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Proceedings Paper

Application of sparse dictionaries to SAR speckle reduction
Author(s): Thomas R. Braun; John B. Greer
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Paper 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.

Paper Details

Date Published: 19 April 2010
PDF: 11 pages
Proc. SPIE 7699, Algorithms for Synthetic Aperture Radar Imagery XVII, 76990R (19 April 2010); doi: 10.1117/12.849535
Show Author Affiliations
Thomas R. Braun, National Geospatial-Intelligence Agency (United States)
John B. Greer, National Geospatial-Intelligence Agency (United States)


Published in SPIE Proceedings Vol. 7699:
Algorithms for Synthetic Aperture Radar Imagery XVII
Edmund G. Zelnio; Frederick D. Garber, Editor(s)

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