Sandia Corporation

National Technology & Engineering Solutions of Sandia, LLC

Mary M Moya

Mark W Koch

David Nikolaus Perkins

Roger Derek West

Jody L Smith

Laurence S Costin

Jeffrey A Mercier

Charles L Walker

Described herein are various technologies relating to generating a reduced bias multi-resolution (RBMR) coherent change detection (CCD) image product. A low bias, low resolution (LBLR) CCD image product is generated based upon a first SAR image of a scene and a second SAR image of the scene, where each pixel in the LBLR CCD image has a respective value that is computed using a large box-filter. The LBLR CCD image is segmented into a plurality of segments, and a box-filter size is determined for each segment based upon values of pixels in the segment. A RBMR CCD image product is then computed using box-filters of the determined sizes.

Reduced-bias multi-resolution coherent change detection

Various embodiments presented herein relate to assigning labels to segments of a synthetic aperture radar (SAR) image, where the segments are based upon a speckle-reduced SAR image product. A plurality of SAR images of a scene are co-registered to form a registered stack of SAR images. A speckle-reduced SAR image product is generated based upon at least one registered SAR image in the registered stack of SAR images. The speckle-reduced SAR image product is segmented into a plurality of superpixels, and boundaries of the superpixels are applied to the at least one registered SAR image to form a segmented SAR image. A segment of the SAR image is then labeled as including or not including a feature, wherein the label is assigned based upon values of pixels in the segment.

Superpixels for improved structure and terrain classification using multiple synthetic aperture radar image products

Various embodiments presented herein relate to identifying one or more edges in a synthetic aperture radar (SAR) image comprising a plurality of superpixels. Superpixels sharing an edge (or boundary) can be identified and one or more properties of the shared superpixels can be compared to determine whether the superpixels form the same or two different features. Where the superpixels form the same feature the edge is identified as an internal edge. Where the superpixels form two different features, the edge is identified as an external edge. Based upon classification of the superpixels, the external edge can be further determined to form part of a roof, wall, etc. The superpixels can be formed from a speckle-reduced SAR image product formed from a registered stack of SAR images, which is further segmented into a plurality of superpixels. The edge identification process is applied to the SAR image comprising the superpixels and edges.

Superpixel edges for boundary detection

A method for estimating the thermal properties of surface materials using long-wavelength thermal imagery by exploiting the differential heating histories of ground points in the vicinity of shadows. The use of differential heating histories of different ground points of the same surface material allows the use of a single image acquisition step to provide the necessary variation in measured parameters for calculation of the thermal properties of surface materials.

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Albuquerque, NM, United States of America

Mary M Moya