Mean field approximation using compound Gauss-Markov random field for edge detection and image restoration

A composed Gauss-Markov random field (CGMRF) model is used with mean field approximation for edge detection and image restoration. A set of iterative equations is presented for the mean values of the intensity field and both horizontal and vertical line processes. It is shown that if the CGMRF is isotropic, the same equations as those of Geiger and Girosi (1989) are obtained. How the proposed method is related to the graduated nonconvexity technique using CGMRF is shown. From an implementation point of view, the emphasis is on the use of an optimal step-descent method to get a robust algorithm. Edge detection and image restoration results from a noisy image are presented.<<ETX>>

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