Abstract
In coastline detection, for synthetic aperture radar (SAR) images, active contour model based on gamma distribution faced unsatisfactory results especially in weak edge region. To solve this problem, we present a coastline detection algorithm with active contour model based on inverse gaussian distribution. Assuming that speckles of SAR images obey inverse Gaussian distribution. The energy functional based on the inverse gaussian distribution is constructed by the maximum likelihood estimation method, and then the active contour model is obtained by introducing the level set function and the length term. Through mathematical derivation, the level set evolution equation is obtained, which is used for coastline detection in SAR image. In experiment, single polarized envisat-1 and envisat-2 of SAR images are utilized. Experimental results show that the proposed algorithm has better detection capability than Gamma model.
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