DDU-Net: A Domain Decomposition-Based CNN for High-Resolution Image Segmentation on Multiple GPUs
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97 MATHEMATICS AND COMPUTING↗
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Results for “image decomposition”
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Evaluation of C-band SAR data from SAREX 1992: Tapajos study site
As part of the SAREX'92 (South American Radar Experiment), the Tapajos study site, located in Para State, Brazil was imaged by the Canada Center for Remote Sensing (CCRS) Convair 580 SAR system using a C-band frequency in HH and VV polarization and 3 different imaging modes (nadir, narrow, and wide swath). A preliminary analysis of this dataset is presented. The wide swath C-band HH polarized image was enlarged to 1:100,000 in a photographic form for manual interpretation. This was compared with a vegetation map produced primarily from Landsat Thematic Mapper (TM) data and with single-band and color composite images derived from a decomposition analysis of TM data. The Synthetic Aperture Radar (SAR) image shows well the topography and drainage network defining the different geomorphological units, and canopy texture differences which appear to be related to the size and maturity of the forest canopy. Areas of recent clearing of the primary forest can also be identified on the SAR image. The SAR system appears to be a source of information for monitoring tropical forest which is complementary to the Landsat Thematic Mapper.
Shimabukuro, Yosio Edemir↗
AIS-2 spectra of California wetland vegetation
Spectral data gathered by Airborne Imaging Spectrometers-2 from wetlands were analyzed. Spectra representing stands of green Salicornia virginica, green Sesuvium verrucosum, senescing Distichlis spicata, a mixture of senescing Scirpus acutus and Scirpus californicus, senescing Scirpus paludosus, senescent S. paludosus, mowed senescent S. paludosus, and soil were isolated. No difference among narrowband spectral reflectance of the cover types was apparent between 0.8 to 1.6 micron. There were, however, broadband differences in brightness. These differences were sufficient to permit a fairly accurate decomposition of the image into its major cover type components using a procedure that assumes an additive linear mixture of surface spectra.
Gross, Michael F.↗
Precipitation of gadolinium from magnetic resonance imaging contrast agents may be the Brass tacks of toxicity
The formation of gadolinium-rich nanoparticles in multiple tissues from intravenous magnetic resonance imaging contrast agents may be the initial step in rare earth metallosis. The mechanism of gadolinium-induced diseases is poorly understood, as is how these characteristic nanoparticles are formed. Gadolinium deposition has been observed with all magnetic resonance imaging contrast agent brands. Aside from endogenous metals and acidic conditions, little attention has been paid to the role of the biological milieu in the degradation of magnetic resonance imaging contrast agents into nanoparticles. Herein, we describe the decomposition of the commercial magnetic resonance imaging contrast agents Omniscan and Dotarem in the presence of oxalic acid, a well-known endogenous compound. Omniscan dechelated rapidly and preluded measurement by the means available, while Dotarem underwent a two-step decomposition process. The decomposition of both magnetic resonance imaging contrast agents by oxalic acid formed gadolinium oxalate (Gd 2 [C 2 O 4 ] 3 , Gd 2 Ox 3 ). Furthermore, both observed steps of the Dotarem reaction involved the associative addition of oxalic acid. Adding protein (bovine serum albumin) increased the rate of dechelation. Displacement reactions could occur at lysosomal pH. Through these studies, we have demonstrated that magnetic resonance imaging contrast agents can be dissociated by endogenous molecules, thus illustrating a metric by which gadolinium-based contrast agents (GBCAs) might be destabilized in vivo.
Gadodiamide↗
Dynamically reconfigurable optical morphological processor and its applications
An innovative optically implemented morphological processor is introduced. With the use of a large space-bandwidth-product Dammann grating and a high-speed shutter spatial light modulator, effective structuring element with large size and arbitrary shape can be constructed with dynamic reconfigurability. This reconfigurability is a major improvement over the conventional correlator-based morphological processor in which fixed holographic filters are used as structuring elements (Casasent and Botha, 1988). A novel two-dimensional thresholding photodetector array, capable of performing parallel thresholding and feedback, is utilized in this system and makes possible the implementation of many complex morphological operations requiring iterative feedbacks and full programmability. The optical architecture and the principle of operation are presented. Experimental demonstration of binary image morphological erosion, dilation, opening, and closing are also demonstrated. A technique for extending this technique to gray-scale image using thresholding decomposition technique is also discussed.
Chao, Tien-Hsin↗
Optimum adaptive imaging through atmospheric turbulence
Recent results for the atmospheric mode decomposition are applied to an idealized imaging problem in which the receiver has a priori knowledge of the channel impulse response and mode decomposition. It is shown that a channel-matched filter receiver is essentially optimum and, on the average, achieves diffraction-limited performance. Furthermore, when the transmitting aperture lies within a single isoplanatic patch, this system may be realized without a priori channel knowledge by transmitted reference techniques.
Shapiro, J. H.↗
Optical Implementation of Matching Pursuit for Image Representation
We have developed a technique for image analysis, representation, and decomposition. This technique was motivated by Stephane Mallat's matching-pursuit algorithm. We've altered and simplified the mechanics of his algorithm to enable an extremely fast implementation via optical processing. Initial computer simulations show that our algorithm is capable of decomposing and representing a 2-D image as a linear combination of basis images with both high speed and high fidelity.
matching pursuit adaptive wavelet transform image ↗
Doppler radar imaging of spherical planetary surfaces
This paper describes a technique for using echo power-spectra for making radar images of spherical planetary targets. In developing the Doppler-radar imaging system, the target's reflectivity distribution is expanded in a truncated spherical harmonic series; the distribution of echo power in rotational phase and the Doppler frequency are obtained in form of a system of linear equations which express the echo spectra as functions of the series coefficients. To estimate the coefficients from an observed phase-Doppler distribution, the inversion is cast as a least-squares problem, and is solved using singular value decompositions, yielding a linear imaging system which can be fully characterized by its impulse response as a function of latitude. Simulations were designed and used to explore the capabilities of Doppler radar imaging, and the sensitivity of imaging to such factors as subradar altitude coverage and signal-to-noise ratio was investigated.
Hudson, R. Scott↗
Far-UV properties of the nuclear region of M31
Comparison of the Hubble Space Telescope (HST) far-UV and visible images of the nucleus of M31 deepens the mystery of the two brightness peaks recently discovered by Lauer et al. At 175 mm the brightest point is the optically fainter peak (P2) that is close to the dynamical center. The very center of P2 has a UV upturn that is much greater than that of the bulge light, while the UV upturn of the optically brighter but off-center P1 is very similar to that of its surroundings. The excess FUV radiation form P2 is closely confined to its center and has a total flux density of 3 micro-joules, a level that is less likely to come from stellar radiation than from a high-frequency extension of the radio source at the center of M31. A surrounding region of 1.8 pc radius has a somewhat smaller Uv upturn than the rest of the bulge, but there is some lingering possibility that this depression might be an artifact of our correction of the spherical aberration. Our improvement decomposition of the V image removes the need to postulate a dust lane near the center. We confirm that P1 is very compact, and we derive a luminosity for it similar to that found by Lauer et al. The implications of all of this are briefly discussed.
King, Ivan R.↗
Recursive time-varying filter banks for subband image coding
Filter banks and wavelet decompositions that employ recursive filters have been considered previously and are recognized for their efficiency in partitioning the frequency spectrum. This paper presents an analysis of a new infinite impulse response (IIR) filter bank in which these computationally efficient filters may be changed adaptively in response to the input. The filter bank is presented and discussed in the context of finite-support signals with the intended application in subband image coding. In the absence of quantization errors, exact reconstruction can be achieved and by the proper choice of an adaptation scheme, it is shown that IIR time-varying filter banks can yield improvement over conventional ones.
Smith, Mark J. T.↗
Improving 3D Wavelet-Based Compression of Hyperspectral Images
Two methods of increasing the effectiveness of three-dimensional (3D) wavelet-based compression of hyperspectral images have been developed. (As used here, images signifies both images and digital data representing images.) The methods are oriented toward reducing or eliminating detrimental effects of a phenomenon, referred to as spectral ringing, that is described below. In 3D wavelet-based compression, an image is represented by a multiresolution wavelet decomposition consisting of several subbands obtained by applying wavelet transforms in the two spatial dimensions corresponding to the two spatial coordinate axes of the image plane, and by applying wavelet transforms in the spectral dimension. Spectral ringing is named after the more familiar spatial ringing (spurious spatial oscillations) that can be seen parallel to and near edges in ordinary images reconstructed from compressed data. These ringing phenomena are attributable to effects of quantization. In hyperspectral data, the individual spectral bands play the role of edges, causing spurious oscillations to occur in the spectral dimension. In the absence of such corrective measures as the present two methods, spectral ringing can manifest itself as systematic biases in some reconstructed spectral bands and can reduce the effectiveness of compression of spatially-low-pass subbands. One of the two methods is denoted mean subtraction. The basic idea of this method is to subtract mean values from spatial planes of spatially low-pass subbands prior to encoding, because (a) such spatial planes often have mean values that are far from zero and (b) zero-mean data are better suited for compression by methods that are effective for subbands of two-dimensional (2D) images. In this method, after the 3D wavelet decomposition is performed, mean values are computed for and subtracted from each spatial plane of each spatially-low-pass subband. The resulting data are converted to sign-magnitude form and compressed in a manner similar to that of a baseline hyperspectral- image-compression method. The mean values are encoded in the compressed bit stream and added back to the data at the appropriate decompression step. The overhead incurred by encoding the mean values only a few bits per spectral band is negligible with respect to the huge size of a typical hyperspectral data set. The other method is denoted modified decomposition. This method is so named because it involves a modified version of a commonly used multiresolution wavelet decomposition, known in the art as the 3D Mallat decomposition, in which (a) the first of multiple stages of a 3D wavelet transform is applied to the entire dataset and (b) subsequent stages are applied only to the horizontally-, vertically-, and spectrally-low-pass subband from the preceding stage. In the modified decomposition, in stages after the first, not only is the spatially-low-pass, spectrally-low-pass subband further decomposed, but also spatially-low-pass, spectrally-high-pass subbands are further decomposed spatially. Either method can be used alone to improve the quality of a reconstructed image (see figure). Alternatively, the two methods can be combined by first performing modified decomposition, then subtracting the mean values from spatial planes of spatially-low-pass subbands.
Klimesh, Matthew↗
A multifunction recognition operator for telerobotic vision
Research on developing an operator capable of performing the various subtasks required of a telerobot's vision sensor is reported. The operator uses a goal-driven matching technique which is an application of a linear programming method that readily adapts to the elastic template matching approach to pattern recognition. Four applications of the operator are discussed: (1) three-space location of an isolated object; (2) shape determination of isolated planar figures; (3) image compression/restoration; and (4) shape decomposition.
Goode, P. W., IV↗
The Photospheric Convection Spectrum
Spectra of the photospheric cellular flows are determined from Solar and Heliospheric Observatory/Michelson Doppler Imager (SOHO/MDI) observations. Spherical harmonic decompositions are obtained from the full-disc observations. Fourier decompositions are obtained from the high-resolution observations. The p-mode oscillation signals and instrumental artifacts are reduced by temporal filtering of the Doppler data. The resulting spectra give power (kinetic energy) per wavenumber for effective spherical harmonic degrees from 1 to about 3000. The spectra show distinct peaks representing granules and supergranules but no distinct features at wavenumbers representative of mesogranules or giant cells.
Hathaway, David H.↗
Characterization of the Inner Knot of the Crab: The Site of the Gamma-Ray Flares?
Subsequent to the detections AGILE and Fermi/LAT of the gamma-ray flares from the Crab Nebula in the fall of 2010, this team has been monitoring the X-Ray emission from the Crab on a regular basis. Initially X-Ray observations took place once per month when viewing constraints allowed. More recently observations with Chandra and HST have taken place four times per year. There have been notable exceptions, e.g. in April of 2011 and March 2013 when we initiated a set of Chandra Target of opportunity observations in conjunction with bright gamma-ray flares. Often Keck observations were obtained. The aim of this program to characterize, in depth, the X-ray, optical, and infrared variations that take place in the nebula, and, by so doing, determine the regions which contribute to the harder X-ray variations and, if possible, determine the precise location within the Nebula of the origin of the gamma-ray flares. As part of this project members of the team have applied Singular Value Decomposition techniques to sequences of images in order to more accurately characterize features and their behavior. The current status of the project will be discussed highlighting studies of the inner knot and possible correlations with the gamma-ray flares.
Chandra↗
Monitoring of the Crab Nebula with Chandra and Other Observatories Including HST
Subsequent to the detections AGILE and Fermi/LAT of the gamma‐ray flares from the Crab Nebula in the fall of 2010, this team has been monitoring the X‐Ray emission from the Crab on a regular basis. X‐Ray observations have taken place typically once per month when viewing constraints allow and more recently four times per year. There have been notable exceptions, e.g. in April of 2011 and March 2013 when we initiated a set of Chandra Target of opportunity observations in conjunction with bright gamma‐ray flares. For much of the time regular HST observations were made in conjunction with the Chandra observations. The aim of this program to further characterize, in depth, the X‐Ray and optical variations that take place in the nebula, and by so doing determine the regions which contribute to the harder X‐ray variations and, if possible, determine the precise location within the Nebula of the origin of the gamma‐ray flares. As part of this project members of the team have developed Singular Value Decomposition techniques to sequences of images in order to more accurately characterize features. The current status of the project will be presented highlighting studies of the inner knot and possible correlations with the flares.
Weisskopf, Martin C.↗
Heuristic Area Cost Estimation for Observational Coverage Schedulers
This paper presents a comparison of heuris- tics used to estimate the amount of time it would take for a spacecraft to image an area using Boustrophedon decomposition (Choset and Pignon 1998). Machine learning tech- niques are used to characterize algorithmic performance of coverage algorithms. It is shown that an ordinary least-squares linear model is among the most accurate in a set of constant and linear order regression models both in terms of memory consumption and schedule duration. These are demonstrated using the ASPEN planning system (Fukunaga et al. 1997) on the Eagle Eye domain.
Knight, Russell↗
Dynamic Analysis of Reynolds Number Effects on Trailing Edge Transonic Vortex Shedding and Its Impact on Turbine Blade Aerodynamic Performance
Time-resolved, high-speed self-aligned focusing schlieren images were acquired in the NASA Glenn Research Center Transonic Turbine Blade Cascade facility to help understand the aerodynamic behavior of high-pressure, thick trailing edge turbine blades. The trailing edge thickness of 9% of axial chord tested represents simulated ceramic matrix composite fabrication constraints, which was verified previously to possess a high-loss flow regime at high inlet turbulence conditions over a narrow range of Reynolds numbers and at a fixed design exit Mach number of 0.74. Our high-speed images, which were acquired at 10 distinct Reynolds numbers, show a significant increase in energy from flow oscillations due to transonic vortex shedding at Reynolds numbers corresponding to the high loss conditions. For those conditions, strong acoustic waves turn into shock waves. Spectral Proper Orthogonal Decomposition of the high-speed images shows acoustic waves from trailing edge vortex shedding at all conditions, with increased spectral energy at the high-loss conditions and slightly increasing frequency (about 6%) as a function of Reynolds number. Analysis of potential feedback timing is performed using velocity fields from a previous LES simulation, considering different feedback mechanisms. Most noteworthy is the acoustic/shock-boundary layer interaction mechanism on the suction surface at the blade geometric throat, which likely plays an important role in realistic curved blade passages.
Trailing Edge↗
Applicability of Spectral Decomposition by Varimax-Rotated, Principal Component Analysis to the Surface Biology and Geology (SBG) VNIR Mission Concept
Cyanobacterial and Harmful Algal Blooms (CyanoHABs) are a growing concern in coastal and inland waters. But, spectral interference from multiple constituents in optically complex waters can hamper application of remote sensing using traditional image processing methods. The Kent State University (KSU) spectral decomposition method can be applied to multispectral and hyperspectral remote sensing images (e.g. HICO and the NASA Glenn HSI2) to partition and identify signals related to cyanobacteria, algae, pigment degradation products and suspended sediment in each pixel. Fundamental to the use of remote sensing data is the ability to extract independent signals from correlated hyperspectral VNIR data cubes. The Kent State University varimax-rotated, principal component analysis method (VPCA) is important to integrate into the SBG VNIR mission concept because it provides greater specificity, a software-based SNR boost relative to hardware performance, and can assist with Cal/Val, Modeling and Applications. We present examples of the hyperspectral application of the KSU VPCA method with relevance to SBG. The information extracted by VPCA can be validated spectrally or spatially with laboratory and/or in situ sensors, which capture spatial or time series of information at discrete points within remote sensing images. Comparisons show hyperspectral sensors extract more components than multispectral ones, but more independent information can be extracted from multispectral sensors by VPCA than traditional band ratio approaches. The spectral decomposition method is capable of enhancing the signal to noise ratio (SNR) of the NASA Glenn, second-generation hyperspectral imager by a factor of 7x to 20x, with a spectral reproducibility of ±3%. The spectral decomposition method, when compared against existing remote sensing monitoring methods exhibits both greater specificity and a lower detection limit. The method has been validated with multispectral images in Lake Erie to quantify the Microcystis CyanoHAB and from the Indian River Lagoon, Florida to quantify the Brown Tide resulting from A. lagunesnsis. Field operations in the Western Basin of Lake Erie were conducted using a bbe Fluoroprobe to collect vertical profiles and horizontal tows along a transect from the Toledo to the Detroit Lighthouse during coincident satellite overpasses. Extraction of pixel values from the MODIS Aqua sensor yields agreement between in situ field and lab-based measures of cyanobacterial, cryptophyte, diatoms and green algae, suspended sediment and pigment degradation products with R2>0.8.
hyperspectral↗