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At least 1,585 records · Page 88

Image-domain DAS 3D VSP elastic transmission tomography

SUMMARY Full-wavefield elastic imaging of active-source seismic data acquired by downhole receivers commonly offers higher-resolution subsurface images in the vicinity of a borehole compared to conventional surface seismic data sets, which can lack higher-frequency wavefield components due to longer travel paths and increased attenuation. An increasingly used approach for downhole acquisition is vertical seismic profiling (VSP), which has become more attractive when coupled with distributed acoustic sensing (DAS) using optical fibres installed in wells. The main difficulty for generating high-quality images with full-wavefield imaging tools for DAS VSP data, though, is the need for an accurate velocity model. To build plausible velocity models using active-source DAS VSP data, we adopt a 3-D image-domain elastic transmission tomography technique, originally developed for surface-recorded passive (microseismic) data, by exchanging the source and receiver positions (i.e. reciprocity) to mimic a passive-seismic surface monitoring scenario. The inversion approach exploits various images for each source constructed through time-reverse imaging (TRI) of downgoing P- and S-wave first-arrival waveforms. The TRI process uses the kinetic term of the (extended) PS energy imaging condition that exhibits sufficient sensitivity to velocity model errors. The method automatically updates the P- and S-wave velocity models to optimize image focusing via adjoint-state inversion. We illustrate the efficacy of the adopted elastic inversion technique using an active-source DAS 3-D VSP field data set acquired in the North Slope of Alaska. The numerical experiments demonstrate that the inverted elastic velocity models can be further used in full-wavefield acoustic/elastic imaging algorithms to obtain accurate subsurface images.

Oren, Can (ORCID:000000019534265X)↗

A Scalable Pipeline for Gigapixel Whole Slide Imaging Analysis on Leadership Class HPC Systems

Whole Slide Imaging (WSI) captures microscopic details of a patient's histopathological features at multiple res-olutions organized across different levels. Images produced by WSI are gigapixel-sized, and saving a single image in memory requires a few gigabytes which is scarce since a complicated model occupies tens of gigabytes. Performing a simple met-ric operation on these large images is also expensive. High-performance computing (HPC) can help us quickly analyze such large images using distributed training of complex deep learning models. One popular approach in analyzing these images is to divide a WSI image into smaller tiles (patches) and then train a simpler model with these reduced-sized but large numbers of patches. However, we need to solve three pre-processing challenges efficiently for pursuing this patch-based approach. 1) Creating small patches from a high-resolution image can result in a high number (hundreds of thousands per image) of patches. Storing and processing these images can be challenging due to a large number of I/O and arithmetic operations. To reduce I/Oand memory accesses, an optimal balance between the size and number of patches must exist to reduce I/O and memory accesses. 2) WSI images may have tiny annotated regions for cancer tissue and a significant portion with normal and fatty tissues; correct patch sampling should avoid dataset imbalance. 3) storing and retrieving many patches to and from disk storage might incur I/O latency while training a deep learning model. An efficient distributed data loader should reduce I/O latency during the training and inference steps. This paper explores these three challenges and provides empirical and algorithmic solutions deployed on the Summit supercomputer hosted at the Oak Ridge Leadership Computing Facility.

Dash, Sajal↗

Automatic tracking of arbitrarily shaped implanted markers in kilovoltage projection images: A feasibility study

Purpose: Certain types of commonly used fiducial markers take on irregular shapes upon implantation in soft tissue. This poses a challenge for methods that assume a predefined shape of markers when automatically tracking such markers in kilovoltage (kV) radiographs. The authors have developed a method of automatically tracking regularly and irregularly shaped markers using kV projection images and assessed its potential for detecting intrafractional target motion during rotational treatment. Methods: Template-based matching used a normalized cross-correlation with simplex minimization. Templates were created from computed tomography (CT) images for phantom studies and from end-expiration breath-hold planning CT for patient studies. The kV images were processed using a Sobel filter to enhance marker visibility. To correct for changes in intermarker relative positions between simulation and treatment that can introduce errors in automatic matching, marker offsets in three dimensions were manually determined from an approximately orthogonal pair of kV images. Two studies in anthropomorphic phantom were carried out, one using a gold cylindrical marker representing regular shape, another using a Visicoil marker representing irregular shape. Automatic matching of templates to cone beam CT (CBCT) projection images was performed to known marker positions in phantom. In patient data, automatic matching was compared to manual matching as an approximate ground truth. Positional discrepancy between automatic and manual matching of less than 2 mm was assumed as the criterion for successful tracking. Tracking success rates were examined in kV projection images from 22 CBCT scans of four pancreas, six gastroesophageal junction, and one lung cancer patients. Each patient had at least one irregularly shaped radiopaque marker implanted in or near the tumor. In addition, automatic tracking was tested in intrafraction kV images of three lung cancer patients with irregularly shaped markers during 11 volumetric modulated arc treatments. Purpose-built software developed at our institution was used to create marker templates and track the markers embedded in kV images. Results: Phantom studies showed mean ± standard deviation measurement uncertainty of automatic registration to be 0.14 ± 0.07 mm and 0.17 ± 0.08 mm for Visicoil and gold cylindrical markers, respectively. The mean success rate of automatic tracking with CBCT projections (11 frames per second, fps) of pancreas, gastroesophageal junction, and lung cancer patients was 100%, 99.1% (range 98%–100%), and 100%, respectively. With intrafraction images (approx. 0.2 fps) of lung cancer patients, the success rate was 98.2% (range 97%–100%), and 94.3% (range 93%–97%) using templates from 1.25 mm and 2.5 mm slice spacing CT scans, respectively. Correction of intermarker relative position was found to improve the success rate in two out of eight patients analyzed. Conclusions: The proposed method can track arbitrary marker shapes in kV images using templates generated from a breath-hold CT acquired at simulation. The studies indicate its feasibility for tracking tumor motion during rotational treatment. Investigation of the causes of misregistration suggests that its rate of incidence can be reduced with higher frequency of image acquisition, templates made from smaller CT slice spacing, and correction of changes in intermarker relative positions when they occur.

60 APPLIED LIFE SCIENCES↗

MO-E-17A-01: BEST IN PHYSICS (IMAGING) - Calculating SSDE From CT Exams Using Size Data Available in the DICOM Header of CT Localizer Radiographs

Purpose: To demonstrate the feasibility of using existing data stored within the DICOM header of certain CT localizer radiographs as a patient size metric for calculating CT size-specific dose estimates (SSDE). Methods: For most Siemens CT scanners, the CT localizer radiograph (topogram) contains a private DICOM field that stores an array of numbers describing AP and LAT attenuation-based measures of patient dimension. The square root of the product of the AP and LAT size data, which provides an estimate of water-equivalent-diameter (WED), was calculated retrospectively from topogram data of 20 patients who received clinically-indicated abdomen/pelvis (n=10) and chest (n=10) scans (WED-topo). In addition, slice-by-slice water-equivalent-diameter (WED-image) and effective diameter (ED-image) values were calculated from the respective image data. Using TG-204 lookup tables, size-dependent conversion factors were determined based upon WED-topo, WED-image and ED-image values. These conversion factors were used with the reported CTDIvol to calculate slice-by-slice SSDE for each method. Averaging over all slices, a single SSDE value was determined for each patient and size metric. Patientspecific SSDE and CTDIvol values were then compared with patientspecific organ doses derived from detailed Monte Carlo simulations of fixed tube current scans. Results: For abdomen/pelvis scans, the average difference between liver dose and CTDIvol, SSDE(WED-topo), SSDE(WED-image), and SSDE(ED-image) was 18.70%, 8.17%, 6.84%, and 7.58%, respectively. For chest scans, the average difference between lung dose and CTDIvol, SSDE(WED-topo), SSDE(WED-image), and SSDE(ED-image) was 25.80%, 3.33%, 4.11%, and 7.66%, respectively. Conclusion: SSDE calculated using WED derived from data in the DICOM header of the topogram was comparable to SSDE calculated using WED and ED derived from axial images; each of these estimated organ dose to within 10% for both abdomen/pelvis and chest CT examinations. The topogrambased method has the advantage that WED data are already provided and therefore available without additional post-processing of the image data. Funding Support: NIH Grant R01-EB017095; Disclosures - Michael McNitt-Gray: Institutional Research Agreement, Siemens AG; Research Support, Siemens AG; Consultant, Flaherty Sensabaugh Bonasso PLLC; Consultant, Fulbright and Jaworski; Disclosures - Cynthia McCollough: Research Grant, Siemens Healthcare.

60 APPLIED LIFE SCIENCES↗

WE-E-18A-07: MAGIC: Multi-Acquisition Gain Image Correction for Mobile X-Ray Systems with Intrinsic Localization Crosshairs

Purpose: Gain calibration for X-ray imaging systems with movable flat panel detectors (FPD) and intrinsic crosshairs is a challenge due to the geometry dependence of the heel effect and crosshair artifact. This study aims to develop a gain correction method for such systems by implementing the multi-acquisition gain image correction (MAGIC) technique. Methods: Raw flat-field images containing crosshair shadows and heel effect were acquired in 4 different FPD positions with fixed exposure parameters. The crosshair region was automatically detected and substituted with interpolated values from nearby exposed regions, generating a conventional single-image gain-map for each FPD position. Large kernel-based correction was applied to these images to correct the heel effect. A mask filter was used to invalidate the original cross-hair regions previously filled with the interpolated values. A final, seamless gain-map was created from the processed images by either the sequential filling (SF) or selective averaging (SA) techniques developed in this study. Quantitative evaluation was performed based on detective quantum efficiency improvement factor (DQEIF) for gain-corrected images using the conventional and proposed techniques. Results: Qualitatively, the MAGIC technique was found to be more effective in eliminating crosshair artifacts compared to the conventional single-image method. The mean DQEIF over the range of frequencies from 0.5 to 3.5 mm-1 were 1.09±0.06, 2.46±0.32, and 3.34±0.36 in the crosshair-artifact region and 2.35±0.31, 2.33±0.31, and 3.09±0.34 in the normal region, for the conventional, MAGIC-SF, and MAGIC-SA techniques, respectively. Conclusion: The introduced MAGIC technique is appropriate for gain calibration of an imaging system associated with a moving FPD and an intrinsic crosshair. The technique showed advantages over a conventional single image-based technique by successfully reducing residual crosshair artifacts, and higher image quality with respect to DQE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Experiments and Computational Theory for Electrical Breakdown in Critical Components: THz Imaging of Electronic Plasmas.

This report describes the development of ultra-short pulse laser (USPL) induced terahertz (THz) radiation to image electronic plasmas during electrical breakdown. The technique uses three pulses from two USPLs to (1) trigger the breakdown, (2) create a 2 picosecond (ps, 10 -12 s), THz pulse to illuminate the breakdown, and (3) record the THz image of the breakdown. During this three year internal research program, sub-picosecond jitter timing for the lasers, THz generation, high bandwidth (BW) diagnostics, and THz image acquisition was demonstrated. High intensity THz radiation was optically-induced in a pulse-charged gallium arsenide photoconductive switch. The radiation was collected, transported, concentrated, and co-propagated through an electro-optic crystal with an 800 nm USPL pulse whose polarization was rotated due to the spatially varying electric field of the THz image. The polarization modulated USPL pulse was then passed through a polarizer and the resulting spatially varying intensity was detected in a high resolution digital camera. Single shot images had a signal to noise of %7E3:1. Signal to noise was improved to %7E30:1 with several experimental techniques and by averaging the THz images from %7E4000 laser pulses internally and externally with the camera and the acquisition system (40 pulses per readout). THz shadows of metallic films and objects were also recorded with this system to demonstrate free-carrier absorption of the THz radiation and improve image contrast and resolution. These 2 ps THz pulses were created and resolved with 100 femtosecond (fs, 10 -15 s) long USPL pulses. Thus this technology has the capability to time-resolve extremely fast repetitive or single shot phenomena, such as those that occur during the initiation of electrical breakdown. The goal of imaging electrical breakdown was not reached during this three year project. However, plans to achieve this goal as part of a follow-on project are described in this document. Further modifications to improve the THz image contrast and resolution are proposed, and after they are made, images of photo-induced carriers in gallium arsenide and silicon will be acquired to evaluate image sensitivity versus carrier density. Finally electrical breakdown will be induced with the first USPL pulse, illuminated with THz radiation produced with the second USPL pulse and recorded with the third USPL pulse.

36 MATERIALS SCIENCE↗

Visualization of Multi-Dimensional Imaging Data for the DIII-D National Fusion Facility

With funding provided from the Office of Fusion Energy Science’s program on Diagnostic Systems for Magnetic Fusion Energy Sciences, the PI and his team have pioneered the development of microwave imaging systems for magnetic fusion plasma diagnostics. Specifically, electron cyclotron emission (ECE) imaging [1], a passive radiometric technique, measures electron temperature fluctuations; and microwave imaging reflectometry (MIR) [2], an active radar imaging technique, measures electron density fluctuations. These microwave imaging diagnostic instruments developed by UC Davis have made important contributions to fusion science in a relatively short period of time from their original installation on DIII-D. The microwave imaging diagnostic technique has matured considerably since the beginning of a fruitful collaboration with DIII-D and PPPL, and has also been adopted at preeminent tokamak facilities worldwide. As discussed in detail in the following, this has continued with the development of revolutionary microwave diagnostic instruments employing monolithic millimeter wave integrated circuit (MMIC) system-on-chip (SoC) technology. Specifically, “chip” receivers mounted in liquid crystal polymer (LCP) modules have been demonstrated to dramatically improve the performance of the electron cyclotron emission imaging (ECEI) system including: 30x improvement in noise temperature thereby permitting absolute 2-D electron temperature images, outstanding shielding against out-of-band interference including microwave bursting which had plagued previous ELM studies using the old quasi-optical mini-lens ECEI system, and independent modules facilitating flexible repair and replacement. Under the “Visualization of multi-dimensional imaging data for the DIII-D National Fusion Facility” program, funding was provided for a research scientist postdoc and a Ph.D. student to support physics studies at DIII-D employing these instruments. This endeavor is synergistic with our current grant under the DOE Fusion Energy Sciences (FES) program on Diagnostic Systems for Magnetic Fusion Energy Sciences. This support considerably increased the scientific output of the diagnostics. The activities were strongly focused in the areas of pedestal and ELM stability, energetic particle confinement, and the early detection and avoidance of tokamak disruptions employing the microwave imaging diagnostic instruments developed under the advanced diagnostics program where imaging of the ELM crash was made possible by the elimination of the interference from the associated microwave “bursts”

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Numerical image manipulation and display in solar astronomy

The paper describes the system configuration and data manipulation capabilities of a solar image display system which allows interactive analysis of visual images and on-line manipulation of digital data. Image processing features include smoothing or filtering of images stored in the display, contrast enhancement, and blinking or flickering images. A computer with a core memory of 28,672 words provides the capacity to perform complex calculations based on stored images, including computing histograms, selecting subsets of images for further analysis, combining portions of images to produce images with physical meaning, and constructing mathematical models of features in an image. Some of the processing modes are illustrated by some image sequences from solar observations.

Levine, R. H.↗

A model for radar images and its application to adaptive digital filtering of multiplicative noise

Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noise. The model leads to the functional form of an optimum (minimum MSE) filter for smoothing radar images. By using locally estimated parameter values the filter is made adaptive so that it provides minimum MSE estimates inside homogeneous areas of an image while preserving the edge structure. It is shown that the filter can be easily implemented in the spatial domain and is computationally efficient. The performance of the adaptive filter is compared (qualitatively and quantitatively) with several standard filters using real and simulated radar images.

Frost, V. S.↗

Rock type discrimination techniques using Landsat and Seasat image data

Results of a sedimentary rock type discrimination project using Seasat radar and Landsat multispectral image data of the San Rafael Swell, in eastern Utah, are presented, which has the goal of determining the potential contribution of radar image data to Landsat image data for rock type discrimination, particularly when the images are coregistered. The procedure employs several images processing techniques using the Landsat and Seasat data independently, and then both data sets are coregistered. The images are evaluated according to the ease with which contacts can be located and rock units (not just stratigraphically adjacent ones) separated. Results show that of the Landsat images evaluated, the image using a supervised classification scheme is the best for sedimentary rock type discrimination. Of less value, in decreasing order, are color ratio composites, principal components, and the standard color composite. In addition, for rock type discrimination, the black and white Seasat image is less useful than any of the Landsat color images by itself. However, it is found that the incorporation of the surface textural measures made from the Seasat image provides a considerable and worthwhile improvement in rock type discrimination.

Blom, R.↗

Image management research

Two types of research issues are involved in image management systems with space station applications: image processing research and image perception research. The image processing issues are the traditional ones of digitizing, coding, compressing, storing, analyzing, and displaying, but with a new emphasis on the constraints imposed by the human perceiver. Two image coding algorithms have been developed that may increase the efficiency of image management systems (IMS). Image perception research involves a study of the theoretical and practical aspects of visual perception of electronically displayed images. Issues include how rapidly a user can search through a library of images, how to make this search more efficient, and how to present images in terms of resolution and split screens. Other issues include optimal interface to an IMS and how to code images in a way that is optimal for the human perceiver. A test-bed within which such issues can be addressed has been designed.

Watson, Andrew B.↗

Developing tools for digital radar image data evaluation

The refinement of radar image analysis methods has led to a need for a systems approach to radar image processing software. Developments stimulated through satellite radar are combined with standard image processing techniques to create a user environment to manipulate and analyze airborne and satellite radar images. One aim is to create radar products for the user from the original data to enhance the ease of understanding the contents. The results are called secondary image products and derive from the original digital images. Another aim is to support interactive SAR image analysis. Software methods permit use of a digital height model to create ortho images, synthetic images, stereo-ortho images, radar maps or color combinations of different component products. Efforts are ongoing to integrate individual tools into a combined hardware/software environment for interactive radar image analysis.

Domik, G.↗

Spaceborne radar observations: A guide for Magellan radar-image analysis

Geologic analyses of spaceborne radar images of Earth are reviewed and summarized with respect to detecting, mapping, and interpreting impact craters, volcanic landforms, eolian and subsurface features, and tectonic landforms. Interpretations are illustrated mostly with Seasat synthetic aperture radar and shuttle-imaging-radar images. Analogies are drawn for the potential interpretation of radar images of Venus, with emphasis on the effects of variation in Magellan look angle with Venusian latitude. In each landform category, differences in feature perception and interpretive capability are related to variations in imaging geometry, spatial resolution, and wavelength of the imaging radar systems. Impact craters and other radially symmetrical features may show apparent bilateral symmetry parallel to the illumination vector at low look angles. The styles of eruption and the emplacement of major and minor volcanic constructs can be interpreted from morphological features observed in images. Radar responses that are governed by small-scale surface roughness may serve to distinguish flow types, but do not provide unambiguous information. Imaging of sand dunes is rigorously constrained by specific angular relations between the illumination vector and the orientation and angle of repose of the dune faces, but is independent of radar wavelength. With a single look angle, conditions that enable shallow subsurface imaging to occur do not provide the information necessary to determine whether the radar has recorded surface or subsurface features. The topographic linearity of many tectonic landforms is enhanced on images at regional and local scales, but the detection of structural detail is a strong function of illumination direction. Nontopographic tectonic lineaments may appear in response to contrasts in small-surface roughness or dielectric constant. The breakpoint for rough surfaces will vary by about 25 percent through the Magellan viewing geometries from low to high Venusian latitudes. Examples of anomalies and system artifacts that can affect image interpretation are described.

Ford, J. P.↗

Image processing software for providing radiometric inputs to land surface climatology models

During the First International Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), 80 gigabytes of image data were generated from a variety of satellite and airborne sensors in a multidisciplinary attempt to study energy and mass exchange between the land surface and the atmosphere. To make these data readily available to researchers with a range of image data handling experience and capabilities, unique image-processing software was designed to perform a variety of nonstandard image-processing manipulations and to derive a set of standard-format image products. The nonconventional features of the software include: (1) adding new layers of geographic coordinates, and solar and viewing conditions to existing data; (2) providing image polygon extraction and calibration of data to at-sensor radiances; and, (3) generating standard-format derived image products that can be easily incorporated into radiometric or climatology models. The derived image products consist of easily handled ASCII descriptor files, byte image data files, and additional per-pixel integer data files (e.g., geographic coordinates, and sun and viewing conditions). Details of the solutions to the image-processing problems, the conventions adopted for handling a variety of satellite and aircraft image data, and the applicability of the output products to quantitative modeling are presented. They should be of general interest to future experiment and data-handling design considerations.

Newcomer, Jeffrey A.↗

High-performance compression of astronomical images

Astronomical images have some rather unusual characteristics that make many existing image compression techniques either ineffective or inapplicable. A typical image consists of a nearly flat background sprinkled with point sources and occasional extended sources. The images are often noisy, so that lossless compression does not work very well; furthermore, the images are usually subjected to stringent quantitative analysis, so any lossy compression method must be proven not to discard useful information, but must instead discard only the noise. Finally, the images can be extremely large. For example, the Space Telescope Science Institute has digitized photographic plates covering the entire sky, generating 1500 images each having 14000 x 14000 16-bit pixels. Several astronomical groups are now constructing cameras with mosaics of large CCD's (each 2048 x 2048 or larger); these instruments will be used in projects that generate data at a rate exceeding 100 MBytes every 5 minutes for many years. An effective technique for image compression may be based on the H-transform (Fritze et al. 1977). The method that we have developed can be used for either lossless or lossy compression. The digitized sky survey images can be compressed by at least a factor of 10 with no noticeable losses in the astrometric and photometric properties of the compressed images. The method has been designed to be computationally efficient: compression or decompression of a 512 x 512 image requires only 4 seconds on a Sun SPARCstation 1. The algorithm uses only integer arithmetic, so it is completely reversible in its lossless mode, and it could easily be implemented in hardware for space applications.

White, Richard L.↗

Improved image decompression for reduced transform coding artifacts

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

Orourke, Thomas P.↗

Magnetospheric Image Unfolding

The Grant was a three year grant funded under the Space Physics Supporting Research and Technology and Suborbital Program. Our objective was to develop automated techniques needed to unfold or "invert" global images of the magnetospheric ion populations obtained by the new magnetospheric imaging techniques (ENA, EUV) in anticipation of future missions such as the Magnetospheric Imager and, now, IMAGE. Our focus on the present three year grant is to determine the degree to which such images can quantitatively constrain the global electromagnetic properties of the magnetosphere. In a previous three year grant period we successfully automated a forward modeling inversion algorithm, demonstrated that these inversions are robust in the face of realistic instrumental considerations such as counting statistics and backgrounds, applied error analysis techniques to the extracted parameters using variational procedures, implemented very realistic magnetospheric test images to test the inversion algorithms using the Rice University Magnetospheric Specification Model, and began the process of generating parametric models with the flexibility to handle the realistic magnetospheric images (e.g. Roelof et al, 1992; 1993). Our plan for the present 3 year grant period was to complete the development of the inversion tools needed to handle realistic magnetospheric images, assess the degree to which global electrodynamics is quantitatively constrained by ENA images of the magnetosphere, and bring the inversion of EUV images up to the maturity that we will have achieved for the ENA imaging. Below the accomplishments of our three year effort are present followed by a list of our presentations and publications. The accomplishments of all three years are presented here, and thus some of these items appeared on interim progress reports.

Source record↗

Neutral Networks for Subpixel Classification of Multispectral Images

In this work, the implementation and use of AVHRR (Advanced Very High Resolution Radiometer) images for subpixel analysis is studied. The work consists of two parts, the first is making training data, the second is using the training data to design a neural net subpixel analyzer. Most work on subpixel analysis has been done with images with more spectral bands. AVHRR images were chosen because of their easy acquisition, and because the five spectral bands allow investigation into the development of training data. The first step in subpixel analysis is the development of training data. This consists of image to be classified, and the classification of each pixel. In order to do the classification, a high spatial resolution image is typically needed in order to manually create a classified image. It is difficult to have both the image of interest, and a high spatial resolution image of the same area taken at the same time. Thus it was studied whether a subsampled image taken from the image of interest could serve as the training data. Statistical work has been done showing the unusefulness of this approach. In the second part of the analysis, a feedforward neural net was trained and used to classify the AVHRR images. Results of these tests, comparing the neural net with typical statistical based schemes are shown.

Figueroa, Ricardo R.↗