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Proceedings Paper

Speckle and scene spatial statistical estimators for SAR image filtering and texture analysis: some applications to agriculture, forestry, and point targets detection
Author(s): Edmond Nezry; Marc Leysen; Gianfranco D. de Grandi
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Paper Abstract

Most of the processing/analysis tools for SAR images, and particularly the most usual speckle filters, are based on the use of first order local statistics (local mean and local variance). In order to account for the effects due to the spatial correlation of both the speckle and the scene in SAR images, estimators originating from the local autocorrelation functions (ACF) are used, to refine the evaluation of the non-stationary first order local statistics, as well as to detect the structural elements of the scene. The aim is to enhance scene textural properties, and to preserve the useful spatial resolution in the speckle filtered image. To detect and preserve very thin scene structures in the presence of speckle, an heuristic implementation of these estimators is presented for the case of multilook SAR images. Results obtained on 7-look airborne C-SAR and 3-look spaceborne ERS PRI images with different spatial resolutions illustrate the performance of these estimators, either implemented in the speckle filter, or for texture analysis, or for small/thin scene objects detection. Finally, it is shown how two-points statistics and derived indices can be used as texture analysis tools or as discriminators. Some ERS applications using these techniques, either for speckle filtering, or for texture-based analysis, are briefly presented.

Paper Details

Date Published: 21 November 1995
PDF: 11 pages
Proc. SPIE 2584, Synthetic Aperture Radar and Passive Microwave Sensing, (21 November 1995); doi: 10.1117/12.227163
Show Author Affiliations
Edmond Nezry, Institute for Remote Sensing Applications (Italy)
Marc Leysen, Institute for Remote Sensing Applications (Italy)
Gianfranco D. de Grandi, Institute for Remote Sensing Applications (Italy)

Published in SPIE Proceedings Vol. 2584:
Synthetic Aperture Radar and Passive Microwave Sensing
Giorgio Franceschetti; Christopher John Oliver; James C. Shiue; Shahram Tajbakhsh, Editor(s)

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