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18 April 2010 Application of sparse dictionaries to SAR speckle reduction
Thomas R. Braun, John B. Greer
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Proceedings Volume 7699, Algorithms for Synthetic Aperture Radar Imagery XVII; 76990R (2010) https://doi.org/10.1117/12.849535
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States
Abstract
Synthetic Aperture Radar (SAR) provides day/night all weather imagery, and as such is being increasingly utilized for overhead reconnaissance. Additionally, the active, coherent nature of the system provides for analysis not readily achievable with electro-optical imagery. However, like all coherent systems, SAR imagery suffers degradation from speckle (a random interference pattern) which hinders interpretation. Herein, we investigate SAR denoising with a new method based on sparse reconstruction over learned dictionaries and show this approach performs better than the current state of the art speckle filters.
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Thomas R. Braun and John B. Greer "Application of sparse dictionaries to SAR speckle reduction", Proc. SPIE 7699, Algorithms for Synthetic Aperture Radar Imagery XVII, 76990R (18 April 2010); https://doi.org/10.1117/12.849535
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KEYWORDS
Speckle
Associative arrays
Synthetic aperture radar
Image filtering
Boxcar filters
Denoising
Image resolution
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