On detecting edges in speckle imagery

Methods for detecting sustained intensity changes in images corrupted by speckle are analyzed. The problem is complicated by the nature of the speckle, which is characterized by a high degree of correlation and (approximately multiplicative) signal dependence. These characteristics make the automated extraction of edges in speckle very difficult for applications requiring the location and identifications of objects (e.g., synthetic aperture radar). In particular, the Laplacian-of-a-Gaussian (LoG) edge detector for this problem is analyzed. While the LoG is found to be effective for detecting meaningful edges, use of the LoG also gives rise to numerous extraneous edges having no physical correlate. To alleviate these effects, a ratio-of-averages edge detector is used in conjunction with the LoG. The combined scheme is found to be much more effective than either of the individual edge detectors. Actual SEASAT synthetic aperture radar (SAR) images are used to demonstrate the effectiveness of each technique