Detection of object boundaries in synthetic aperture radar imagery using a human visual model

We consider the problem of automatically detecting sustained intensity changes, corresponding to object boundaries, in SAR imagery. The problem is complicated by the speckle noise found in SAR imagery, which is highly correlated and signal-dependent. In this paper, we analyze the efficacy of applying to this problem recently developed models for visual edge detection, in particular, the Marr-Hildreth Laplacian-of-a-Gaussian operator.