Maximum entropy methods for despeckling and resampling synthetic aperture radar images of rough terrain

Mihai P. Datcu; Marc Walessa

doi:10.1117/12.295634

22 December 1997 Maximum-entropy methods for despeckling and resampling synthetic aperture radar images of rough terrain

Mihai P. Datcu, Marc Walessa

Author Affiliations +

Proceedings Volume 3217, Image Processing, Signal Processing, and Synthetic Aperture Radar for Remote Sensing; (1997) https://doi.org/10.1117/12.295634
Event: Aerospace Remote Sensing '97, 1997, London, United Kingdom

Abstract

SAR systems, like any coherent imaging system, are subject to (I) speckling effects, which considerably reduce the useful detail within the acquired scenes and (II), strong geometric distortions. Furthermore, the resolution of SAR systems is comparable to the size of many of the objects of interest in the scene. Our paper proposes a unified treatment of these problems within the framework of probabilistic inference. Despeckling and segmentation are the main objectives only in the first case. In the second case, due to the strong geometric aberrations introduced by the SAR image formation system, the emphasis is on image resampling, with speckle reduction and image segmentation as collateral, but strongly related issues. In both cases, the model is built upon the statistical properties of the speckle noise and the SAR image formation equations.

Citation Download Citation

Mihai P. Datcu and Marc Walessa "Maximum-entropy methods for despeckling and resampling synthetic aperture radar images of rough terrain", Proc. SPIE 3217, Image Processing, Signal Processing, and Synthetic Aperture Radar for Remote Sensing, (22 December 1997); https://doi.org/10.1117/12.295634

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