method.

Passive synthetic aperture radar imaging of ground moving targets

NASA Astrophysics Data System (ADS)

Wacks, Steven; Yazici, Birsen

2012-05-01

In this paper we present a method for imaging ground moving targets using passive synthetic aperture radar. A passive radar imaging system uses small, mobile receivers that do not radiate any energy. For these reasons, passive imaging systems result in signicant cost, manufacturing, and stealth advantages. The received signals are obtained by multiple airborne receivers collecting scattered waves due to illuminating sources of opportunity such as commercial television, radio, and cell phone towers. We describe a novel forward model and a corresponding ltered-backprojection type image reconstruction method combined with entropy optimization. Our method determines the location and velocity of multiple targets moving at dierent velocities. Furthermore, it can accommodate arbitrary imaging geometries. we present numerical simulations to verify the imaging method.

A versatile calibration procedure for portable coded aperture gamma cameras and RGB-D sensors

NASA Astrophysics Data System (ADS)

Paradiso, V.; Crivellaro, A.; Amgarou, K.; de Lanaute, N. Blanc; Fua, P.; Liénard, E.

2018-04-01

The present paper proposes a versatile procedure for the geometrical calibration of coded aperture gamma cameras and RGB-D depth sensors, using only one radioactive point source and a simple experimental set-up. Calibration data is then used for accurately aligning radiation images retrieved by means of the γ-camera with the respective depth images computed with the RGB-D sensor. The system resulting from such a combination is thus able to retrieve, automatically, the distance of radioactive hotspots by means of pixel-wise mapping between gamma and depth images. This procedure is of great interest for a wide number of applications, ranging from precise automatic estimation of the shape and distance of radioactive objects to Augmented Reality systems. Incidentally, the corresponding results validated the choice of a perspective design model for a coded aperture γ-camera.

Task-based data-acquisition optimization for sparse image reconstruction systems

NASA Astrophysics Data System (ADS)

Chen, Yujia; Lou, Yang; Kupinski, Matthew A.; Anastasio, Mark A.

2017-03-01

Conventional wisdom dictates that imaging hardware should be optimized by use of an ideal observer (IO) that exploits full statistical knowledge of the class of objects to be imaged, without consideration of the reconstruction method to be employed. However, accurate and tractable models of the complete object statistics are often difficult to determine in practice. Moreover, in imaging systems that employ compressive sensing concepts, imaging hardware and (sparse) image reconstruction are innately coupled technologies. We have previously proposed a sparsity-driven ideal observer (SDIO) that can be employed to optimize hardware by use of a stochastic object model that describes object sparsity. The SDIO and sparse reconstruction method can therefore be "matched" in the sense that they both utilize the same statistical information regarding the class of objects to be imaged. To efficiently compute SDIO performance, the posterior distribution is estimated by use of computational tools developed recently for variational Bayesian inference. Subsequently, the SDIO test statistic can be computed semi-analytically. The advantages of employing the SDIO instead of a Hotelling observer are systematically demonstrated in case studies in which magnetic resonance imaging (MRI) data acquisition schemes are optimized for signal detection tasks.

Computational efficiency improvements for image colorization

NASA Astrophysics Data System (ADS)

Yu, Chao; Sharma, Gaurav; Aly, Hussein

2013-03-01

We propose an efficient algorithm for colorization of greyscale images. As in prior work, colorization is posed as an optimization problem: a user specifies the color for a few scribbles drawn on the greyscale image and the color image is obtained by propagating color information from the scribbles to surrounding regions, while maximizing the local smoothness of colors. In this formulation, colorization is obtained by solving a large sparse linear system, which normally requires substantial computation and memory resources. Our algorithm improves the computational performance through three innovations over prior colorization implementations. First, the linear system is solved iteratively without explicitly constructing the sparse matrix, which significantly reduces the required memory. Second, we formulate each iteration in terms of integral images obtained by dynamic programming, reducing repetitive computation. Third, we use a coarseto- fine framework, where a lower resolution subsampled image is first colorized and this low resolution color image is upsampled to initialize the colorization process for the fine level. The improvements we develop provide significant speedup and memory savings compared to the conventional approach of solving the linear system directly using off-the-shelf sparse solvers, and allow us to colorize images with typical sizes encountered in realistic applications on typical commodity computing platforms.

Thermal response of solar receiver aperture plates during sun walk-off

NASA Technical Reports Server (NTRS)

Wen, L.; Roschke, J.

1982-01-01

The tracking mechanism for a point-focusing concentrator may be subject to failure. If this should occur, the solar image will travel across the aperture plate, and it may also impinge on the adjacent support structure. Such an event is called 'sun walk-off'. The present investigation is concerned with the transient response of different aperture plate materials to the intense heating produced in a typical walk-off situation for parabolic dish concentrators. Receivers for two solar module systems are considered, including a high-temperature receiver that utilizes a 2-milliradian (mrad) concentrator, and a lower-temperature receiver which is coupled with a 4-mrad concentrator. It is found that during a walk-off situation the solar image travels in a straight line in the radial direction. The results obtained for a copper aperture plate were disappointing. It appears that passive metallic plates without cooling or other protective support cannot withstand the intense heating.

Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging.

PubMed

Zhang, Xiaodong; Jing, Shasha; Gao, Peiyi; Xue, Jing; Su, Lu; Li, Weiping; Ren, Lijie; Hu, Qingmao

2016-01-01

Segmentation of infarcts at hyperacute stage is challenging as they exhibit substantial variability which may even be hard for experts to delineate manually. In this paper, a sparse representation based classification method is explored. For each patient, four volumetric data items including three volumes of diffusion weighted imaging and a computed asymmetry map are employed to extract patch features which are then fed to dictionary learning and classification based on sparse representation. Elastic net is adopted to replace the traditional L 0 -norm/ L 1 -norm constraints on sparse representation to stabilize sparse code. To decrease computation cost and to reduce false positives, regions-of-interest are determined to confine candidate infarct voxels. The proposed method has been validated on 98 consecutive patients recruited within 6 hours from onset. It is shown that the proposed method could handle well infarcts with intensity variability and ill-defined edges to yield significantly higher Dice coefficient (0.755 ± 0.118) than the other two methods and their enhanced versions by confining their segmentations within the regions-of-interest (average Dice coefficient less than 0.610). The proposed method could provide a potential tool to quantify infarcts from diffusion weighted imaging at hyperacute stage with accuracy and speed to assist the decision making especially for thrombolytic therapy.

Reducing computational costs in large scale 3D EIT by using a sparse Jacobian matrix with block-wise CGLS reconstruction.

PubMed

Yang, C L; Wei, H Y; Adler, A; Soleimani, M

2013-06-01

Electrical impedance tomography (EIT) is a fast and cost-effective technique to provide a tomographic conductivity image of a subject from boundary current-voltage data. This paper proposes a time and memory efficient method for solving a large scale 3D EIT inverse problem using a parallel conjugate gradient (CG) algorithm. The 3D EIT system with a large number of measurement data can produce a large size of Jacobian matrix; this could cause difficulties in computer storage and the inversion process. One of challenges in 3D EIT is to decrease the reconstruction time and memory usage, at the same time retaining the image quality. Firstly, a sparse matrix reduction technique is proposed using thresholding to set very small values of the Jacobian matrix to zero. By adjusting the Jacobian matrix into a sparse format, the element with zeros would be eliminated, which results in a saving of memory requirement. Secondly, a block-wise CG method for parallel reconstruction has been developed. The proposed method has been tested using simulated data as well as experimental test samples. Sparse Jacobian with a block-wise CG enables the large scale EIT problem to be solved efficiently. Image quality measures are presented to quantify the effect of sparse matrix reduction in reconstruction results.

Estimation of signal-dependent noise level function in transform domain via a sparse recovery model.

PubMed

Yang, Jingyu; Gan, Ziqiao; Wu, Zhaoyang; Hou, Chunping

2015-05-01

This paper proposes a novel algorithm to estimate the noise level function (NLF) of signal-dependent noise (SDN) from a single image based on the sparse representation of NLFs. Noise level samples are estimated from the high-frequency discrete cosine transform (DCT) coefficients of nonlocal-grouped low-variation image patches. Then, an NLF recovery model based on the sparse representation of NLFs under a trained basis is constructed to recover NLF from the incomplete noise level samples. Confidence levels of the NLF samples are incorporated into the proposed model to promote reliable samples and weaken unreliable ones. We investigate the behavior of the estimation performance with respect to the block size, sampling rate, and confidence weighting. Simulation results on synthetic noisy images show that our method outperforms existing state-of-the-art schemes. The proposed method is evaluated on real noisy images captured by three types of commodity imaging devices, and shows consistently excellent SDN estimation performance. The estimated NLFs are incorporated into two well-known denoising schemes, nonlocal means and BM3D, and show significant improvements in denoising SDN-polluted images.

Magnetic resonance brain tissue segmentation based on sparse representations

NASA Astrophysics Data System (ADS)

Rueda, Andrea

2015-12-01

Segmentation or delineation of specific organs and structures in medical images is an important task in the clinical diagnosis and treatment, since it allows to characterize pathologies through imaging measures (biomarkers). In brain imaging, segmentation of main tissues or specific structures is challenging, due to the anatomic variability and complexity, and the presence of image artifacts (noise, intensity inhomogeneities, partial volume effect). In this paper, an automatic segmentation strategy is proposed, based on sparse representations and coupled dictionaries. Image intensity patterns are singly related to tissue labels at the level of small patches, gathering this information in coupled intensity/segmentation dictionaries. This dictionaries are used within a sparse representation framework to find the projection of a new intensity image onto the intensity dictionary, and the same projection can be used with the segmentation dictionary to estimate the corresponding segmentation. Preliminary results obtained with two publicly available datasets suggest that the proposal is capable of estimating adequate segmentations for gray matter (GM) and white matter (WM) tissues, with an average overlapping of 0:79 for GM and 0:71 for WM (with respect to original segmentations).

Determining Snow Depth Using Airborne Multi-Pass Interferometric Synthetic Aperture Radar

DTIC Science & Technology

2013-09-01

relatively low resolution 10m DEM of the survey area was obtained from the USDA NAIP and then geocorrected to match the SAR image area. Centered on...Propulsion Laboratory LiDAR Light Detection and Ranging METAR Meteorological reporting observations medivac Medical Evacuation NASA National...Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X- SAR) mission was a joint National Aeronautical and Space Administration ( NASA

Shuttle synthetic aperture radar implementation study, volume 1. [flight instrument and ground data processor system for collecting raw imaged radar data

NASA Technical Reports Server (NTRS)

Mehlis, J. G.

1976-01-01

Results of an implementation study for a synthetic aperture radar for the space shuttle orbiter are described. The overall effort was directed toward the determination of the feasibility and usefulness of a multifrequency, multipolarization imaging radar for the shuttle orbiter. The radar is intended for earth resource monitoring as well as oceanographic and marine studies.

Tibial tunnel aperture irregularity after drilling with 5 reamer designs: a qualitative micro-computed tomography analysis.

PubMed

Geeslin, Andrew G; Jansson, Kyle S; Wijdicks, Coen A; Chapman, Mark A; Fok, Alex S; LaPrade, Robert F

2011-04-01

There is limited information in the literature on comparisons of antegrade versus retrograde reaming techniques and the effect on the creation of anterior cruciate ligament (ACL) tibial tunnel entry and exit apertures. Proximal and distal apertures of ACL tibial tunnels, as created with different reamers, will be affected by type of reamer design. Controlled laboratory study. Forty skeletally mature porcine tibias with bone mineral density values comparable with a young athletic population were included in this study. Five 9-mm reamer models were used (3 antegrade: A1, smooth-bore reamer; A2, acorn-head reamer; A3, flat-head reamer; 2 retrograde: R1, retrograde acorn reamer; R2, single-blade retrograde reamer), and a new reamer was used for each tibia (8 reamer-tibia pairs per reamer model). All specimens underwent micro-computed tomography scanning, and images were reconstructed and analyzed using 3-dimensional image analysis software. Aperture rim fractures were graded on a 0-IV scale that described the proportion of the fractured aperture circumference. Specimens with incomplete apertures were also recorded. Because of the unique characteristics of various tunnels, intratunnel characteristics were observed and recorded. In sum, 1 proximal and 7 distal aperture rim fractures were found; 3, 0, and 4 distal aperture rim fractures were found with groups A1, A2, and A3, respectively. Incomplete apertures were more commonly found at the distal aperture (n = 15) than the proximal aperture (n = 8); there were no tibias with this finding at both apertures. All incomplete distal apertures occurred with the retrograde technique, and all incomplete proximal apertures occurred with the antegrade technique, most commonly with reamer design A3. An added finding of tunnel curvature at the distal aspect of the tunnel was observed in all 8 tibias with R1 reamers and 5 tibias with R2 reamers. This phenomenon was not observed in any of the tibias reamed with the antegrade technique. Anterior cruciate ligament tibial tunnel aperture characteristics were highly dependent on reamer design. Optimal proximal aperture characteristics were produced by the retrograde reamers, whereas optimal distal aperture characteristics were obtained with the antegrade reamers. In addition, a phenomenon of tunnel curvature in retrograde-type reamers was found, which may have effects on ACL graft or screw fixation. Differences in tunnel aperture shapes and fractures depend on reamer design. This information is important for the creation of ACL reconstruction tunnels with different reamer designs.

Planetary Remote Sensing Science Enabled by MIDAS (Multiple Instrument Distributed Aperture Sensor)

NASA Technical Reports Server (NTRS)

Pitman, Joe; Duncan, Alan; Stubbs, David; Sigler, Robert; Kendrick, Rick; Chilese, John; Lipps, Jere; Manga, Mike; Graham, James; dePater, Imke

2004-01-01

The science capabilities and features of an innovative and revolutionary approach to remote sensing imaging systems, aimed at increasing the return on future space science missions many fold, are described. Our concept, called Multiple Instrument Distributed Aperture Sensor (MIDAS), provides a large-aperture, wide-field, diffraction-limited telescope at a fraction of the cost, mass and volume of conventional telescopes, by integrating optical interferometry technologies into a mature multiple aperture array concept that addresses one of the highest needs for advancing future planetary science remote sensing.

Birefringence of single and bundled microtubules.

PubMed

Oldenbourg, R; Salmon, E D; Tran, P T

1998-01-01

We have measured the birefringence of microtubules (MTs) and of MT-based macromolecular assemblies in vitro and in living cells by using the new Pol-Scope. A single microtubule in aqueous suspension and imaged with a numerical aperture of 1.4 had a peak retardance of 0.07 nm. The peak retardance of a small bundle increased linearly with the number of MTs in the bundle. Axonemes (prepared from sea urchin sperm) had a peak retardance 20 times higher than that of single MTs, in accordance with the nine doublets and two singlets arrangement of parallel MTs in the axoneme. Measured filament retardance decreased when the filament was defocused or the numerical aperture of the imaging system was decreased. However, the retardance "area," which we defined as the image retardance integrated along a line perpendicular to the filament axis, proved to be independent of focus and of numerical aperture. These results are in good agreement with a theory that we developed for measuring retardances with imaging optics. Our theoretical concept is based on Wiener's theory of mixed dielectrics, which is well established for nonimaging applications. We extend its use to imaging systems by considering the coherence region defined by the optical set-up. Light scattered from within that region interferes coherently in the image point. The presence of a filament in the coherence region leads to a polarization dependent scattering cross section and to a finite retardance measured in the image point. Similar to resolution measurements, the linear dimension of the coherence region for retardance measurements is on the order lambda/(2 NA), where lambda is the wavelength of light and NA is the numerical aperture of the illumination and imaging lenses.

Birefringence of single and bundled microtubules.

PubMed Central

Oldenbourg, R; Salmon, E D; Tran, P T

1998-01-01

We have measured the birefringence of microtubules (MTs) and of MT-based macromolecular assemblies in vitro and in living cells by using the new Pol-Scope. A single microtubule in aqueous suspension and imaged with a numerical aperture of 1.4 had a peak retardance of 0.07 nm. The peak retardance of a small bundle increased linearly with the number of MTs in the bundle. Axonemes (prepared from sea urchin sperm) had a peak retardance 20 times higher than that of single MTs, in accordance with the nine doublets and two singlets arrangement of parallel MTs in the axoneme. Measured filament retardance decreased when the filament was defocused or the numerical aperture of the imaging system was decreased. However, the retardance "area," which we defined as the image retardance integrated along a line perpendicular to the filament axis, proved to be independent of focus and of numerical aperture. These results are in good agreement with a theory that we developed for measuring retardances with imaging optics. Our theoretical concept is based on Wiener's theory of mixed dielectrics, which is well established for nonimaging applications. We extend its use to imaging systems by considering the coherence region defined by the optical set-up. Light scattered from within that region interferes coherently in the image point. The presence of a filament in the coherence region leads to a polarization dependent scattering cross section and to a finite retardance measured in the image point. Similar to resolution measurements, the linear dimension of the coherence region for retardance measurements is on the order lambda/(2 NA), where lambda is the wavelength of light and NA is the numerical aperture of the illumination and imaging lenses. PMID:9449366

Online Hierarchical Sparse Representation of Multifeature for Robust Object Tracking

PubMed Central

Qu, Shiru

2016-01-01

Object tracking based on sparse representation has given promising tracking results in recent years. However, the trackers under the framework of sparse representation always overemphasize the sparse representation and ignore the correlation of visual information. In addition, the sparse coding methods only encode the local region independently and ignore the spatial neighborhood information of the image. In this paper, we propose a robust tracking algorithm. Firstly, multiple complementary features are used to describe the object appearance; the appearance model of the tracked target is modeled by instantaneous and stable appearance features simultaneously. A two-stage sparse-coded method which takes the spatial neighborhood information of the image patch and the computation burden into consideration is used to compute the reconstructed object appearance. Then, the reliability of each tracker is measured by the tracking likelihood function of transient and reconstructed appearance models. Finally, the most reliable tracker is obtained by a well established particle filter framework; the training set and the template library are incrementally updated based on the current tracking results. Experiment results on different challenging video sequences show that the proposed algorithm performs well with superior tracking accuracy and robustness. PMID:27630710

Optimized Design and Analysis of Sparse-Sampling fMRI Experiments

PubMed Central

Perrachione, Tyler K.; Ghosh, Satrajit S.

2013-01-01

Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase the number of samples and improve statistical power. PMID:23616742

Optimized design and analysis of sparse-sampling FMRI experiments.

PubMed

Perrachione, Tyler K; Ghosh, Satrajit S

2013-01-01

Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase the number of samples and improve statistical power.

High-resolution inverse synthetic aperture radar imaging for large rotation angle targets based on segmented processing algorithm

NASA Astrophysics Data System (ADS)

Chen, Hao; Zhang, Xinggan; Bai, Yechao; Tang, Lan

2017-01-01

In inverse synthetic aperture radar (ISAR) imaging, the migration through resolution cells (MTRCs) will occur when the rotation angle of the moving target is large, thereby degrading image resolution. To solve this problem, an ISAR imaging method based on segmented preprocessing is proposed. In this method, the echoes of large rotating target are divided into several small segments, and every segment can generate a low-resolution image without MTRCs. Then, each low-resolution image is rotated back to the original position. After image registration and phase compensation, a high-resolution image can be obtained. Simulation and real experiments show that the proposed algorithm can deal with the radar system with different range and cross-range resolutions and significantly compensate the MTRCs.

Terahertz wide aperture reflection tomography.

PubMed

Pearce, Jeremy; Choi, Hyeokho; Mittleman, Daniel M; White, Jeff; Zimdars, David

2005-07-01

We describe a powerful imaging modality for terahertz (THz) radiation, THz wide aperture reflection tomography (WART). Edge maps of an object's cross section are reconstructed from a series of time-domain reflection measurements at different viewing angles. Each measurement corresponds to a parallel line projection of the object's cross section. The filtered backprojection algorithm is applied to recover the image from the projection data. To our knowledge, this is the first demonstration of a reflection computed tomography technique using electromagnetic waves. We demonstrate the capabilities of THz WART by imaging the cross sections of two test objects.

Multibeam synthetic aperture radar for global oceanography

NASA Technical Reports Server (NTRS)

Jain, A.

1979-01-01

A single-frequency multibeam synthetic aperture radar concept for large swath imaging desired for global oceanography is evaluated. Each beam iilluminates a separate range and azimuth interval, and images for different beams may be separated on the basis of the Doppler spectrum of the beams or their spatial azimuth separation in the image plane of the radar processor. The azimuth resolution of the radar system is selected so that the Doppler spectrum of each beam does not interfere with the Doppler foldover due to the finite pulse repetition frequency of the radar system.

Synthetic aperture radar images with composite azimuth resolution

DOEpatents

Bielek, Timothy P; Bickel, Douglas L

2015-03-31

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

Stitching Type Large Aperture Depolarizer for Gas Monitoring Imaging Spectrometer

NASA Astrophysics Data System (ADS)

Liu, X.; Li, M.; An, N.; Zhang, T.; Cao, G.; Cheng, S.

2018-04-01

To increase the accuracy of radiation measurement for gas monitoring imaging spectrometer, it is necessary to achieve high levels of depolarization of the incoming beam. The preferred method in space instrument is to introduce the depolarizer into the optical system. It is a combination device of birefringence crystal wedges. Limited to the actual diameter of the crystal, the traditional depolarizer cannot be used in the large aperture imaging spectrometer (greater than 100 mm). In this paper, a stitching type depolarizer is presented. The design theory and numerical calculation model for dual babinet depolarizer were built. As required radiometric accuracies of the imaging spectrometer with 250 mm × 46 mm aperture, a stitching type dual babinet depolarizer was design in detail. Based on designing the optimum structural parmeters the tolerance of wedge angle refractive index, and central thickness were given. The analysis results show that the maximum residual polarization degree of output light from depolarizer is less than 2 %. The design requirements of polarization sensitivity is satisfied.

Studying the inner regions of young stars and their disks with aperture masking interferometry

NASA Astrophysics Data System (ADS)

Greenbaum, Alexandra; Sivaramakrishnan, Anand; GPI Instrument Team; NIRISS Instrument Team

2017-01-01

High resolution aperture masking interferometry complements coronagraphic imagers to provide a unique perspective on star and planet formation at more moderate contrast. By targeting young stars, especially those with disks, we aim to understand complex protoplanetary environments. Ground-based non-redundant masking (NRM) paired with spectrographs and polarimeters probes both thermally emitting young companions, possibly embedded in the disk or gap and scattered light in protoplanetary disks. And soon the community will have access to the most stable NRM conditions yet, with the Near Infrared Imager and Slitless Spectrograph (NIRISS) Aperture Masking Interferometry (AMI) mode on the James Webb Space Telescope. I will present my thesis work commissioning the Gemini Planet Imager’s NRM, highlighting results through both its spectroscopy and polarimetry modes, which set the stage for future space-based imaging. I will also give an overview of NIRISS-AMI capabilities and performance predictions for imaging young low-mass companions and disks, and how it will complement other instruments on JWST.

MO-F-CAMPUS-I-04: Characterization of Fan Beam Coded Aperture Coherent Scatter Spectral Imaging Methods for Differentiation of Normal and Neoplastic Breast Structures

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

Morris, R; Albanese, K; Lakshmanan, M

Purpose: This study intends to characterize the spectral and spatial resolution limits of various fan beam geometries for differentiation of normal and neoplastic breast structures via coded aperture coherent scatter spectral imaging techniques. In previous studies, pencil beam raster scanning methods using coherent scatter computed tomography and selected volume tomography have yielded excellent results for tumor discrimination. However, these methods don’t readily conform to clinical constraints; primarily prolonged scan times and excessive dose to the patient. Here, we refine a fan beam coded aperture coherent scatter imaging system to characterize the tradeoffs between dose, scan time and image quality formore » breast tumor discrimination. Methods: An X-ray tube (125kVp, 400mAs) illuminated the sample with collimated fan beams of varying widths (3mm to 25mm). Scatter data was collected via two linear-array energy-sensitive detectors oriented parallel and perpendicular to the beam plane. An iterative reconstruction algorithm yields images of the sample’s spatial distribution and respective spectral data for each location. To model in-vivo tumor analysis, surgically resected breast tumor samples were used in conjunction with lard, which has a form factor comparable to adipose (fat). Results: Quantitative analysis with current setup geometry indicated optimal performance for beams up to 10mm wide, with wider beams producing poorer spatial resolution. Scan time for a fixed volume was reduced by a factor of 6 when scanned with a 10mm fan beam compared to a 1.5mm pencil beam. Conclusion: The study demonstrates the utility of fan beam coherent scatter spectral imaging for differentiation of normal and neoplastic breast tissues has successfully reduced dose and scan times whilst sufficiently preserving spectral and spatial resolution. Future work to alter the coded aperture and detector geometries could potentially allow the use of even wider fans, thereby making coded aperture coherent scatter imaging a clinically viable method for breast cancer detection. United States Department of Homeland Security; Duke University Medical Center - Department of Radiology; Carl E Ravin Advanced Imaging Laboratories; Duke University Medical Physics Graduate Program.« less

Phase Change Material for Temperature Control of Imager or Sounder on GOES Type Satellites in GEO

NASA Technical Reports Server (NTRS)

Choi, Michael K.

2014-01-01

This paper uses phase change material (PCM) in the scan cavity of an imager or sounder on satellites in geostationary orbit (GEO) to maintain the telescope temperature stable. When sunlight enters the scan aperture, solar heating causes the PCM to melt. When sunlight stops entering the scan aperture, the PCM releases the thermal energy stored to keep the components in the telescope warm. It has no moving parts or bimetallic springs. It reduces heater power required to make up the heat lost by radiation to space through the aperture. It is an attractive thermal control option to a radiator with a louver and a sunshade.

Using redundancy of round-trip ultrasound signal for non-continuous arrays: Application to gap and blockage compensation.

PubMed

Robert, Jean-Luc; Erkamp, Ramon; Korukonda, Sanghamithra; Vignon, François; Radulescu, Emil

2015-11-01

In ultrasound imaging, an array of elements is used to image a medium. If part of the array is blocked by an obstacle, or if the array is made from several sub-arrays separated by a gap, grating lobes appear and the image is degraded. The grating lobes are caused by missing spatial frequencies, corresponding to the blocked or non-existing elements. However, in an active imaging system, where elements are used both for transmitting and receiving, the round trip signal is redundant: different pairs of transmit and receive elements carry similar information. It is shown here that, if the gaps are smaller than the active sub-apertures, this redundancy can be used to compensate for the missing signals and recover full resolution. Three algorithms are proposed: one is based on a synthetic aperture method, a second one uses dual-apodization beamforming, and the third one is a radio frequency (RF) data based deconvolution. The algorithms are evaluated on simulated and experimental data sets. An application could be imaging through ribs with a large aperture.

Sparseness- and continuity-constrained seismic imaging

NASA Astrophysics Data System (ADS)

Herrmann, Felix J.

2005-04-01

Non-linear solution strategies to the least-squares seismic inverse-scattering problem with sparseness and continuity constraints are proposed. Our approach is designed to (i) deal with substantial amounts of additive noise (SNR < 0 dB); (ii) use the sparseness and locality (both in position and angle) of directional basis functions (such as curvelets and contourlets) on the model: the reflectivity; and (iii) exploit the near invariance of these basis functions under the normal operator, i.e., the scattering-followed-by-imaging operator. Signal-to-noise ratio and the continuity along the imaged reflectors are significantly enhanced by formulating the solution of the seismic inverse problem in terms of an optimization problem. During the optimization, sparseness on the basis and continuity along the reflectors are imposed by jointly minimizing the l1- and anisotropic diffusion/total-variation norms on the coefficients and reflectivity, respectively. [Joint work with Peyman P. Moghaddam was carried out as part of the SINBAD project, with financial support secured through ITF (the Industry Technology Facilitator) from the following organizations: BG Group, BP, ExxonMobil, and SHELL. Additional funding came from the NSERC Discovery Grants 22R81254.

Multi-aperture laser transmissometer system for long-path aerosol extinction rate measurement.

PubMed

Wu, Chensheng; Rzasa, John R; Ko, Jonathan; Paulson, Daniel A; Coffaro, Joseph; Spychalsky, Jonathan; Crabbs, Robert F; Davis, Christopher C

2018-01-20

We present the theory, design, simulation, and experimental evaluations of a new laser transmissometer system for aerosol extinction rate measurement over long paths. The transmitter emits an ON/OFF modulated Gaussian beam that does not require strict collimation. The receiver uses multiple point detectors to sample the sub-aperture irradiance of the arriving beam. The sparse detector arrangement makes our transmissometer system immune to turbulence-induced beam distortion and beam wander caused by the atmospheric channel. Turbulence effects often cause spatial discrepancies in beam propagation and lead to miscalculation of true power loss when using the conventional approach of measuring the total beam power directly with a large-aperture optical concentrator. Our transmissometer system, on the other hand, combines the readouts from distributed detectors to rule out turbulence-induced temporal power fluctuations. As a result, we show through both simulation and field experiments that our transmissometer system works accurately with turbulence strength Cn2 up to 10 -12   m -2/3 over a typical 1-km atmospheric channel. In application, our turbulence- and weather-resistant laser transmissometer system has significant advantages for the measurement and study of aerosol concentration, absorption, and scattering properties, which are crucial for directed energy systems, ground-level free-space optical communication systems, environmental monitoring, and weather forecasting.

Median prior constrained TV algorithm for sparse view low-dose CT reconstruction.

PubMed

Liu, Yi; Shangguan, Hong; Zhang, Quan; Zhu, Hongqing; Shu, Huazhong; Gui, Zhiguo

2015-05-01

It is known that lowering the X-ray tube current (mAs) or tube voltage (kVp) and simultaneously reducing the total number of X-ray views (sparse view) is an effective means to achieve low-dose in computed tomography (CT) scan. However, the associated image quality by the conventional filtered back-projection (FBP) usually degrades due to the excessive quantum noise. Although sparse-view CT reconstruction algorithm via total variation (TV), in the scanning protocol of reducing X-ray tube current, has been demonstrated to be able to result in significant radiation dose reduction while maintain image quality, noticeable patchy artifacts still exist in reconstructed images. In this study, to address the problem of patchy artifacts, we proposed a median prior constrained TV regularization to retain the image quality by introducing an auxiliary vector m in register with the object. Specifically, the approximate action of m is to draw, in each iteration, an object voxel toward its own local median, aiming to improve low-dose image quality with sparse-view projection measurements. Subsequently, an alternating optimization algorithm is adopted to optimize the associative objective function. We refer to the median prior constrained TV regularization as "TV_MP" for simplicity. Experimental results on digital phantoms and clinical phantom demonstrated that the proposed TV_MP with appropriate control parameters can not only ensure a higher signal to noise ratio (SNR) of the reconstructed image, but also its resolution compared with the original TV method. Copyright © 2015 Elsevier Ltd. All rights reserved.

The laboratory demonstration and signal processing of the inverse synthetic aperture imaging ladar

NASA Astrophysics Data System (ADS)

Gao, Si; Zhang, ZengHui; Xu, XianWen; Yu, WenXian

2017-10-01

This paper presents a coherent inverse synthetic-aperture imaging ladar(ISAL)system to obtain high resolution images. A balanced coherent optics system in laboratory is built with binary phase coded modulation transmit waveform which is different from conventional chirp. A whole digital signal processing solution is proposed including both quality phase gradient autofocus(QPGA) algorithm and cubic phase function(CPF) algorithm. Some high-resolution well-focused ISAL images of retro-reflecting targets are shown to validate the concepts. It is shown that high resolution images can be achieved and the influences from vibrations of platform involving targets and radar can be automatically compensated by the distinctive laboratory system and digital signal process.

70 nm resolution in subsurface optical imaging of silicon integrated-circuits using pupil-function engineering

NASA Astrophysics Data System (ADS)

Serrels, K. A.; Ramsay, E.; Reid, D. T.

2009-02-01

We present experimental evidence for the resolution-enhancing effect of an annular pupil-plane aperture when performing nonlinear imaging in the vectorial-focusing regime through manipulation of the focal spot geometry. By acquiring two-photon optical beam-induced current images of a silicon integrated-circuit using solid-immersion-lens microscopy at 1550 nm we achieved 70 nm resolution. This result demonstrates a reduction in the minimum effective focal spot diameter of 36%. In addition, the annular-aperture-induced extension of the depth-of-focus causes an observable decrease in the depth contrast of the resulting image and we explain the origins of this using a simulation of the imaging process.

3D Imaging Millimeter Wave Circular Synthetic Aperture Radar

PubMed Central

Zhang, Renyuan; Cao, Siyang

2017-01-01

In this paper, a new millimeter wave 3D imaging radar is proposed. The user just needs to move the radar along a circular track, and high resolution 3D imaging can be generated. The proposed radar uses the movement of itself to synthesize a large aperture in both the azimuth and elevation directions. It can utilize inverse Radon transform to resolve 3D imaging. To improve the sensing result, the compressed sensing approach is further investigated. The simulation and experimental result further illustrated the design. Because a single transceiver circuit is needed, a light, affordable and high resolution 3D mmWave imaging radar is illustrated in the paper. PMID:28629140

Statistical regularities of art images and natural scenes: spectra, sparseness and nonlinearities.

PubMed

Graham, Daniel J; Field, David J

2007-01-01

Paintings are the product of a process that begins with ordinary vision in the natural world and ends with manipulation of pigments on canvas. Because artists must produce images that can be seen by a visual system that is thought to take advantage of statistical regularities in natural scenes, artists are likely to replicate many of these regularities in their painted art. We have tested this notion by computing basic statistical properties and modeled cell response properties for a large set of digitized paintings and natural scenes. We find that both representational and non-representational (abstract) paintings from our sample (124 images) show basic similarities to a sample of natural scenes in terms of their spatial frequency amplitude spectra, but the paintings and natural scenes show significantly different mean amplitude spectrum slopes. We also find that the intensity distributions of paintings show a lower skewness and sparseness than natural scenes. We account for this by considering the range of luminances found in the environment compared to the range available in the medium of paint. A painting's range is limited by the reflective properties of its materials. We argue that artists do not simply scale the intensity range down but use a compressive nonlinearity. In our studies, modeled retinal and cortical filter responses to the images were less sparse for the paintings than for the natural scenes. But when a compressive nonlinearity was applied to the images, both the paintings' sparseness and the modeled responses to the paintings showed the same or greater sparseness compared to the natural scenes. This suggests that artists achieve some degree of nonlinear compression in their paintings. Because paintings have captivated humans for millennia, finding basic statistical regularities in paintings' spatial structure could grant insights into the range of spatial patterns that humans find compelling.

Concepts for the Next Generation Space Telescope

NASA Astrophysics Data System (ADS)

Margulis, M.; Tenerelli, D.

1996-12-01

In collaboration with NASA GSFC, we have examined a wide range of potential concepts for a large, passively cooled space telescope. Our design goals were to achieve a theoretical imaging sensitivity in the near-IR of 1 nJy and an angular resolution at 1 micron of 0.06 arcsec. Concepts examined included a telescope/spacecraft system with a 6-m diameter monolithic primary mirror, a variety of telescope/spacecraft systems with deployable primary mirror segments to achieve an 8-m diameter aperture, and a 12-element sparse aperture phased array telescope. Trade studies indicate that all three concept categories can achieve the required sensitivity and resolution, but that considerable technology development is required to bring any of the concepts to fruition. One attractive option is the system with the 6-m diameter monolithic primary. This option achieves high sensitivity without telescope deployments and includes a stiff structure for robust attitude and figure control. This system capitalizes on coming advances in launch vehicle and shroud technology, which should enable launch of large, monolithic payloads into orbit positions where background noise due to zodiacal dust is low. Our large space telescope study was performed by a consortium of organizations and individuals including: Domenick Tenerelli et al. (Lockheed Martin Corp.), Roger Angel et al. (U. Ariz.), Tom Casey et al. (Eastman Kodak Co.), Jim Gunn (Princeton), Shel Kulick (Composite Optics, Inc.), Jim Westphal (CIT), Johnny Batache et al. (Harris Corp.), Costas Cassapakis et al. (L'Garde, Inc.), Dave Sandler et al. (ThermoTrex Corp.), David Miller et al. (MIT), Ephrahim Garcia et al. (Garman Systems Inc.), Mark Enright (New Focus Inc.), Chris Burrows (STScI), Roc Cutri (IPAC), and Art Bradley (Allied Signal Aerospace).

Optimization-based image reconstruction from sparse-view data in offset-detector CBCT

NASA Astrophysics Data System (ADS)

Bian, Junguo; Wang, Jiong; Han, Xiao; Sidky, Emil Y.; Shao, Lingxiong; Pan, Xiaochuan

2013-01-01

The field of view (FOV) of a cone-beam computed tomography (CBCT) unit in a single-photon emission computed tomography (SPECT)/CBCT system can be increased by offsetting the CBCT detector. Analytic-based algorithms have been developed for image reconstruction from data collected at a large number of densely sampled views in offset-detector CBCT. However, the radiation dose involved in a large number of projections can be of a health concern to the imaged subject. CBCT-imaging dose can be reduced by lowering the number of projections. As analytic-based algorithms are unlikely to reconstruct accurate images from sparse-view data, we investigate and characterize in the work optimization-based algorithms, including an adaptive steepest descent-weighted projection onto convex sets (ASD-WPOCS) algorithms, for image reconstruction from sparse-view data collected in offset-detector CBCT. Using simulated data and real data collected from a physical pelvis phantom and patient, we verify and characterize properties of the algorithms under study. Results of our study suggest that optimization-based algorithms such as ASD-WPOCS may be developed for yielding images of potential utility from a number of projections substantially smaller than those used currently in clinical SPECT/CBCT imaging, thus leading to a dose reduction in CBCT imaging.

Volumetric CT with sparse detector arrays (and application to Si-strip photon counters).

PubMed

Sisniega, A; Zbijewski, W; Stayman, J W; Xu, J; Taguchi, K; Fredenberg, E; Lundqvist, Mats; Siewerdsen, J H

2016-01-07

Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling. Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm  ×  25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise. Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40% reduction in the dispersion of SSIM in the volume compared to the constant penalty (both penalties applied at optimal regularization strength). Images of the spherical clutter and wrist phantoms confirmed the advantages of the spatially varying penalty, showing a 25% improvement in image uniformity and 1.8  ×  higher CNR (at matched spatial resolution) compared to the constant penalty. The studies elucidate the relationship between sampling in the detector plane, acquisition orbit, sampling of the reconstructed volume, and the resulting image quality. They also demonstrate the benefit of spatially varying regularization in MBIR for scenarios with irregular sampling patterns. Such findings are important and integral to the incorporation of a sparsely sampled Si-strip PCD in CT imaging.

Volumetric CT with sparse detector arrays (and application to Si-strip photon counters)

NASA Astrophysics Data System (ADS)

Sisniega, A.; Zbijewski, W.; Stayman, J. W.; Xu, J.; Taguchi, K.; Fredenberg, E.; Lundqvist, Mats; Siewerdsen, J. H.

2016-01-01

Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling. Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm  ×  25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise. Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40% reduction in the dispersion of SSIM in the volume compared to the constant penalty (both penalties applied at optimal regularization strength). Images of the spherical clutter and wrist phantoms confirmed the advantages of the spatially varying penalty, showing a 25% improvement in image uniformity and 1.8  ×  higher CNR (at matched spatial resolution) compared to the constant penalty. The studies elucidate the relationship between sampling in the detector plane, acquisition orbit, sampling of the reconstructed volume, and the resulting image quality. They also demonstrate the benefit of spatially varying regularization in MBIR for scenarios with irregular sampling patterns. Such findings are important and integral to the incorporation of a sparsely sampled Si-strip PCD in CT imaging.

Volumetric CT with sparse detector arrays (and application to Si-strip photon counters)

PubMed Central

Sisniega, A; Zbijewski, W; Stayman, J W; Xu, J; Taguchi, K; Fredenberg, E; Lundqvist, Mats; Siewerdsen, J H

2016-01-01

Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling. Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm × 25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise. Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40% reduction in the dispersion of SSIM in the volume compared to the constant penalty (both penalties applied at optimal regularization strength). Images of the spherical clutter and wrist phantoms confirmed the advantages of the spatially varying penalty, showing a 25% improvement in image uniformity and 1.8 × higher CNR (at matched spatial resolution) compared to the constant penalty. The studies elucidate the relationship between sampling in the detector plane, acquisition orbit, sampling of the reconstructed volume, and the resulting image quality. They also demonstrate the benefit of spatially varying regularization in MBIR for scenarios with irregular sampling patterns. Such findings are important and integral to the incorporation of a sparsely sampled Si-strip PCD in CT imaging. PMID:26611740

A broad band X-ray imaging spectrophotometer for astrophysical studies

NASA Technical Reports Server (NTRS)

Lum, Kenneth S. K.; Lee, Dong Hwan; Ku, William H.-M.

1988-01-01

A broadband X-ray imaging spectrophotometer (BBXRIS) has been built for astrophysical studies. The BBXRIS is based on a large-imaging gas scintillation proportional counter (LIGSPC), a combination of a gas scintillation proportional counter and a multiwire proportional counter, which achieves 8 percent (FWHM) energy resolution and 1.5-mm (FWHM) spatial resolution at 5.9 keV. The LIGSPC can be integrated with a grazing incidence mirror and a coded aperture mask to provide imaging over a broad range of X-ray energies. The results of tests involving the LIGSPC and a coded aperture mask are presented, and possible applications of the BBXRIS are discussed.

Interferometric synthetic aperture radar imagery of the Gulf Stream

NASA Technical Reports Server (NTRS)

Ainsworth, T. L.; Cannella, M. E.; Jansen, R. W.; Chubb, S. R.; Carande, R. E.; Foley, E. W.; Goldstein, R. M.; Valenzuela, G. R.

1993-01-01

The advent of interferometric synthetic aperture radar (INSAR) imagery brought to the ocean remote sensing field techniques used in radio astronomy. Whilst details of the interferometry differ between the two fields, the basic idea is the same: Use the phase information arising from positional differences of the radar receivers and/or transmitters to probe remote structures. The interferometric image is formed from two complex synthetic aperture radar (SAR) images. These two images are of the same area but separated in time. Typically the time between these images is very short -- approximately 50 msec for the L-band AIRSAR (Airborne SAR). During this short period the radar scatterers on the ocean surface do not have time to significantly decorrelate. Hence the two SAR images will have the same amplitude, since both obtain the radar backscatter from essentially the same object. Although the ocean surface structure does not significantly decorrelate in 50 msec, surface features do have time to move. It is precisely the translation of scattering features across the ocean surface which gives rise to phase differences between the two SAR images. This phase difference is directly proportional to the range velocity of surface scatterers. The constant of proportionality is dependent upon the interferometric mode of operation.

Synthetic aperture radar/LANDSAT MSS image registration

NASA Technical Reports Server (NTRS)

Maurer, H. E. (Editor); Oberholtzer, J. D. (Editor); Anuta, P. E. (Editor)

1979-01-01

Algorithms and procedures necessary to merge aircraft synthetic aperture radar (SAR) and LANDSAT multispectral scanner (MSS) imagery were determined. The design of a SAR/LANDSAT data merging system was developed. Aircraft SAR images were registered to the corresponding LANDSAT MSS scenes and were the subject of experimental investigations. Results indicate that the registration of SAR imagery with LANDSAT MSS imagery is feasible from a technical viewpoint, and useful from an information-content viewpoint.

High resolution earth observation from geostationary orbit by optical aperture synthesys

NASA Astrophysics Data System (ADS)

Mesrine, M.; Thomas, E.; Garin, S.; Blanc, P.; Alis, C.; Cassaing, F.; Laubier, D.

2017-11-01

In this paper, we describe Optical Aperture Synthesis (OAS) imaging instrument concepts studied by Alcatel Alenia Space under a CNES R&T contract in term of technical feasibility. First, the methodology to select the aperture configuration is proposed, based on the definition and quantification of image quality criteria adapted to an OAS instrument for direct imaging of extended objects. The following section presents, for each interferometer type (Michelson and Fizeau), the corresponding optical configurations compatible with a large field of view from GEO orbit. These optical concepts take into account the constraints imposed by the foreseen resolution and the implementation of the co-phasing functions. The fourth section is dedicated to the analysis of the co-phasing methodologies, from the configuration deployment to the fine stabilization during observation. Finally, we present a trade-off analysis allowing to select the concept wrt mission specification and constraints related to instrument accommodation under launcher shroud and in-orbit deployment.

Performance bounds for modal analysis using sparse linear arrays

NASA Astrophysics Data System (ADS)

Li, Yuanxin; Pezeshki, Ali; Scharf, Louis L.; Chi, Yuejie

2017-05-01

We study the performance of modal analysis using sparse linear arrays (SLAs) such as nested and co-prime arrays, in both first-order and second-order measurement models. We treat SLAs as constructed from a subset of sensors in a dense uniform linear array (ULA), and characterize the performance loss of SLAs with respect to the ULA due to using much fewer sensors. In particular, we claim that, provided the same aperture, in order to achieve comparable performance in terms of Cramér-Rao bound (CRB) for modal analysis, SLAs require more snapshots, of which the number is about the number of snapshots used by ULA times the compression ratio in the number of sensors. This is shown analytically for the case with one undamped mode, as well as empirically via extensive numerical experiments for more complex scenarios. Moreover, the misspecified CRB proposed by Richmond and Horowitz is also studied, where SLAs suffer more performance loss than their ULA counterpart.

Variance based joint sparsity reconstruction of synthetic aperture radar data for speckle reduction

NASA Astrophysics Data System (ADS)

Scarnati, Theresa; Gelb, Anne

2018-04-01

In observing multiple synthetic aperture radar (SAR) images of the same scene, it is apparent that the brightness distributions of the images are not smooth, but rather composed of complicated granular patterns of bright and dark spots. Further, these brightness distributions vary from image to image. This salt and pepper like feature of SAR images, called speckle, reduces the contrast in the images and negatively affects texture based image analysis. This investigation uses the variance based joint sparsity reconstruction method for forming SAR images from the multiple SAR images. In addition to reducing speckle, the method has the advantage of being non-parametric, and can therefore be used in a variety of autonomous applications. Numerical examples include reconstructions of both simulated phase history data that result in speckled images as well as the images from the MSTAR T-72 database.

Lung dynamic MRI deblurring using low-rank decomposition and dictionary learning.

PubMed

Gou, Shuiping; Wang, Yueyue; Wu, Jiaolong; Lee, Percy; Sheng, Ke

2015-04-01

Lung dynamic MRI (dMRI) has emerged to be an appealing tool to quantify lung motion for both planning and treatment guidance purposes. However, this modality can result in blurry images due to intrinsically low signal-to-noise ratio in the lung and spatial/temporal interpolation. The image blurring could adversely affect the image processing that depends on the availability of fine landmarks. The purpose of this study is to reduce dMRI blurring using image postprocessing. To enhance the image quality and exploit the spatiotemporal continuity of dMRI sequences, a low-rank decomposition and dictionary learning (LDDL) method was employed to deblur lung dMRI and enhance the conspicuity of lung blood vessels. Fifty frames of continuous 2D coronal dMRI frames using a steady state free precession sequence were obtained from five subjects including two healthy volunteer and three lung cancer patients. In LDDL, the lung dMRI was decomposed into sparse and low-rank components. Dictionary learning was employed to estimate the blurring kernel based on the whole image, low-rank or sparse component of the first image in the lung MRI sequence. Deblurring was performed on the whole image sequences using deconvolution based on the estimated blur kernel. The deblurring results were quantified using an automated blood vessel extraction method based on the classification of Hessian matrix filtered images. Accuracy of automated extraction was calculated using manual segmentation of the blood vessels as the ground truth. In the pilot study, LDDL based on the blurring kernel estimated from the sparse component led to performance superior to the other ways of kernel estimation. LDDL consistently improved image contrast and fine feature conspicuity of the original MRI without introducing artifacts. The accuracy of automated blood vessel extraction was on average increased by 16% using manual segmentation as the ground truth. Image blurring in dMRI images can be effectively reduced using a low-rank decomposition and dictionary learning method using kernels estimated by the sparse component.

Method for measuring the focal spot size of an x-ray tube using a coded aperture mask and a digital detector.

PubMed

Russo, Paolo; Mettivier, Giovanni

2011-04-01

The goal of this study is to evaluate a new method based on a coded aperture mask combined with a digital x-ray imaging detector for measurements of the focal spot sizes of diagnostic x-ray tubes. Common techniques for focal spot size measurements employ a pinhole camera, a slit camera, or a star resolution pattern. The coded aperture mask is a radiation collimator consisting of a large number of apertures disposed on a predetermined grid in an array, through which the radiation source is imaged onto a digital x-ray detector. The method of the coded mask camera allows one to obtain a one-shot accurate and direct measurement of the two dimensions of the focal spot (like that for a pinhole camera) but at a low tube loading (like that for a slit camera). A large number of small apertures in the coded mask operate as a "multipinhole" with greater efficiency than a single pinhole, but keeping the resolution of a single pinhole. X-ray images result from the multiplexed output on the detector image plane of such a multiple aperture array, and the image of the source is digitally reconstructed with a deconvolution algorithm. Images of the focal spot of a laboratory x-ray tube (W anode: 35-80 kVp; focal spot size of 0.04 mm) were acquired at different geometrical magnifications with two different types of digital detector (a photon counting hybrid silicon pixel detector with 0.055 mm pitch and a flat panel CMOS digital detector with 0.05 mm pitch) using a high resolution coded mask (type no-two-holes-touching modified uniformly redundant array) with 480 0.07 mm apertures, designed for imaging at energies below 35 keV. Measurements with a slit camera were performed for comparison. A test with a pinhole camera and with the coded mask on a computed radiography mammography unit with 0.3 mm focal spot was also carried out. The full width at half maximum focal spot sizes were obtained from the line profiles of the decoded images, showing a focal spot of 0.120 mm x 0.105 mm at 35 kVp and M = 6.1, with a detector entrance exposure as low as 1.82 mR (0.125 mA s tube load). The slit camera indicated a focal spot of 0.112 mm x 0.104 mm at 35 kVp and M = 3.15, with an exposure at the detector of 72 mR. Focal spot measurements with the coded mask could be performed up to 80 kVp. Tolerance to angular misalignment with the reference beam up to 7 degrees in in-plane rotations and 1 degrees deg in out-of-plane rotations was observed. The axial distance of the focal spot from the coded mask could also be determined. It is possible to determine the beam intensity via measurement of the intensity of the decoded image of the focal spot and via a calibration procedure. Coded aperture masks coupled to a digital area detector produce precise determinations of the focal spot of an x-ray tube with reduced tube loading and measurement time, coupled to a large tolerance in the alignment of the mask.

Characterising rock fracture aperture-spacing relationships using power-law relationships: some considerations

NASA Astrophysics Data System (ADS)

Brook, Martin; Hebblewhite, Bruce; Mitra, Rudrajit

2016-04-01

The size-scaling of rock fractures is a well-studied problem in geology, especially for permeability quantification. The intensity of fractures may control the economic exploitation of fractured reservoirs because fracture intensity describes the abundance of fractures potentially available for fluid flow. Moreover, in geotechnical engineering, fractures are important for parameterisation of stress models and excavation design. As fracture data is often collected from widely-spaced boreholes where core recovery is often incomplete, accurate interpretation and representation of fracture aperture-frequency relationships from sparse datasets is important. Fracture intensity is the number of fractures encountered per unit length along a sample scanline oriented perpendicular to the fractures in a set. Cumulative frequency of fractures (F) is commonly related to fracture aperture (A) in the form of a power-law (F = aA-b), with variations in the size of the a coefficient between sites interpreted to equate to fracture frequency for a given aperture (A). However, a common flaw in this approach is that even a small change in b can have a large effect on the response of the fracture frequency (F) parameter. We compare fracture data from the Late Permian Rangal Coal Measures from Australia's Bowen Basin, with fracture data from Jurassic carbonates from the Sierra Madre Oriental, northeastern Mexico. Both power-law coefficient a and exponent b control the fracture aperture-frequency relationship in conjunction with each other; that is, power-laws with relatively low a coefficients have relatively high b exponents and vice versa. Hence, any comparison of different power-laws must take both a and b into consideration. The corollary is that different sedimentary beds in the Sierra Madre carbonates do not show ˜8× the fracture frequency for a given fracture aperture, as based solely on the comparison of coefficient a. Rather, power-law "sensitivity factors" developed from both Sierra Madre and the Bowen Basin span similar ranges, indicating that the factor of increase in frequency (F) for a doubling of aperture size (A) shows similar relationships and variability from both sites. Despite their limitations, we conclude that fracture aperture-frequency power-law relationships are valid and, when interpreted carefully, provide a useful basis for comparing rock fracture distributions across different sites.

Embedded sparse representation of fMRI data via group-wise dictionary optimization

NASA Astrophysics Data System (ADS)

Zhu, Dajiang; Lin, Binbin; Faskowitz, Joshua; Ye, Jieping; Thompson, Paul M.

2016-03-01

Sparse learning enables dimension reduction and efficient modeling of high dimensional signals and images, but it may need to be tailored to best suit specific applications and datasets. Here we used sparse learning to efficiently represent functional magnetic resonance imaging (fMRI) data from the human brain. We propose a novel embedded sparse representation (ESR), to identify the most consistent dictionary atoms across different brain datasets via an iterative group-wise dictionary optimization procedure. In this framework, we introduced additional criteria to make the learned dictionary atoms more consistent across different subjects. We successfully identified four common dictionary atoms that follow the external task stimuli with very high accuracy. After projecting the corresponding coefficient vectors back into the 3-D brain volume space, the spatial patterns are also consistent with traditional fMRI analysis results. Our framework reveals common features of brain activation in a population, as a new, efficient fMRI analysis method.

Thermal Neutron Imaging Using A New Pad-Based Position Sensitive Neutron Detector

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

Dioszegi I.; Vanier P.E.; Salwen C.

2016-10-29

Thermal neutrons (with mean energy of 25 meV) have a scattering mean free path of about 20 m in air. Therefore it is feasible to find localized thermal neutron sources up to ~30 m standoff distance using thermal neutron imaging. Coded aperture thermal neutron imaging was developed in our laboratory in the nineties, using He-3 filled wire chambers. Recently a new generation of coded-aperture neutron imagers has been developed. In the new design the ionization chamber has anode and cathode planes, where the anode is composed of an array of individual pads. The charge is collected on each of themore » individual 5x5 mm2 anode pads, (48x48 in total, corresponding to 24x24 cm2 sensitive area) and read out by application specific integrated circuits (ASICs). The high sensitivity of the ASICs allows unity gain operation mode. The new design has several advantages for field deployable imaging applications, compared to the previous generation of wire-grid based neutron detectors. Among these are the rugged design, lighter weight and use of non-flammable stopping gas. For standoff localization of thermalized neutron sources a low resolution (11x11 pixel) coded aperture mask has been fabricated. Using the new larger area detector and the coarse resolution mask we performed several standoff experiments using moderated californium and plutonium sources at Idaho National Laboratory. In this paper we will report on the development and performance of the new pad-based neutron camera, and present long range coded-aperture images of various thermalized neutron sources.« less

Automatic segmentation of right ventricular ultrasound images using sparse matrix transform and a level set

NASA Astrophysics Data System (ADS)

Qin, Xulei; Cong, Zhibin; Fei, Baowei

2013-11-01

An automatic segmentation framework is proposed to segment the right ventricle (RV) in echocardiographic images. The method can automatically segment both epicardial and endocardial boundaries from a continuous echocardiography series by combining sparse matrix transform, a training model, and a localized region-based level set. First, the sparse matrix transform extracts main motion regions of the myocardium as eigen-images by analyzing the statistical information of the images. Second, an RV training model is registered to the eigen-images in order to locate the position of the RV. Third, the training model is adjusted and then serves as an optimized initialization for the segmentation of each image. Finally, based on the initializations, a localized, region-based level set algorithm is applied to segment both epicardial and endocardial boundaries in each echocardiograph. Three evaluation methods were used to validate the performance of the segmentation framework. The Dice coefficient measures the overall agreement between the manual and automatic segmentation. The absolute distance and the Hausdorff distance between the boundaries from manual and automatic segmentation were used to measure the accuracy of the segmentation. Ultrasound images of human subjects were used for validation. For the epicardial and endocardial boundaries, the Dice coefficients were 90.8 ± 1.7% and 87.3 ± 1.9%, the absolute distances were 2.0 ± 0.42 mm and 1.79 ± 0.45 mm, and the Hausdorff distances were 6.86 ± 1.71 mm and 7.02 ± 1.17 mm, respectively. The automatic segmentation method based on a sparse matrix transform and level set can provide a useful tool for quantitative cardiac imaging.

Autofocus algorithm for curvilinear SAR imaging

NASA Astrophysics Data System (ADS)

Bleszynski, E.; Bleszynski, M.; Jaroszewicz, T.

2012-05-01

We describe an approach to autofocusing for large apertures on curved SAR trajectories. It is a phase-gradient type method in which phase corrections compensating trajectory perturbations are estimated not directly from the image itself, but rather on the basis of partial" SAR data { functions of the slow and fast times { recon- structed (by an appropriate forward-projection procedure) from windowed scene patches, of sizes comparable to distances between distinct targets or localized features of the scene. The resulting partial data" can be shown to contain the same information on the phase perturbations as that in the original data, provided the frequencies of the perturbations do not exceed a quantity proportional to the patch size. The algorithm uses as input a sequence of conventional scene images based on moderate-size subapertures constituting the full aperture for which the phase corrections are to be determined. The subaperture images are formed with pixel sizes comparable to the range resolution which, for the optimal subaperture size, should be also approximately equal the cross-range resolution. The method does not restrict the size or shape of the synthetic aperture and can be incorporated in the data collection process in persistent sensing scenarios. The algorithm has been tested on the publicly available set of GOTCHA data, intentionally corrupted by random-walk-type trajectory uctuations (a possible model of errors caused by imprecise inertial navigation system readings) of maximum frequencies compatible with the selected patch size. It was able to eciently remove image corruption for apertures of sizes up to 360 degrees.

Large-aperture MOEMS Fabry-Perot interferometer for miniaturized spectral imagers

NASA Astrophysics Data System (ADS)

Rissanen, Anna; Langner, Andreas; Viherkanto, Kai; Mannila, Rami

2015-02-01

VTT's optical MEMS Fabry-Perot interferometers (FPIs) are tunable optical filters, which enable miniaturization of spectral imagers into small, mass producible hand-held sensors with versatile optical measurement capabilities. FPI technology has also created a basis for various hyperspectral imaging instruments, ranging from nanosatellites, environmental sensing and precision agriculture with UAVs to instruments for skin cancer detection. Until now, these application demonstrations have been mostly realized with piezo-actuated FPIs fabricated by non-monolithical assembly method, suitable for achieving very large optical apertures and with capacity to small-to-medium volumes; however large-volume production of MEMS manufacturing supports the potential for emerging spectral imaging applications also in large-volume applications, such as in consumer/mobile products. Previously reported optical apertures of MEMS FPIs in the visible range have been up to 2 mm in size; this paper presents the design, successful fabrication and characterization of MEMS FPIs for central wavelengths of λ = 500 nm and λ = 650 nm with optical apertures up to 4 mm in diameter. The mirror membranes of the FPI structures consist of ALD (atomic layer deposited) TiO2-Al2O3 λ/4- thin film Bragg reflectors, with the air gap formed by sacrificial polymer etching in O2 plasma. The entire fabrication process is conducted below 150 °C, which makes it possible to monolithically integrate the filter structures on other ICdevices such as detectors. The realized MEMS devices are aimed for nanosatellite space application as breadboard hyperspectral imager demonstrators.

Hybrid Geometric Calibration Method for Multi-Platform Spaceborne SAR Image with Sparse Gcps

NASA Astrophysics Data System (ADS)

Lv, G.; Tang, X.; Ai, B.; Li, T.; Chen, Q.

2018-04-01

Geometric calibration is able to provide high-accuracy geometric coordinates of spaceborne SAR image through accurate geometric parameters in the Range-Doppler model by ground control points (GCPs). However, it is very difficult to obtain GCPs that covering large-scale areas, especially in the mountainous regions. In addition, the traditional calibration method is only used for single platform SAR images and can't support the hybrid geometric calibration for multi-platform images. To solve the above problems, a hybrid geometric calibration method for multi-platform spaceborne SAR images with sparse GCPs is proposed in this paper. First, we calibrate the master image that contains GCPs. Secondly, the point tracking algorithm is used to obtain the tie points (TPs) between the master and slave images. Finally, we calibrate the slave images using TPs as the GCPs. We take the Beijing-Tianjin- Hebei region as an example to study SAR image hybrid geometric calibration method using 3 TerraSAR-X images, 3 TanDEM-X images and 5 GF-3 images covering more than 235 kilometers in the north-south direction. Geometric calibration of all images is completed using only 5 GCPs. The GPS data extracted from GNSS receiver are used to assess the plane accuracy after calibration. The results after geometric calibration with sparse GCPs show that the geometric positioning accuracy is 3 m for TSX/TDX images and 7.5 m for GF-3 images.

Blind image deblurring based on trained dictionary and curvelet using sparse representation

NASA Astrophysics Data System (ADS)

Feng, Liang; Huang, Qian; Xu, Tingfa; Li, Shao

2015-04-01

Motion blur is one of the most significant and common artifacts causing poor image quality in digital photography, in which many factors resulted. In imaging process, if the objects are moving quickly in the scene or the camera moves in the exposure interval, the image of the scene would blur along the direction of relative motion between the camera and the scene, e.g. camera shake, atmospheric turbulence. Recently, sparse representation model has been widely used in signal and image processing, which is an effective method to describe the natural images. In this article, a new deblurring approach based on sparse representation is proposed. An overcomplete dictionary learned from the trained image samples via the KSVD algorithm is designed to represent the latent image. The motion-blur kernel can be treated as a piece-wise smooth function in image domain, whose support is approximately a thin smooth curve, so we employed curvelet to represent the blur kernel. Both of overcomplete dictionary and curvelet system have high sparsity, which improves the robustness to the noise and more satisfies the observer's visual demand. With the two priors, we constructed restoration model of blurred images and succeeded to solve the optimization problem with the help of alternating minimization technique. The experiment results prove the method can preserve the texture of original images and suppress the ring artifacts effectively.

Laser differential image-motion monitor for characterization of turbulence during free-space optical communication tests.

PubMed

Brown, David M; Juarez, Juan C; Brown, Andrea M

2013-12-01

A laser differential image-motion monitor (DIMM) system was designed and constructed as part of a turbulence characterization suite during the DARPA free-space optical experimental network experiment (FOENEX) program. The developed link measurement system measures the atmospheric coherence length (r0), atmospheric scintillation, and power in the bucket for the 1550 nm band. DIMM measurements are made with two separate apertures coupled to a single InGaAs camera. The angle of arrival (AoA) for the wavefront at each aperture can be calculated based on focal spot movements imaged by the camera. By utilizing a single camera for the simultaneous measurement of the focal spots, the correlation of the variance in the AoA allows a straightforward computation of r0 as in traditional DIMM systems. Standard measurements of scintillation and power in the bucket are made with the same apertures by redirecting a percentage of the incoming signals to InGaAs detectors integrated with logarithmic amplifiers for high sensitivity and high dynamic range. By leveraging two, small apertures, the instrument forms a small size and weight configuration for mounting to actively tracking laser communication terminals for characterizing link performance.

Compressive Coded-Aperture Multimodal Imaging Systems

NASA Astrophysics Data System (ADS)

Rueda-Chacon, Hoover F.

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

Design of the polar neutron-imaging aperture for use at the National Ignition Facility.

PubMed

Fatherley, V E; Barker, D A; Fittinghoff, D N; Hibbard, R L; Martinez, J I; Merrill, F E; Oertel, J A; Schmidt, D W; Volegov, P L; Wilde, C H

2016-11-01

The installation of a neutron imaging diagnostic with a polar view at the National Ignition Facility (NIF) required design of a new aperture, an extended pinhole array (PHA). This PHA is different from the pinhole array for the existing equatorial system due to significant changes in the alignment and recording systems. The complex set of component requirements, as well as significant space constraints in its intended location, makes the design of this aperture challenging. In addition, lessons learned from development of prior apertures mandate careful aperture metrology prior to first use. This paper discusses the PHA requirements, constraints, and the final design. The PHA design is complex due to size constraints, machining precision, assembly tolerances, and design requirements. When fully assembled, the aperture is a 15 mm × 15 mm × 200 mm tungsten and gold assembly. The PHA body is made from 2 layers of tungsten and 11 layers of gold. The gold layers include 4 layers containing penumbral openings, 4 layers containing pinholes and 3 spacer layers. In total, there are 64 individual, triangular pinholes with a field of view (FOV) of 200 μm and 6 penumbral apertures. Each pinhole is pointed to a slightly different location in the target plane, making the effective FOV of this PHA a 700 μm square in the target plane. The large FOV of the PHA reduces the alignment requirements both for the PHA and the target, allowing for alignment with a laser tracking system at NIF.

Blind deconvolution with principal components analysis for wide-field and small-aperture telescopes

NASA Astrophysics Data System (ADS)

Jia, Peng; Sun, Rongyu; Wang, Weinan; Cai, Dongmei; Liu, Huigen

2017-09-01

Telescopes with a wide field of view (greater than 1°) and small apertures (less than 2 m) are workhorses for observations such as sky surveys and fast-moving object detection, and play an important role in time-domain astronomy. However, images captured by these telescopes are contaminated by optical system aberrations, atmospheric turbulence, tracking errors and wind shear. To increase the quality of images and maximize their scientific output, we propose a new blind deconvolution algorithm based on statistical properties of the point spread functions (PSFs) of these telescopes. In this new algorithm, we first construct the PSF feature space through principal component analysis, and then classify PSFs from a different position and time using a self-organizing map. According to the classification results, we divide images of the same PSF types and select these PSFs to construct a prior PSF. The prior PSF is then used to restore these images. To investigate the improvement that this algorithm provides for data reduction, we process images of space debris captured by our small-aperture wide-field telescopes. Comparing the reduced results of the original images and the images processed with the standard Richardson-Lucy method, our method shows a promising improvement in astrometry accuracy.

Vision based obstacle detection and grouping for helicopter guidance

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Chatterji, Gano

1993-01-01

Electro-optical sensors can be used to compute range to objects in the flight path of a helicopter. The computation is based on the optical flow/motion at different points in the image. The motion algorithms provide a sparse set of ranges to discrete features in the image sequence as a function of azimuth and elevation. For obstacle avoidance guidance and display purposes, these discrete set of ranges, varying from a few hundreds to several thousands, need to be grouped into sets which correspond to objects in the real world. This paper presents a new method for object segmentation based on clustering the sparse range information provided by motion algorithms together with the spatial relation provided by the static image. The range values are initially grouped into clusters based on depth. Subsequently, the clusters are modified by using the K-means algorithm in the inertial horizontal plane and the minimum spanning tree algorithms in the image plane. The object grouping allows interpolation within a group and enables the creation of dense range maps. Researchers in robotics have used densely scanned sequence of laser range images to build three-dimensional representation of the outside world. Thus, modeling techniques developed for dense range images can be extended to sparse range images. The paper presents object segmentation results for a sequence of flight images.

Enhancement of snow cover change detection with sparse representation and dictionary learning

NASA Astrophysics Data System (ADS)

Varade, D.; Dikshit, O.

2014-11-01

Sparse representation and decoding is often used for denoising images and compression of images with respect to inherent features. In this paper, we adopt a methodology incorporating sparse representation of a snow cover change map using the K-SVD trained dictionary and sparse decoding to enhance the change map. The pixels often falsely characterized as "changes" are eliminated using this approach. The preliminary change map was generated using differenced NDSI or S3 maps in case of Resourcesat-2 and Landsat 8 OLI imagery respectively. These maps are extracted into patches for compressed sensing using Discrete Cosine Transform (DCT) to generate an initial dictionary which is trained by the K-SVD approach. The trained dictionary is used for sparse coding of the change map using the Orthogonal Matching Pursuit (OMP) algorithm. The reconstructed change map incorporates a greater degree of smoothing and represents the features (snow cover changes) with better accuracy. The enhanced change map is segmented using kmeans to discriminate between the changed and non-changed pixels. The segmented enhanced change map is compared, firstly with the difference of Support Vector Machine (SVM) classified NDSI maps and secondly with a reference data generated as a mask by visual interpretation of the two input images. The methodology is evaluated using multi-spectral datasets from Resourcesat-2 and Landsat-8. The k-hat statistic is computed to determine the accuracy of the proposed approach.

Servomechanism for Doppler shift compensation in optical correlator for synthetic aperture radar

NASA Technical Reports Server (NTRS)

Constaninides, N. J.; Bicknell, T. J. (Inventor)

1980-01-01

A method and apparatus for correcting Doppler shifts in synthetic aperture radar data is described. An optical correlator for synthetic aperture radar data has a means for directing a laser beam at a signal film having radar return pulse intensity information recorded on it. A resultant laser beam passes through a range telescope, an azimuth telescope, and a Fourier transform filter located between the range and azimuth telescopes, and forms an image for recording on an image film. A compensation means for Doppler shift in the radar return pulse intensity information includes a beam splitter for reflecting the modulated laser beam, after having passed through the Fourier transform filter, to a detection screen having two photodiodes mounted on it.

A New Method of Synthetic Aperture Radar Image Reconstruction Using Modified Convolution Back-Projection Algorithm.

DTIC Science & Technology

1986-08-01

SECURITY CLASSIFICATION AUTHORITY 3 DISTRIBUTIONAVAILABILITY OF REPORT N/A \\pproved for public release, 21b. OECLASS FI) CAT ) ON/OOWNGRAOING SCMEOLLE...from this set of projections. The Convolution Back-Projection (CBP) algorithm is widely used technique in Computer Aide Tomography ( CAT ). In this work...University of Illinois at Urbana-Champaign. 1985 Ac % DTICEl_ FCTE " AUG 1 11986 Urbana. Illinois U,) I A NEW METHOD OF SYNTHETIC APERTURE RADAR IMAGE

Coded aperture imaging with self-supporting uniformly redundant arrays. [Patent application

DOEpatents

Fenimore, E.E.

1980-09-26

A self-supporting uniformly redundant array pattern for coded aperture imaging. The invention utilizes holes which are an integer times smaller in each direction than holes in conventional URA patterns. A balance correlation function is generated where holes are represented by 1's, nonholes are represented by -1's, and supporting area is represented by 0's. The self-supporting array can be used for low energy applications where substrates would greatly reduce throughput.

A Novel Multi-Aperture Based Sun Sensor Based on a Fast Multi-Point MEANSHIFT (FMMS) Algorithm

PubMed Central

You, Zheng; Sun, Jian; Xing, Fei; Zhang, Gao-Fei

2011-01-01

With the current increased widespread interest in the development and applications of micro/nanosatellites, it was found that we needed to design a small high accuracy satellite attitude determination system, because the star trackers widely used in large satellites are large and heavy, and therefore not suitable for installation on micro/nanosatellites. A Sun sensor + magnetometer is proven to be a better alternative, but the conventional sun sensor has low accuracy, and cannot meet the requirements of the attitude determination systems of micro/nanosatellites, so the development of a small high accuracy sun sensor with high reliability is very significant. This paper presents a multi-aperture based sun sensor, which is composed of a micro-electro-mechanical system (MEMS) mask with 36 apertures and an active pixels sensor (APS) CMOS placed below the mask at a certain distance. A novel fast multi-point MEANSHIFT (FMMS) algorithm is proposed to improve the accuracy and reliability, the two key performance features, of an APS sun sensor. When the sunlight illuminates the sensor, a sun spot array image is formed on the APS detector. Then the sun angles can be derived by analyzing the aperture image location on the detector via the FMMS algorithm. With this system, the centroid accuracy of the sun image can reach 0.01 pixels, without increasing the weight and power consumption, even when some missing apertures and bad pixels appear on the detector due to aging of the devices and operation in a harsh space environment, while the pointing accuracy of the single-aperture sun sensor using the conventional correlation algorithm is only 0.05 pixels. PMID:22163770

DM/LCWFC based adaptive optics system for large aperture telescopes imaging from visible to infrared waveband.

PubMed

Sun, Fei; Cao, Zhaoliang; Wang, Yukun; Zhang, Caihua; Zhang, Xingyun; Liu, Yong; Mu, Quanquan; Xuan, Li

2016-11-28

Almost all the deformable mirror (DM) based adaptive optics systems (AOSs) used on large aperture telescopes work at the infrared waveband due to the limitation of the number of actuators. To extend the imaging waveband to the visible, we propose a DM and Liquid crystal wavefront corrector (DM/LCWFC) combination AOS. The LCWFC is used to correct the high frequency aberration corresponding to the visible waveband and the aberrations of the infrared are corrected by the DM. The calculated results show that, to a 10 m telescope, DM/LCWFC AOS which contains a 1538 actuators DM and a 404 × 404 pixels LCWFC is equivalent to a DM based AOS with 4057 actuators. It indicates that the DM/LCWFC AOS is possible to work from visible to infrared for larger aperture telescopes. The simulations and laboratory experiment are performed for a 2 m telescope. The experimental results show that, after correction, near diffraction limited resolution USAF target images are obtained at the wavebands of 0.7-0.9 μm, 0.9-1.5 μm and 1.5-1.7 μm respectively. Therefore, the DM/LCWFC AOS may be used to extend imaging waveband of larger aperture telescope to the visible. It is very appropriate for the observation of spatial objects and the scientific research in astronomy.

Dynamic imaging and RCS measurements of aircraft

NASA Astrophysics Data System (ADS)

Jain, Atul; Patel, Indu

1995-01-01

Results on radar cross section (RCS) measurements and inverse synthetic aperture radar images of a Mooney 231 aircraft using a ground-to-air measurement system (GTAMS) and a KC-135 airplane using an airborne radar are presented. The Mooney 231 flew in a controlled path in both clockwise and counterclockwise orbits, and successively with the gear down, flaps in the take-off position and with the speed brakes up. The data indicates that RCS pattern measurements from both ground-based and airborne radar of flying aircraft are useful and that the inverse synthetic aperture radar (ISAR) images obtained are valuable for signature diagnostics.

Determining biosonar images using sparse representations.

PubMed

Fontaine, Bertrand; Peremans, Herbert

2009-05-01

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

Optimization-based image reconstruction in x-ray computed tomography by sparsity exploitation of local continuity and nonlocal spatial self-similarity

NASA Astrophysics Data System (ADS)

Han-Ming, Zhang; Lin-Yuan, Wang; Lei, Li; Bin, Yan; Ai-Long, Cai; Guo-En, Hu

2016-07-01

The additional sparse prior of images has been the subject of much research in problems of sparse-view computed tomography (CT) reconstruction. A method employing the image gradient sparsity is often used to reduce the sampling rate and is shown to remove the unwanted artifacts while preserve sharp edges, but may cause blocky or patchy artifacts. To eliminate this drawback, we propose a novel sparsity exploitation-based model for CT image reconstruction. In the presented model, the sparse representation and sparsity exploitation of both gradient and nonlocal gradient are investigated. The new model is shown to offer the potential for better results by introducing a similarity prior information of the image structure. Then, an effective alternating direction minimization algorithm is developed to optimize the objective function with a robust convergence result. Qualitative and quantitative evaluations have been carried out both on the simulation and real data in terms of accuracy and resolution properties. The results indicate that the proposed method can be applied for achieving better image-quality potential with the theoretically expected detailed feature preservation. Project supported by the National Natural Science Foundation of China (Grant No. 61372172).

Sparse decomposition of seismic data and migration using Gaussian beams with nonzero initial curvature

NASA Astrophysics Data System (ADS)

Liu, Peng; Wang, Yanfei

2018-04-01

We study problems associated with seismic data decomposition and migration imaging. We first represent the seismic data utilizing Gaussian beam basis functions, which have nonzero curvature, and then consider the sparse decomposition technique. The sparse decomposition problem is an l0-norm constrained minimization problem. In solving the l0-norm minimization, a polynomial Radon transform is performed to achieve sparsity, and a fast gradient descent method is used to calculate the waveform functions. The waveform functions can subsequently be used for sparse Gaussian beam migration. Compared with traditional sparse Gaussian beam methods, the seismic data can be properly reconstructed employing fewer Gaussian beams with nonzero initial curvature. The migration approach described in this paper is more efficient than the traditional sparse Gaussian beam migration.

Image Reconstruction for Interferometric Imaging of Geosynchronous Satellites

NASA Astrophysics Data System (ADS)

DeSantis, Zachary J.

Imaging distant objects at a high resolution has always presented a challenge due to the diffraction limit. Larger apertures improve the resolution, but at some point the cost of engineering, building, and correcting phase aberrations of large apertures become prohibitive. Interferometric imaging uses the Van Cittert-Zernike theorem to form an image from measurements of spatial coherence. This effectively allows the synthesis of a large aperture from two or more smaller telescopes to improve the resolution. We apply this method to imaging geosynchronous satellites with a ground-based system. Imaging a dim object from the ground presents unique challenges. The atmosphere creates errors in the phase measurements. The measurements are taken simultaneously across a large bandwidth of light. The atmospheric piston error, therefore, manifests as a linear phase error across the spectral measurements. Because the objects are faint, many of the measurements are expected to have a poor signal-to-noise ratio (SNR). This eliminates possibility of use of commonly used techniques like closure phase, which is a standard technique in astronomical interferometric imaging for making partial phase measurements in the presence of atmospheric error. The bulk of our work has been focused on forming an image, using sub-Nyquist sampled data, in the presence of these linear phase errors without relying on closure phase techniques. We present an image reconstruction algorithm that successfully forms an image in the presence of these linear phase errors. We demonstrate our algorithm’s success in both simulation and in laboratory experiments.

Detection of low-contrast images in film-grain noise.

PubMed

Naderi, F; Sawchuk, A A

1978-09-15

When low contrast photographic images are digitized by a very small aperture, extreme film-grain noise almost completely obliterates the image information. Using a large aperture to average out the noise destroys the fine details of the image. In these situations conventional statistical restoration techniques have little effect, and well chosen heuristic algorithms have yielded better results. In this paper we analyze the noisecheating algorithm of Zweig et al. [J. Opt. Soc. Am. 65, 1347 (1975)] and show that it can be justified by classical maximum-likelihood detection theory. A more general algorithm applicable to a broader class of images is then developed by considering the signal-dependent nature of film-grain noise. Finally, a Bayesian detection algorithm with improved performance is presented.

Influence of polarization characteristic of targets on synthetic aperture imaging ladar

NASA Astrophysics Data System (ADS)

Xu, Qian; Sun, Jianfeng; Lu, Zhiyong; Wang, Lijuan; Hou, Peipei; Lu, Wei; Liu, Liren

2017-09-01

Synthetic aperture imaging ladar (SAIL) is one of the most possible optical active imaging methods to break the diffraction limit and achieve super-resolution in a long distance. Nevertheless, two-dimensional reconstructed images of the natural targets have not been achieved. Polarization state change of the backscattered light, which is always determined by the interaction of the light and the materials on the target plane, will affect the imaging of SAIL. The Mueller matrices can describe the complex polarization features of the target reflection and treat this interaction. In this paper, a measurement of the Mueller matrices for different target materials will be designed, and the influences of polarization characteristic of targets on resolution element imaging in side-looking and down-looking SAILs will be theoretically analyzed.

XUV coherent diffraction imaging in reflection geometry with low numerical aperture.

PubMed

Zürch, Michael; Kern, Christian; Spielmann, Christian

2013-09-09

We present an experimental realization of coherent diffraction imaging in reflection geometry illuminating the sample with a laser driven high harmonic generation (HHG) based XUV source. After recording the diffraction pattern in reflection geometry, the data must be corrected before the image can be reconstructed with a hybrid-input-output (HIO) algorithm. In this paper we present a detailed investigation of sources of spoiling the reconstructed image due to the nonlinear momentum transfer, errors in estimating the angle of incidence on the sample, and distortions by placing the image off center in the computation grid. Finally we provide guidelines for the necessary parameters to realize a satisfactory reconstruction within a spatial resolution in the range of one micron for an imaging scheme with a numerical aperture NA < 0.03.

Distributed Compressive Sensing

DTIC Science & Technology

2009-01-01

example, smooth signals are sparse in the Fourier basis, and piecewise smooth signals are sparse in a wavelet basis [8]; the commercial coding standards MP3...including wavelets [8], Gabor bases [8], curvelets [35], etc., are widely used for representation and compression of natural signals, images, and...spikes and the sine waves of a Fourier basis, or the Fourier basis and wavelets . Signals that are sparsely represented in frames or unions of bases can

SDL: Saliency-Based Dictionary Learning Framework for Image Similarity.

PubMed

Sarkar, Rituparna; Acton, Scott T

2018-02-01

In image classification, obtaining adequate data to learn a robust classifier has often proven to be difficult in several scenarios. Classification of histological tissue images for health care analysis is a notable application in this context due to the necessity of surgery, biopsy or autopsy. To adequately exploit limited training data in classification, we propose a saliency guided dictionary learning method and subsequently an image similarity technique for histo-pathological image classification. Salient object detection from images aids in the identification of discriminative image features. We leverage the saliency values for the local image regions to learn a dictionary and respective sparse codes for an image, such that the more salient features are reconstructed with smaller error. The dictionary learned from an image gives a compact representation of the image itself and is capable of representing images with similar content, with comparable sparse codes. We employ this idea to design a similarity measure between a pair of images, where local image features of one image, are encoded with the dictionary learned from the other and vice versa. To effectively utilize the learned dictionary, we take into account the contribution of each dictionary atom in the sparse codes to generate a global image representation for image comparison. The efficacy of the proposed method was evaluated using three tissue data sets that consist of mammalian kidney, lung and spleen tissue, breast cancer, and colon cancer tissue images. From the experiments, we observe that our methods outperform the state of the art with an increase of 14.2% in the average classification accuracy over all data sets.

Investigation of imaging properties for submillimeter rectangular pinholes

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

Xia, Dan, E-mail: dxia@uchicago.edu; Moore, Stephen C., E-mail: scmoore@bwh.harvard.edu, E-mail: miaepark@bwh.harvard.edu, E-mail: mcervo@bwh.harvard.edu; Park, Mi-Ae, E-mail: scmoore@bwh.harvard.edu, E-mail: miaepark@bwh.harvard.edu, E-mail: mcervo@bwh.harvard.edu

Purpose: Recently, a multipinhole collimator with inserts that have both rectangular apertures and rectangular fields of view (FOVs) has been proposed for SPECT imaging since it can tile the projection onto the detector efficiently and the FOVs in transverse and axial directions become separable. The purpose of this study is to investigate the image properties of rectangular-aperture pinholes with submillimeter apertures sizes. Methods: In this work, the authors have conducted sensitivity and FOV experiments for 18 replicates of a prototype insert fabricated in platinum/iridium (Pt/Ir) alloy with submillimeter square-apertures. A sin{sup q}θ fit to the experimental sensitivity has been performedmore » for these inserts. For the FOV measurement, the authors have proposed a new formula to calculate the projection intensity of a flood image on the detector, taking into account the penumbra effect. By fitting this formula to the measured projection data, the authors obtained the acceptance angles. Results: The mean (standard deviation) of fitted sensitivity exponents q and effective edge lengths w{sub e} were, respectively, 10.8 (1.8) and 0.38 mm (0.02 mm), which were close to the values, 7.84 and 0.396 mm, obtained from Monte Carlo calculations using the parameters of the designed inserts. For the FOV measurement, the mean (standard deviation) of the transverse and axial acceptances were 35.0° (1.2°) and 30.5° (1.6°), which are in good agreement with the designed values (34.3° and 29.9°). Conclusions: These results showed that the physical properties of the fabricated inserts with submillimeter aperture size matched our design well.« less

AIRSAR Data for Geological and Geomorphological Mapping in the Great Sandy Desert and Pilbara Regions of Western Australia

NASA Technical Reports Server (NTRS)

Tapley, Ian J.

1996-01-01

Enhancements of AIRSAR data have demonstrated the benefits of synthetic aperture radar (SAR) for revealing an additional and mich higher level of information about the composition of the terrain than enhancements f either SPOT-PAN or Landsat TM data. With appropriate image processing techniques, surface and near surface geological structures, hydrological systems (both current and ancient) and landform features, have been evidenced in a diverse range of landscapes. In the Great Sandy Desert region where spectral variability is minimal, radar's sensitivity to the micromorphology of sparse exposures of subcrop and lag gravels has provided a new insight into the region's geological framework, its landforms, and their evolution. In the Pilbara region, advanced processing of AIRSAR data to unmix the backscatter between and within the three frequencies of data has highlighted subsurface extensions of greenstone lithologies below sand cover and morphological evidence of past flow conditions under former climate regimes. On the basis of these observations, it is recommend that radar remote sensing technology involving the use of high resolution, polarimetric data be seriously considered as a viable tool for exploration in erosional and depositional environments located within Australia's mineral and oil-prospective provinces.

Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis.

PubMed

Kim, Hyunsoo; Park, Haesun

2007-06-15

Many practical pattern recognition problems require non-negativity constraints. For example, pixels in digital images and chemical concentrations in bioinformatics are non-negative. Sparse non-negative matrix factorizations (NMFs) are useful when the degree of sparseness in the non-negative basis matrix or the non-negative coefficient matrix in an NMF needs to be controlled in approximating high-dimensional data in a lower dimensional space. In this article, we introduce a novel formulation of sparse NMF and show how the new formulation leads to a convergent sparse NMF algorithm via alternating non-negativity-constrained least squares. We apply our sparse NMF algorithm to cancer-class discovery and gene expression data analysis and offer biological analysis of the results obtained. Our experimental results illustrate that the proposed sparse NMF algorithm often achieves better clustering performance with shorter computing time compared to other existing NMF algorithms. The software is available as supplementary material.

DOLPHIn—Dictionary Learning for Phase Retrieval

NASA Astrophysics Data System (ADS)

Tillmann, Andreas M.; Eldar, Yonina C.; Mairal, Julien

2016-12-01

We propose a new algorithm to learn a dictionary for reconstructing and sparsely encoding signals from measurements without phase. Specifically, we consider the task of estimating a two-dimensional image from squared-magnitude measurements of a complex-valued linear transformation of the original image. Several recent phase retrieval algorithms exploit underlying sparsity of the unknown signal in order to improve recovery performance. In this work, we consider such a sparse signal prior in the context of phase retrieval, when the sparsifying dictionary is not known in advance. Our algorithm jointly reconstructs the unknown signal - possibly corrupted by noise - and learns a dictionary such that each patch of the estimated image can be sparsely represented. Numerical experiments demonstrate that our approach can obtain significantly better reconstructions for phase retrieval problems with noise than methods that cannot exploit such "hidden" sparsity. Moreover, on the theoretical side, we provide a convergence result for our method.

An investigation of kV CBCT image quality and dose reduction for volume-of-interest imaging using dynamic collimation

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

Parsons, David, E-mail: david.parsons@dal.ca, E-mail: james.robar@cdha.nshealth.ca; Robar, James L., E-mail: david.parsons@dal.ca, E-mail: james.robar@cdha.nshealth.ca

2015-09-15

Purpose: The focus of this work was to investigate the improvements in image quality and dose reduction for volume-of-interest (VOI) kilovoltage-cone beam CT (CBCT) using dynamic collimation. Methods: A prototype iris aperture was used to track a VOI during a CBCT acquisition. The current aperture design is capable of 1D translation as a function of gantry angle and dynamic adjustment of the iris radius. The aperture occupies the location of the bow-tie filter on a Varian On-Board Imager system. CBCT and planar image quality were investigated as a function of aperture radius, while maintaining the same dose to the VOI,more » for a 20 cm diameter cylindrical water phantom with a 9 mm diameter bone insert centered on isocenter. Corresponding scatter-to-primary ratios (SPR) were determined at the detector plane with Monte Carlo simulation using EGSnrc. Dose distributions for various sizes VOI were modeled using a dynamic BEAMnrc library and DOSXYZnrc. The resulting VOI dose distributions were compared to full-field distributions. Results: SPR was reduced by a factor of 8.4 when decreasing iris diameter from 21.2 to 2.4 cm (at isocenter). Depending upon VOI location and size, dose was reduced to 16%–90% of the full-field value along the central axis plane and down to 4% along the axis of rotation, while maintaining the same dose to the VOI compared to full-field techniques. When maintaining constant dose to the VOI, this change in iris diameter corresponds to a factor increase of approximately 1.6 in image contrast and a factor decrease in image noise of approximately 1.2. This results in a measured gain in contrast-to-noise ratio by a factor of approximately 2.0. Conclusions: The presented VOI technique offers improved image quality for image-guided radiotherapy while sparing the surrounding volume of unnecessary dose compared to full-field techniques.« less

Apparatus, systems, and methods for ultrasound synthetic aperature focusing

DOEpatents

Schuster, George J.; Crawford, Susan L.; Doctor, Steven R.; Harris, Robert V.

2005-04-12

One form of the present invention is a technique for interrogating a sample with ultrasound which includes: generating ultrasonic energy data corresponding to a volume of a sample and performing a synthetic aperture focusing technique on the ultrasonic energy data. The synthetic aperture focusing technique includes: defining a number of hyperbolic surfaces which extend through the volume at different depths and a corresponding number of multiple element accumulation vectors, performing a focused element calculation procedure for a group of vectors which are representative of the interior of a designated aperture, performing another focused element calculation procedure for vectors corresponding to the boundary of the aperture, and providing an image corresponding to features of the sample in accordance with the synthetic aperture focusing technique.

Mapping the Extent and Magnitude of Severe Flooding Induced by Hurricanes Harvey, Irma, and Maria with Sentinel-1 SAR and InSAR Observations

NASA Astrophysics Data System (ADS)

Zhang, B.; Koirala, R.; Oliver-Cabrera, T.; Wdowinski, S.; Osmanoglu, B.

2017-12-01

Hurricanes can cause winds, rainfall and storm surge, all of which could result in flooding. Between August and September 2017, Hurricanes Harvey, Irma and Maria made landfall over Texas, Florida and Puerto Rico causing destruction and damages. Flood mapping is important for water management and to estimate risks and property damage. Though water gauges are able to monitor water levels, they are normally distributed sparsely. To map flooding products of these extreme events, we use Synthetic Aperture Radar (SAR) observations acquired by the European satellite constellation Sentinel-1. We obtained two acquisitions from before each flooding event, a single acquisition during the hurricane, and two after each event, a total of five acquisitions. We use both amplitude and phase observations to map extent and magnitude of flooding respectively. To map flooding extents, we use amplitude images from before, after and if possible during the hurricane pass. A calibration is used to convert the image raw data to backscatter coefficient, termed sigma nought. We generate a composite of the two image layers using red and green bands to show the change of sigma nought between acquisitions, which directly reflects the extent of flooding. Because inundation can result with either an increase or decrease of sigma nought values depending on the surface scattering characteristics, we map flooded areas in location where sigma nought changes were above a detection threshold. To study magnitude of flooding we study Interferometric Synthetic Aperture Radar (InSAR) phase changes. Changes in the water level can be detected by the radar when the signal is reflected away from water surface and bounces again by another object (e.g. trees and/or buildings) known as double bounce phase. To generate meaningful interferograms, we compare phase information with the nearest water gauge records to verify our results. Preliminary results show that the three hurricanes caused flooding condition over wide area including both rural and urban areas. The flooding in Everglades National Park in Florida following hurricane Irma covered area 1087.35 km2. Flooding in Puerto Rico main island was limited to low flat areas covering 287.84 km2. Preliminary results of the InSAR analysis shows that flooding magnitude reached in some location level of 1 m.

Plasmonic micropolarizers for full Stokes vector imaging

NASA Astrophysics Data System (ADS)

Peltzer, J. J.; Bachman, K. A.; Rose, J. W.; Flammer, P. D.; Furtak, T. E.; Collins, R. T.; Hollingsworth, R. E.

2012-06-01

Polarimetric imaging using micropolarizers integrated on focal plane arrays has previously been limited to the linear components of the Stokes vector because of the lack of an effective structure with selectivity to circular polarization. We discuss a plasmonic micropolarizing filter that can be tuned for linear or circular polarization as well as wavelength selectivity from blue to infrared (IR) through simple changes in its horizontal geometry. The filter consists of a patterned metal film with an aperture in a central cavity that is surrounded by gratings that couple to incoming light. The aperture and gratings are covered with a transparent dielectric layer to form a surface plasmon slab waveguide. A metal cap covers the aperture and forms a metal-insulator-metal (MIM) waveguide. Structures with linear apertures and gratings provide sensitivity to linear polarization, while structures with circular apertures and spiral gratings give circular polarization selectivity. Plasmonic TM modes are transmitted down the MIM waveguide while the TE modes are cut off due to the sub-wavelength dielectric thickness, providing the potential for extremely high extinction ratios. Experimental results are presented for micropolarizers fabricated on glass or directly into the Ohmic contact metallization of silicon photodiodes. Extinction ratios for linear polarization larger than 3000 have been measured.

Multifrequency Aperture-Synthesizing Microwave Radiometer System (MFASMR). Volume 2: Appendix

NASA Technical Reports Server (NTRS)

Wiley, C. A.; Chang, M. U.

1981-01-01

A number of topics supporting the systems analysis of a multifrequency aperture-synthesizing microwave radiometer system are discussed. Fellgett's (multiple) advantage, interferometer mapping behavior, mapping geometry, image processing programs, and sampling errors are among the topics discussed. A FORTRAN program code is given.

Remote sensing with spaceborne synthetic aperture imaging radars: A review

NASA Technical Reports Server (NTRS)

Cimino, J. B.; Elachi, C.

1983-01-01

A review is given of remote sensing with Spaceborne Synthetic Aperture Radars (SAR's). In 1978, a spaceborne SA was flown on the SEASAT satellite. It acquired high resulution images over many regions in North America and the North Pacific. The acquired data clearly demonstrate the capability of spaceborne SARs to: image and track polar ice floes; image ocean surface patterns including swells, internal waves, current boundaries, weather boundaries and vessels; and image land features which are used to acquire information about the surface geology and land cover. In 1981, another SAR was flown on the second shuttle flight. This Shuttle Imaging Radar (SIR-A) acquired land and ocean images over many areas around the world. The emphasis of the SIR-A experiment was mainly toward geologic mapping. Some of the key results of the SIR-A experiment are given.

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

NASA Technical Reports Server (NTRS)

Moore, R. K.

1979-01-01

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

A Large Aperture Fabry-Perot Tunable Filter Based On Micro Opto Electromechanical Systems Technology

NASA Technical Reports Server (NTRS)

Greenhouse, Matt; Mott, Brent; Powell, Dan; Barclay, Rich; Hsieh, Wen-Ting

2002-01-01

A research and development effort sponsored by the NASA Goddard Spaceflight Center (GSFC) is focused on applying Micro Opto Electromechanical Systems (MOEMS) technology to create a miniature Fabry-Perot tunable etalon for space and ground-based near infrared imaging spectrometer applications. Unlike previous devices developed for small-aperture telecommunications systems, the GSFC research is directed toward a novel 12 - 40 mm aperture for astrophysical studies, including emission line imaging of galaxies and nebulae, and multi-spectral redshift surveys in the 1.1 - 2.3 micron wavelength region. The MOEMS design features integrated electrostatic scanning of the 11-micron optical gap, and capacitance micrometry for closed loop control of parallelism within a 10-nm tolerance. The low thermal mass and inertia inherent in MOEMS devices allows for rapid cooling to the proposed 30 K operating temperature, and high frequency response. Achieving the proposed 6-nm aperture flatness (with an effective finesse of 50) represents the primary technical challenge in the current 12-mm prototype.

Waveform-Diverse Multiple-Input Multiple-Output Radar Imaging Measurements

NASA Astrophysics Data System (ADS)

Stewart, Kyle B.

Multiple-input multiple-output (MIMO) radar is an emerging set of technologies designed to extend the capabilities of multi-channel radar systems. While conventional radar architectures emphasize the use of antenna array beamforming to maximize real-time power on target, MIMO radar systems instead attempt to preserve some degree of independence between their received signals and to exploit this expanded matrix of target measurements in the signal-processing domain. Specifically the use of sparse “virtual” antenna arrays may allow MIMO radars to achieve gains over traditional multi-channel systems by post-processing diverse received signals to implement both transmit and receive beamforming at all points of interest within a given scene. MIMO architectures have been widely examined for use in radar target detection, but these systems may yet be ideally suited to real and synthetic aperture radar imaging applications where their proposed benefits include improved resolutions, expanded area coverage, novel modes of operation, and a reduction in hardware size, weight, and cost. While MIMO radar's theoretical benefits have been well established in the literature, its practical limitations have not received great attention thus far. The effective use of MIMO radar techniques requires a diversity of signals, and to date almost all MIMO system demonstrations have made use of time-staggered transmission to satisfy this requirement. Doing so is reliable but can be prohibitively slow. Waveform-diverse systems have been proposed as an alternative in which multiple, independent waveforms are broadcast simultaneously over a common bandwidth and separated on receive using signal processing. Operating in this way is much faster than its time-diverse equivalent, but finding a set of suitable waveforms for this technique has proven to be a difficult problem. In light of this, many have questioned the practicality of MIMO radar imaging and whether or not its theoretical benefits may be extended to real systems. Work in this writing focuses specifically on the practical aspects of MIMO radar imaging systems and provides performance data sourced from experimental measurements made using a four-channel software-defined MIMO radar platform. Demonstrations of waveform-diverse imaging data products are provided and compared directly against time-diverse equivalents in order to assess the performance of prospective MIMO waveforms. These are sourced from the pseudo-noise, short-term shift orthogonal, and orthogonal frequency multiplexing signal families while experimental results demonstrate waveform-diverse measurements of polarimetric radar cross section, top-down stationary target images, and finally volumetric MIMO synthetic aperture radar imagery. The data presented represents some of the first available concerning the overall practicality of waveform-diverse MIMO radar architectures, and results suggest that such configurations may achieve a reasonable degree of performance even in the presence of significant practical limitations.

Synthetic-Aperture Coherent Imaging From A Circular Path

NASA Technical Reports Server (NTRS)

Jin, Michael Y.

1995-01-01

Imaging algorithms based on exact point-target responses. Developed for use in reconstructing image of target from data gathered by radar, sonar, or other transmitting/receiving coherent-signal sensory apparatus following circular observation path around target. Potential applications include: Wide-beam synthetic-aperture radar (SAR) from aboard spacecraft in circular orbit around target planet; SAR from aboard airplane flying circular course at constant elevation around central ground point, toward which spotlight radar beam pointed; Ultrasonic reflection tomography in medical setting, using one transducer moving in circle around patient or else multiple transducers at fixed positions on circle around patient; and Sonar imaging of sea floor to high resolution, without need for large sensory apparatus.

Approximated transport-of-intensity equation for coded-aperture x-ray phase-contrast imaging.

PubMed

Das, Mini; Liang, Zhihua

2014-09-15

Transport-of-intensity equations (TIEs) allow better understanding of image formation and assist in simplifying the "phase problem" associated with phase-sensitive x-ray measurements. In this Letter, we present for the first time to our knowledge a simplified form of TIE that models x-ray differential phase-contrast (DPC) imaging with coded-aperture (CA) geometry. The validity of our approximation is demonstrated through comparison with an exact TIE in numerical simulations. The relative contributions of absorption, phase, and differential phase to the acquired phase-sensitive intensity images are made readily apparent with the approximate TIE, which may prove useful for solving the inverse phase-retrieval problem associated with these CA geometry based DPC.

Nonrigid synthetic aperture radar and optical image coregistration by combining local rigid transformations using a Kohonen network.

PubMed

Salehpour, Mehdi; Behrad, Alireza

2017-10-01

This study proposes a new algorithm for nonrigid coregistration of synthetic aperture radar (SAR) and optical images. The proposed algorithm employs point features extracted by the binary robust invariant scalable keypoints algorithm and a new method called weighted bidirectional matching for initial correspondence. To refine false matches, we assume that the transformation between SAR and optical images is locally rigid. This property is used to refine false matches by assigning scores to matched pairs and clustering local rigid transformations using a two-layer Kohonen network. Finally, the thin plate spline algorithm and mutual information are used for nonrigid coregistration of SAR and optical images.

Post-focus Instrumentation Of The NST

NASA Astrophysics Data System (ADS)

Cao, Wenda; Gorceix, N.; Andic, A.; Ahn, K.; Coulter, R.; Goode, P.

2009-05-01

The NST (New Solar Telescope), 1.6 m clear aperture, off-axis telescope, is in its commissioning phase at Big Bear Solar Observatory (BBSO). It will be the most capable, largest aperture solar telescope in the US until the 4 m ATST (Advanced Technology Solar Telescope) comes on-line in the middle of the next decade. The NST will be outfitted with state-of-the-art post-focus instrumentation, which currently include Adaptive Optics system (AO), InfraRed Imaging Magnetograph (IRIM), Visible Imaging Magnetograph (VIM), Real-time Image Reconstruction System (RIRS), and Fast Imaging Solar Spectrograph (FISS). A 308 sub-aperture (349-actuator Deformable Mirror) AO system will enable diffraction limited observations over the NST's principal operating wavelengths from 0.4 µm through 1.7 µm. IRIM and VIM are Fabry-Perot based narrow-band tunable filter, which provide high resolution two-dimensional spectroscopic and polarimetric imaging in the near infrared and visible respectively. Using a 32-node parallel computing system, RIRS is capable of performing real-time image reconstruction with one image every minute. FISS is a collaboration between NJIT and Seoul National University to focus on chromosphere dynamics. This instruments would be installed this Summer as a part of the NST commissioning and the implementation of Nysmyth focus instrumentation. Key tasks including optical design, hardware/software integration and subsequent setup/testing on the NST, will be presented in this poster. First light images from the NST will be shown.

Difference Image Analysis of Defocused Observations With CSTAR

NASA Astrophysics Data System (ADS)

Oelkers, Ryan J.; Macri, Lucas M.; Wang, Lifan; Ashley, Michael C. B.; Cui, Xiangqun; Feng, Long-Long; Gong, Xuefei; Lawrence, Jon S.; Qiang, Liu; Luong-Van, Daniel; Pennypacker, Carl R.; Yang, Huigen; Yuan, Xiangyan; York, Donald G.; Zhou, Xu; Zhu, Zhenxi

2015-02-01

The Chinese Small Telescope ARray carried out high-cadence time-series observations of 27 square degrees centered on the South Celestial Pole during the Antarctic winter seasons of 2008-2010. Aperture photometry of the 2008 and 2010 i-band images resulted in the discovery of over 200 variable stars. Yearly servicing left the array defocused for the 2009 winter season, during which the system also suffered from intermittent frosting and power failures. Despite these technical issues, nearly 800,000 useful images were obtained using g, r, and clear filters. We developed a combination of difference imaging and aperture photometry to compensate for the highly crowded, blended, and defocused frames. We present details of this approach, which may be useful for the analysis of time-series data from other small-aperture telescopes regardless of their image quality. Using this approach, we were able to recover 68 previously known variables and detected variability in 37 additional objects. We also have determined the observing statistics for Dome A during the 2009 winter season; we find the extinction due to clouds to be less than 0.1 and 0.4 mag for 40% and 63% of the dark time, respectively.

Interferometric synthetic aperture radar (InSAR)—its past, present and future

USGS Publications Warehouse

Lu, Zhong; Kwoun, Oh-Ig; Rykhus, R.P.

2007-01-01

Very simply, interferometric synthetic aperture radar (InSAR) involves the use of two or more synthetic aperture radar (SAR) images of the same area to extract landscape topography and its deformation patterns. A SAR system transmits electromagnetic waves at a wavelength that can range from a few millimeters to tens of centimeters and therefore can operate during day and night under all-weather conditions. Using SAR processing technique (Curlander and McDonough, 1991), both the intensity and phase of the reflected (or backscattered) radar signal of each ground resolution element (a few meters to tens of meters) can be calculated in the form of a complex-valued SAR image that represents the reflectivity of the ground surface. The amplitude or intensity of the SAR image is determined primarily by terrain slope, surface roughness, and dielectric constants, whereas the phase of the SAR image is determined primarily by the distance between the satellite antenna and the ground targets. InSAR imaging utilizes the interaction of electromagnetic waves, referred to as interference, to measure precise distances between the satellite antenna and ground resolution elements to derive landscape topography and its subtle change in elevation.

Coded-Aperture X- or gamma -ray telescope with Least- squares image reconstruction. III. Data acquisition and analysis enhancements

NASA Astrophysics Data System (ADS)

Kohman, T. P.

1995-05-01

The design of a cosmic X- or gamma -ray telescope with least- squares image reconstruction and its simulated operation have been described (Rev. Sci. Instrum. 60, 3396 and 3410 (1989)). Use of an auxiliary open aperture ("limiter") ahead of the coded aperture limits the object field to fewer pixels than detector elements, permitting least-squares reconstruction with improved accuracy in the imaged field; it also yields a uniformly sensitive ("flat") central field. The design has been enhanced to provide for mask-antimask operation. This cancels and eliminates uncertainties in the detector background, and the simulated results have virtually the same statistical accuracy (pixel-by-pixel output-input RMSD) as with a single mask alone. The simulations have been made more realistic by incorporating instrumental blurring of sources. A second-stage least-squares procedure had been developed to determine the precise positions and total fluxes of point sources responsible for clusters of above-background pixels in the field resulting from the first-stage reconstruction. Another program converts source positions in the image plane to celestial coordinates and vice versa, the image being a gnomic projection of a region of the sky.

Optical super resolution using tilted illumination coupled with object rotation

NASA Astrophysics Data System (ADS)

Hussain, Anwar; Mudassar, Asloob A.

2015-03-01

In conventional imaging systems, the resolution of the final image is mainly distorted due to diffraction of higher spatial frequencies of the target object. To overcome the diffraction limit, imaging techniques which synthetically enlarge the aperture of the system are used. In this paper, synthesized aperture is produced by means of a three fiber illumination assembly coupled with an in-plane object rotation. The high order diffracted spatial frequencies of the object are brought into the pass band of optical system by illuminating the object with tilted beams. The tilt produced at the fiber assembly plane is related to the dimension of the aperture, placed at the Fourier plane of the system. To span the 2D object spectrum at the Fourier plane, an in-plane object rotation procedure is applied at the object plane. The spectrum of the object is rotated as the object is rotated and illuminated with tilted beams. The corresponding object beam is interfered with a reference beam from the same source to record interferograms. All the recorded interferograms are stored in computer and de-convolution algorithm is applied to recover the synthesized spectrum. The image of the synthesized spectrum has three times improved resolution compared to the conventional image.

A novel data processing technique for image reconstruction of penumbral imaging

NASA Astrophysics Data System (ADS)

Xie, Hongwei; Li, Hongyun; Xu, Zeping; Song, Guzhou; Zhang, Faqiang; Zhou, Lin

2011-06-01

CT image reconstruction technique was applied to the data processing of the penumbral imaging. Compared with other traditional processing techniques for penumbral coded pinhole image such as Wiener, Lucy-Richardson and blind technique, this approach is brand new. In this method, the coded aperture processing method was used for the first time independent to the point spread function of the image diagnostic system. In this way, the technical obstacles was overcome in the traditional coded pinhole image processing caused by the uncertainty of point spread function of the image diagnostic system. Then based on the theoretical study, the simulation of penumbral imaging and image reconstruction was carried out to provide fairly good results. While in the visible light experiment, the point source of light was used to irradiate a 5mm×5mm object after diffuse scattering and volume scattering. The penumbral imaging was made with aperture size of ~20mm. Finally, the CT image reconstruction technique was used for image reconstruction to provide a fairly good reconstruction result.

Using an Android application to assess registration strategies in open hepatic procedures: a planning and simulation tool

NASA Astrophysics Data System (ADS)

Doss, Derek J.; Heiselman, Jon S.; Collins, Jarrod A.; Weis, Jared A.; Clements, Logan W.; Geevarghese, Sunil K.; Miga, Michael I.

2017-03-01

Sparse surface digitization with an optically tracked stylus for use in an organ surface-based image-to-physical registration is an established approach for image-guided open liver surgery procedures. However, variability in sparse data collections during open hepatic procedures can produce disparity in registration alignments. In part, this variability arises from inconsistencies with the patterns and fidelity of collected intraoperative data. The liver lacks distinct landmarks and experiences considerable soft tissue deformation. Furthermore, data coverage of the organ is often incomplete or unevenly distributed. While more robust feature-based registration methodologies have been developed for image-guided liver surgery, it is still unclear how variation in sparse intraoperative data affects registration. In this work, we have developed an application to allow surgeons to study the performance of surface digitization patterns on registration. Given the intrinsic nature of soft-tissue, we incorporate realistic organ deformation when assessing fidelity of a rigid registration methodology. We report the construction of our application and preliminary registration results using four participants. Our preliminary results indicate that registration quality improves as users acquire more experience selecting patterns of sparse intraoperative surface data.

Multiscale Region-Level VHR Image Change Detection via Sparse Change Descriptor and Robust Discriminative Dictionary Learning

PubMed Central

Xu, Yuan; Ding, Kun; Huo, Chunlei; Zhong, Zisha; Li, Haichang; Pan, Chunhong

2015-01-01

Very high resolution (VHR) image change detection is challenging due to the low discriminative ability of change feature and the difficulty of change decision in utilizing the multilevel contextual information. Most change feature extraction techniques put emphasis on the change degree description (i.e., in what degree the changes have happened), while they ignore the change pattern description (i.e., how the changes changed), which is of equal importance in characterizing the change signatures. Moreover, the simultaneous consideration of the classification robust to the registration noise and the multiscale region-consistent fusion is often neglected in change decision. To overcome such drawbacks, in this paper, a novel VHR image change detection method is proposed based on sparse change descriptor and robust discriminative dictionary learning. Sparse change descriptor combines the change degree component and the change pattern component, which are encoded by the sparse representation error and the morphological profile feature, respectively. Robust change decision is conducted by multiscale region-consistent fusion, which is implemented by the superpixel-level cosparse representation with robust discriminative dictionary and the conditional random field model. Experimental results confirm the effectiveness of the proposed change detection technique. PMID:25918748

Discriminative Dictionary Learning With Two-Level Low Rank and Group Sparse Decomposition for Image Classification.

PubMed

Wen, Zaidao; Hou, Zaidao; Jiao, Licheng

2017-11-01

Discriminative dictionary learning (DDL) framework has been widely used in image classification which aims to learn some class-specific feature vectors as well as a representative dictionary according to a set of labeled training samples. However, interclass similarities and intraclass variances among input samples and learned features will generally weaken the representability of dictionary and the discrimination of feature vectors so as to degrade the classification performance. Therefore, how to explicitly represent them becomes an important issue. In this paper, we present a novel DDL framework with two-level low rank and group sparse decomposition model. In the first level, we learn a class-shared and several class-specific dictionaries, where a low rank and a group sparse regularization are, respectively, imposed on the corresponding feature matrices. In the second level, the class-specific feature matrix will be further decomposed into a low rank and a sparse matrix so that intraclass variances can be separated to concentrate the corresponding feature vectors. Extensive experimental results demonstrate the effectiveness of our model. Compared with the other state-of-the-arts on several popular image databases, our model can achieve a competitive or better performance in terms of the classification accuracy.

Joint aperture detection for speckle reduction and increased collection efficiency in ophthalmic MHz OCT

PubMed Central

Klein, Thomas; André, Raphael; Wieser, Wolfgang; Pfeiffer, Tom; Huber, Robert

2013-01-01

Joint-aperture optical coherence tomography (JA-OCT) is an angle-resolved OCT method, in which illumination from an active channel is simultaneously probed by several passive channels. JA-OCT increases the collection efficiency and effective sensitivity of the OCT system without increasing the power on the sample. Additionally, JA-OCT provides angular scattering information about the sample in a single acquisition, so the OCT imaging speed is not reduced. Thus, JA-OCT is especially suitable for ultra high speed in-vivo imaging. JA-OCT is compared to other angle-resolved techniques, and the relation between joint aperture imaging, adaptive optics, coherent and incoherent compounding is discussed. We present angle-resolved imaging of the human retina at an axial scan rate of 1.68 MHz, and demonstrate the benefits of JA-OCT: Speckle reduction, signal increase and suppression of specular and parasitic reflections. Moreover, in the future JA-OCT may allow for the reconstruction of the full Doppler vector and tissue discrimination by analysis of the angular scattering dependence. PMID:23577296

Simulation of image formation in x-ray coded aperture microscopy with polycapillary optics.

PubMed

Korecki, P; Roszczynialski, T P; Sowa, K M

2015-04-06

In x-ray coded aperture microscopy with polycapillary optics (XCAMPO), the microstructure of focusing polycapillary optics is used as a coded aperture and enables depth-resolved x-ray imaging at a resolution better than the focal spot dimensions. Improvements in the resolution and development of 3D encoding procedures require a simulation model that can predict the outcome of XCAMPO experiments. In this work we introduce a model of image formation in XCAMPO which enables calculation of XCAMPO datasets for arbitrary positions of the object relative to the focal plane as well as to incorporate optics imperfections. In the model, the exit surface of the optics is treated as a micro-structured x-ray source that illuminates a periodic object. This makes it possible to express the intensity of XCAMPO images as a convolution series and to perform simulations by means of fast Fourier transforms. For non-periodic objects, the model can be applied by enforcing artificial periodicity and setting the spatial period larger then the field-of-view. Simulations are verified by comparison with experimental data.

Detection of Explosive Devices using X-ray Backscatter Radiation

NASA Astrophysics Data System (ADS)

Faust, Anthony A.

2002-09-01

It is our goal to develop a coded aperture based X-ray backscatter imaging detector that will provide sufficient speed, contrast and spatial resolution to detect Antipersonnel Landmines and Improvised Explosive Devices (IED). While our final objective is to field a hand-held detector, we have currently constrained ourselves to a design that can be fielded on a small robotic platform. Coded aperture imaging has been used by the observational gamma astronomy community for a number of years. However, it has been the recent advances in the field of medical nuclear imaging which has allowed for the application of the technique to a backscatter scenario. In addition, driven by requirements in medical applications, advances in X-ray detection are continually being made, and detectors are now being produced that are faster, cheaper and lighter than those only a decade ago. With these advances, a coded aperture hand-held imaging system has only recently become a possibility. This paper will begin with an introduction to the technique, identify recent advances which have made this approach possible, present a simulated example case, and conclude with a discussion on future work.

High-speed and high-resolution quantitative phase imaging with digital-micromirror device-based illumination (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhou, Renjie; Jin, Di; Yaqoob, Zahid; So, Peter T. C.

2017-02-01

Due to the large number of available mirrors, the patterning speed, low-cost, and compactness, digital-micromirror devices (DMDs) have been extensively used in biomedical imaging system. Recently, DMDs have been brought to the quantitative phase microscopy (QPM) field to achieve synthetic-aperture imaging and tomographic imaging. Last year, our group demonstrated using DMD for QPM, where the phase-retrieval is based on a recently developed Fourier ptychography algorithm. In our previous system, the illumination angle was varied through coding the aperture plane of the illumination system, which has a low efficiency on utilizing the laser power. In our new DMD-based QPM system, we use the Lee-holograms, which is conjugated to the sample plane, to change the illumination angles for much higher power efficiency. Multiple-angle illumination can also be achieved with this method. With this versatile system, we can achieve FPM-based high-resolution phase imaging with 250 nm lateral resolution using the Rayleigh criteria. Due to the use of a powerful laser, the imaging speed would only be limited by the camera acquisition speed. With a fast camera, we expect to achieve close to 100 fps phase imaging speed that has not been achieved in current FPM imaging systems. By adding reference beam, we also expect to achieve synthetic-aperture imaging while directly measuring the phase of the sample fields. This would reduce the phase-retrieval processing time to allow for real-time imaging applications in the future.

Galaxy And Mass Assembly: accurate panchromatic photometry from optical priors using LAMBDAR

NASA Astrophysics Data System (ADS)

Wright, A. H.; Robotham, A. S. G.; Bourne, N.; Driver, S. P.; Dunne, L.; Maddox, S. J.; Alpaslan, M.; Andrews, S. K.; Bauer, A. E.; Bland-Hawthorn, J.; Brough, S.; Brown, M. J. I.; Clarke, C.; Cluver, M.; Davies, L. J. M.; Grootes, M. W.; Holwerda, B. W.; Hopkins, A. M.; Jarrett, T. H.; Kafle, P. R.; Lange, R.; Liske, J.; Loveday, J.; Moffett, A. J.; Norberg, P.; Popescu, C. C.; Smith, M.; Taylor, E. N.; Tuffs, R. J.; Wang, L.; Wilkins, S. M.

2016-07-01

We present the Lambda Adaptive Multi-Band Deblending Algorithm in R (LAMBDAR), a novel code for calculating matched aperture photometry across images that are neither pixel- nor PSF-matched, using prior aperture definitions derived from high-resolution optical imaging. The development of this program is motivated by the desire for consistent photometry and uncertainties across large ranges of photometric imaging, for use in calculating spectral energy distributions. We describe the program, specifically key features required for robust determination of panchromatic photometry: propagation of apertures to images with arbitrary resolution, local background estimation, aperture normalization, uncertainty determination and propagation, and object deblending. Using simulated images, we demonstrate that the program is able to recover accurate photometric measurements in both high-resolution, low-confusion, and low-resolution, high-confusion, regimes. We apply the program to the 21-band photometric data set from the Galaxy And Mass Assembly (GAMA) Panchromatic Data Release (PDR; Driver et al. 2016), which contains imaging spanning the far-UV to the far-IR. We compare photometry derived from LAMBDAR with that presented in Driver et al. (2016), finding broad agreement between the data sets. None the less, we demonstrate that the photometry from LAMBDAR is superior to that from the GAMA PDR, as determined by a reduction in the outlier rate and intrinsic scatter of colours in the LAMBDAR data set. We similarly find a decrease in the outlier rate of stellar masses and star formation rates using LAMBDAR photometry. Finally, we note an exceptional increase in the number of UV and mid-IR sources able to be constrained, which is accompanied by a significant increase in the mid-IR colour-colour parameter-space able to be explored.

Pulling the rug out from under California: Seismic images of the Mendocino Triple Junction region

USGS Publications Warehouse

Tréhu, Anne M.

1995-01-01

In 1993 and 1994 a network of large-aperture seismic profiles was collected to image the crustal and upper-mantle structure beneath northern California and the adjacent continental margin. The data include approximately 650 km of onshore seismic refraction/reflection data, 2000 km of off-shore multichannel seismic (MCS) reflection data, and simultaneous onshore and offshore recording of the MCS airgun source to yield large-aperture data. Scientists from more than 12 institutions were involved in data acquisition.

Reconstruction of coded aperture images

NASA Technical Reports Server (NTRS)

Bielefeld, Michael J.; Yin, Lo I.

1987-01-01

Balanced correlation method and the Maximum Entropy Method (MEM) were implemented to reconstruct a laboratory X-ray source as imaged by a Uniformly Redundant Array (URA) system. Although the MEM method has advantages over the balanced correlation method, it is computationally time consuming because of the iterative nature of its solution. Massively Parallel Processing, with its parallel array structure is ideally suited for such computations. These preliminary results indicate that it is possible to use the MEM method in future coded-aperture experiments with the help of the MPP.

Development of a synthetic aperture radar design approach for wide-swath implementation

NASA Technical Reports Server (NTRS)

Jean, B. R.

1981-01-01

The first phase of a study program to develop an advanced synthetic aperture radar design concept is presented. Attributes of particular importance for the system design include wide swath coverage, reduced power requirements, and versatility in the selection of frequency, polarization and incident angle. The multiple beam configuration provides imaging at a nearly constant angle of incidence and offers the potential of realizing a wide range of the attributes desired for an orbital imaging radar for Earth resources applications.

Improvement of image quality of coherently illuminated objects in a turbulent atmosphere

NASA Astrophysics Data System (ADS)

Banakh, Viktor A.; Chen, Ben-Nam

1994-06-01

It is shown that the phenomenon of correlation of opposing waves may lead to improvement of image quality of coherently illuminated objects in a turbulent atmosphere in the case of strong intensity fluctuations. The extent of this improvement depends on the relation between sizes of the output and receiving apertures. The betterment of visibility in a turbulent atmosphere becomes maximal in the case of their proximity and vanishes if the sizes of illuminating and receiving apertures are distinguished from each other significantly.

Joint sparse reconstruction of multi-contrast MRI images with graph based redundant wavelet transform.

PubMed

Lai, Zongying; Zhang, Xinlin; Guo, Di; Du, Xiaofeng; Yang, Yonggui; Guo, Gang; Chen, Zhong; Qu, Xiaobo

2018-05-03

Multi-contrast images in magnetic resonance imaging (MRI) provide abundant contrast information reflecting the characteristics of the internal tissues of human bodies, and thus have been widely utilized in clinical diagnosis. However, long acquisition time limits the application of multi-contrast MRI. One efficient way to accelerate data acquisition is to under-sample the k-space data and then reconstruct images with sparsity constraint. However, images are compromised at high acceleration factor if images are reconstructed individually. We aim to improve the images with a jointly sparse reconstruction and Graph-based redundant wavelet transform (GBRWT). First, a sparsifying transform, GBRWT, is trained to reflect the similarity of tissue structures in multi-contrast images. Second, joint multi-contrast image reconstruction is formulated as a ℓ 2, 1 norm optimization problem under GBRWT representations. Third, the optimization problem is numerically solved using a derived alternating direction method. Experimental results in synthetic and in vivo MRI data demonstrate that the proposed joint reconstruction method can achieve lower reconstruction errors and better preserve image structures than the compared joint reconstruction methods. Besides, the proposed method outperforms single image reconstruction with joint sparsity constraint of multi-contrast images. The proposed method explores the joint sparsity of multi-contrast MRI images under graph-based redundant wavelet transform and realizes joint sparse reconstruction of multi-contrast images. Experiment demonstrate that the proposed method outperforms the compared joint reconstruction methods as well as individual reconstructions. With this high quality image reconstruction method, it is possible to achieve the high acceleration factors by exploring the complementary information provided by multi-contrast MRI.

Ultrasonic imaging of material flaws exploiting multipath information

NASA Astrophysics Data System (ADS)

Shen, Xizhong; Zhang, Yimin D.; Demirli, Ramazan; Amin, Moeness G.

2011-05-01

In this paper, we consider ultrasonic imaging for the visualization of flaws in a material. Ultrasonic imaging is a powerful nondestructive testing (NDT) tool which assesses material conditions via the detection, localization, and classification of flaws inside a structure. Multipath exploitations provide extended virtual array apertures and, in turn, enhance imaging capability beyond the limitation of traditional multisensor approaches. We utilize reflections of ultrasonic signals which occur when encountering different media and interior discontinuities. The waveforms observed at the physical as well as virtual sensors yield additional measurements corresponding to different aspect angles. Exploitation of multipath information addresses unique issues observed in ultrasonic imaging. (1) Utilization of physical and virtual sensors significantly extends the array aperture for image enhancement. (2) Multipath signals extend the angle of view of the narrow beamwidth of the ultrasound transducers, allowing improved visibility and array design flexibility. (3) Ultrasonic signals experience difficulty in penetrating a flaw, thus the aspect angle of the observation is limited unless access to other sides is available. The significant extension of the aperture makes it possible to yield flaw observation from multiple aspect angles. We show that data fusion of physical and virtual sensor data significantly improves the detection and localization performance. The effectiveness of the proposed multipath exploitation approach is demonstrated through experimental studies.

Analysis and measurement of the modulation transfer function of harmonic shear wave induced phase encoding imaging.

PubMed

McAleavey, Stephen A

2014-05-01

Shear wave induced phase encoding (SWIPE) imaging generates ultrasound backscatter images of tissue-like elastic materials by using traveling shear waves to encode the lateral position of the scatters in the phase of the received echo. In contrast to conventional ultrasound B-scan imaging, SWIPE offers the potential advantages of image formation without beam focusing or steering from a single transducer element, lateral resolution independent of aperture size, and the potential to achieve relatively high lateral resolution with low frequency ultrasound. Here a Fourier series description of the phase modulated echo signal is developed, demonstrating that echo harmonics at multiples of the shear wave frequency reveal target k-space data at identical multiples of the shear wavenumber. Modulation transfer functions of SWIPE imaging systems are calculated for maximum shear wave acceleration and maximum shear constraints, and compared with a conventionally focused aperture. The relative signal-to-noise ratio of the SWIPE method versus a conventionally focused aperture is found through these calculations. Reconstructions of wire targets in a gelatin phantom using 1 and 3.5 MHz ultrasound and a cylindrical shear wave source are presented, generated from the fundamental and second harmonic of the shear wave modulation frequency, demonstrating weak dependence of lateral resolution with ultrasound frequency.

The SAMI Galaxy Survey: can we trust aperture corrections to predict star formation?

NASA Astrophysics Data System (ADS)

Richards, S. N.; Bryant, J. J.; Croom, S. M.; Hopkins, A. M.; Schaefer, A. L.; Bland-Hawthorn, J.; Allen, J. T.; Brough, S.; Cecil, G.; Cortese, L.; Fogarty, L. M. R.; Gunawardhana, M. L. P.; Goodwin, M.; Green, A. W.; Ho, I.-T.; Kewley, L. J.; Konstantopoulos, I. S.; Lawrence, J. S.; Lorente, N. P. F.; Medling, A. M.; Owers, M. S.; Sharp, R.; Sweet, S. M.; Taylor, E. N.

2016-01-01

In the low-redshift Universe (z < 0.3), our view of galaxy evolution is primarily based on fibre optic spectroscopy surveys. Elaborate methods have been developed to address aperture effects when fixed aperture sizes only probe the inner regions for galaxies of ever decreasing redshift or increasing physical size. These aperture corrections rely on assumptions about the physical properties of galaxies. The adequacy of these aperture corrections can be tested with integral-field spectroscopic data. We use integral-field spectra drawn from 1212 galaxies observed as part of the SAMI Galaxy Survey to investigate the validity of two aperture correction methods that attempt to estimate a galaxy's total instantaneous star formation rate. We show that biases arise when assuming that instantaneous star formation is traced by broad-band imaging, and when the aperture correction is built only from spectra of the nuclear region of galaxies. These biases may be significant depending on the selection criteria of a survey sample. Understanding the sensitivities of these aperture corrections is essential for correct handling of systematic errors in galaxy evolution studies.

Simulation of photoacoustic tomography (PAT) system in COMSOL and comparison of two popular reconstruction techniques

NASA Astrophysics Data System (ADS)

Sowmiya, C.; Thittai, Arun K.

2017-03-01

Photoacoustic imaging is a molecular cum functional imaging modality based on differential optical absorption of the incident laser pulse by the endogeneous tissue chromophores. Several numerical simulations and finite element models have been developed in the past to describe and study Photoacoustic (PA) signal generation principles and study the effect of variation in PA parameters. Most of these simulation work concentrate on analyzing extracted 1D PA signals and each of them mostly describe only few of the building blocks of a Photoacoustic Tomography (PAT) imaging system. Papers describing simulation of the entire PAT system in one simulation platform, along with reconstruction is seemingly rare. This study attempts to describe how a commercially available Finite Element software (COMSOL(R)), can serve as a single platform for simulating PAT that couples the electromagnetic, thermodynamic and acoustic pressure physics involved in PA phenomena. Further, an array of detector elements placed at the boundary in the FE model can provide acoustic pressure data that can be exported to Matlab(R) to perform tomographic image reconstruction. The performance of two most commonly used image reconstruction techniques; namely, Filtered Backprojection (FBP) and Synthetic Aperture (SA) beamforming are compared. Results obtained showed that the lateral resolution obtained using FBP vs. SA largely depends on the aperture parameters. FBP reconstruction was able to provide a slightly better lateral resolution for smaller aperture while SA worked better for larger aperture. This interesting effect is currently being investigated further. Computationally FBP was faster, but it had artifacts along the spherical shell on which the data is projected.

Single image interpolation via adaptive nonlocal sparsity-based modeling.

PubMed

Romano, Yaniv; Protter, Matan; Elad, Michael

2014-07-01

Single image interpolation is a central and extensively studied problem in image processing. A common approach toward the treatment of this problem in recent years is to divide the given image into overlapping patches and process each of them based on a model for natural image patches. Adaptive sparse representation modeling is one such promising image prior, which has been shown to be powerful in filling-in missing pixels in an image. Another force that such algorithms may use is the self-similarity that exists within natural images. Processing groups of related patches together exploits their correspondence, leading often times to improved results. In this paper, we propose a novel image interpolation method, which combines these two forces-nonlocal self-similarities and sparse representation modeling. The proposed method is contrasted with competitive and related algorithms, and demonstrated to achieve state-of-the-art results.

Investigation of novel fractal shape of the nano-aperture as a metasurface for bio sensing application

NASA Astrophysics Data System (ADS)

Heydari, Samaneh; Rastan, Iman; Parvin, Amin; Pirooj, Azadeh; Zarrabi, Ferdows B.

2017-01-01

Recently, nano-aperture is noticed due to its good transmission in the optical regime. Also, the nano-apertures are developed at the metasurface design for circular polarization; for this aim, various shapes of the nano-aperture are suggested. To reach this objective, we have developed a novel Jerusalem cross fractal shape for a mid-infrared application. We have simulated various formations of the nano-fractal Jerusalem cross based on a simple cross to show the effect of nano-aperture shape on electrical field enhancement in the near-field which is important in spectroscopy and optical imaging. In addition, we have used a single layer graphene over the aperture as a coat for making reconfigurable characteristic also creating a membrane for placement of nano-particle over the aperture. Implementation of the graphene is an amendment to the transfer of the nano-apertures. The biological materials with a thickness of 80 nm have been placed over the graphene layer and the Figures of Merits (FOM) have been obtained. Additionally, the prototype of nano-antenna is independent from incident wave polarization. The Finite Difference Time Domain (FDTD) calculations have been implemented in the simulation and modeling the nano-apertures.

Prototype development of a Geostationary Synthetic Thinned Aperture Radiometer, GeoSTAR

NASA Technical Reports Server (NTRS)

Tanner, A. B.; Wilson, W. J.; Kangaslahti, P. P.; Lambrigsten, B. H.; Dinardo, S. J.; Piepmeier, J. R.; Ruf, C. S.; Rogacki, S.; Gross, S. M.; Musko, S.

2004-01-01

Preliminary details of a 2-D synthetic aperture radiometer prototype operating from 50 to 55 GHz will be presented. The laboratory prototype is being developed to demonstrate the technologies and system design needed to do millimeter-wave atmospheric soundings with high spatial resolution from Geostationary orbit. The concept is to deploy a large thinned aperture Y-array on a geostationary satellite, and to use aperture synthesis to obtain images of the Earth without the need for a large mechanically scanned antenna. The laboratory prototype consists of a Y-array of 24 horn antennas, MMIC receivers, and a digital cross-correlation sub-system.

Discrete Sparse Coding.

PubMed

Exarchakis, Georgios; Lücke, Jörg

2017-11-01

Sparse coding algorithms with continuous latent variables have been the subject of a large number of studies. However, discrete latent spaces for sparse coding have been largely ignored. In this work, we study sparse coding with latents described by discrete instead of continuous prior distributions. We consider the general case in which the latents (while being sparse) can take on any value of a finite set of possible values and in which we learn the prior probability of any value from data. This approach can be applied to any data generated by discrete causes, and it can be applied as an approximation of continuous causes. As the prior probabilities are learned, the approach then allows for estimating the prior shape without assuming specific functional forms. To efficiently train the parameters of our probabilistic generative model, we apply a truncated expectation-maximization approach (expectation truncation) that we modify to work with a general discrete prior. We evaluate the performance of the algorithm by applying it to a variety of tasks: (1) we use artificial data to verify that the algorithm can recover the generating parameters from a random initialization, (2) use image patches of natural images and discuss the role of the prior for the extraction of image components, (3) use extracellular recordings of neurons to present a novel method of analysis for spiking neurons that includes an intuitive discretization strategy, and (4) apply the algorithm on the task of encoding audio waveforms of human speech. The diverse set of numerical experiments presented in this letter suggests that discrete sparse coding algorithms can scale efficiently to work with realistic data sets and provide novel statistical quantities to describe the structure of the data.

Design of the polar neutron-imaging aperture for use at the National Ignition Facility

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

Fatherley, V. E., E-mail: vef@lanl.gov; Martinez, J. I.; Merrill, F. E.

2016-11-15

The installation of a neutron imaging diagnostic with a polar view at the National Ignition Facility (NIF) required design of a new aperture, an extended pinhole array (PHA). This PHA is different from the pinhole array for the existing equatorial system due to significant changes in the alignment and recording systems. The complex set of component requirements, as well as significant space constraints in its intended location, makes the design of this aperture challenging. In addition, lessons learned from development of prior apertures mandate careful aperture metrology prior to first use. This paper discusses the PHA requirements, constraints, and themore » final design. The PHA design is complex due to size constraints, machining precision, assembly tolerances, and design requirements. When fully assembled, the aperture is a 15 mm × 15 mm × 200 mm tungsten and gold assembly. The PHA body is made from 2 layers of tungsten and 11 layers of gold. The gold layers include 4 layers containing penumbral openings, 4 layers containing pinholes and 3 spacer layers. In total, there are 64 individual, triangular pinholes with a field of view (FOV) of 200 μm and 6 penumbral apertures. Each pinhole is pointed to a slightly different location in the target plane, making the effective FOV of this PHA a 700 μm square in the target plane. The large FOV of the PHA reduces the alignment requirements both for the PHA and the target, allowing for alignment with a laser tracking system at NIF.« less

Fisheries imaging radar surveillance test /FIRST/ - Bering Sea test

NASA Technical Reports Server (NTRS)

Woods, E. G.; Ivey, J. H.

1977-01-01

A joint NOAA, U.S. Coast Guard and NASA program is being conducted to determine if a synthetic aperture radar (SAR) system, such as planned for NASA's SEASAT, can be useful in monitoring fishing vessels within the newly established 200-mile fishing limit. As part of this program, data gathering field operations were conducted over concentrations of foreign fishing vessels in the Bering Sea off Alaska in April 1976. The Jet Propulsion Laboratory developed synthetic aperture L-band radar which was flown aboard the NASA Convair 990 aircraft, with a Coast Guard cutter and C-130 aircraft simultaneously gathering data to provide both radar imagery and sea truth information on the vessels being imaged. Results indicate that synthetic aperture radar systems have potential for all weather detection, enumeration and classification of fishing vessels.

Focusing and imaging with increased numerical apertures through multimode fibers with micro-fabricated optics.

PubMed

Bianchi, S; Rajamanickam, V P; Ferrara, L; Di Fabrizio, E; Liberale, C; Di Leonardo, R

2013-12-01

The use of individual multimode optical fibers in endoscopy applications has the potential to provide highly miniaturized and noninvasive probes for microscopy and optical micromanipulation. A few different strategies have been proposed recently, but they all suffer from intrinsically low resolution related to the low numerical aperture of multimode fibers. Here, we show that two-photon polymerization allows for direct fabrication of micro-optics components on the fiber end, resulting in an increase of the numerical aperture to a value that is close to 1. Coupling light into the fiber through a spatial light modulator, we were able to optically scan a submicrometer spot (300 nm FWHM) over an extended region, facing the opposite fiber end. Fluorescence imaging with improved resolution is also demonstrated.

Markerless EPID image guided dynamic multi-leaf collimator tracking for lung tumors

NASA Astrophysics Data System (ADS)

Rottmann, J.; Keall, P.; Berbeco, R.

2013-06-01

Compensation of target motion during the delivery of radiotherapy has the potential to improve treatment accuracy, dose conformity and sparing of healthy tissue. We implement an online image guided therapy system based on soft tissue localization (STiL) of the target from electronic portal images and treatment aperture adaptation with a dynamic multi-leaf collimator (DMLC). The treatment aperture is moved synchronously and in real time with the tumor during the entire breathing cycle. The system is implemented and tested on a Varian TX clinical linear accelerator featuring an AS-1000 electronic portal imaging device (EPID) acquiring images at a frame rate of 12.86 Hz throughout the treatment. A position update cycle for the treatment aperture consists of four steps: in the first step at time t = t0 a frame is grabbed, in the second step the frame is processed with the STiL algorithm to get the tumor position at t = t0, in a third step the tumor position at t = ti + δt is predicted to overcome system latencies and in the fourth step, the DMLC control software calculates the required leaf motions and applies them at time t = ti + δt. The prediction model is trained before the start of the treatment with data representing the tumor motion. We analyze the system latency with a dynamic chest phantom (4D motion phantom, Washington University). We estimate the average planar position deviation between target and treatment aperture in a clinical setting by driving the phantom with several lung tumor trajectories (recorded from fiducial tracking during radiotherapy delivery to the lung). DMLC tracking for lung stereotactic body radiation therapy without fiducial markers was successfully demonstrated. The inherent system latency is found to be δt = (230 ± 11) ms for a MV portal image acquisition frame rate of 12.86 Hz. The root mean square deviation between tumor and aperture position is smaller than 1 mm. We demonstrate the feasibility of real-time markerless DMLC tracking with a standard LINAC-mounted (EPID).