Abstract
Edge detection is a fundamental issue in image analysis. Due to the presence of speckle, which can be modelled as a strong multiplicative noise, edge detection in synthetic aperture radar (SAR) images is very difficult and methods developed for optical images are inefficient. We here propose a new edge detector for SAR images which is optimum in the MMSE sense for a stochastic multiedge model. It computes a normalized ratio of exponentially weighted averages (ROEWA) on opposite sides of the central pixel. This is done in the horizontal and vertical direction, and the module of the two components yields an edge strength map. Thresholding of the edge strength map and postprocessing to eliminate false edges are briefly discussed. We present results on simulated SAR images and ERS1 data.
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