An MRF Model-Based Approach to Simultaneous Recovery of Depth and Restoration from Defocused Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
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A maximum likelihood-based method is proposed for blur identification from multiple observations of a scene. When the relations among the blurring functions are known, the estimate of blur obtained using the proposed method is very good. Since direct computation of the likelihood function becomes difficult as the number of images increases, we propose an algorithm to compute the likelihood function recursively