A Local Statistical Fuzzy Active Contour Model for Change Detection

In this letter, a statistical active contour model exploiting the local information is proposed for classifying changed and unchanged regions in the difference image. It incorporates the local information and fuzzy logic for the purpose of enhancing the changed information and of reducing the effect of speckle noise. The fuzzy length term and the fuzzy penalty term are added into the fuzzy energy function. In particular, in order to avoid deriving the complex fuzzy membership updating function, we solve the Euler-Lagrange equation to minimize the fuzzy energy function instead of calculating the fuzzy energy alterations directly. The experimental results on three synthetic aperture radar images confirm the performance of the proposed model over some existing methods.