Analysis of SAR speckle statistics in support of image filtering and interpretation
Thomas Esch, Andreas Schenk, Michael Thiel, Achim Roth, Michael Schmidt, Stefan W. Dech · elib (German Aerospace Center) · 2008
This study presents an automated approach towards the evaluation of speckle noise statistics in SAR images. Based on the statistical information we derive a textural feature – the so-called speckle divergence - which describes the deviation of local speckle behavior from the scene-specific heterogeneity of fully developed speckle. We show that the speckle divergence is a valuable input parameter for adaptive speckle suppression by introducing a spatially adaptive and radiometrically selective speckle filter algorithm. Moreover the benefit of speckle divergence for both the identification of built-up areas and the generation of a color composite product on the basis of one single-polarized SAR image is presented.