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Semiblind Image Deconvolution with Spatially Adaptive Total Variation Regularization
2014
Mathematical Problems in Engineering
A semiblind image deconvolution algorithm with spatially adaptive total variation (SATV) regularization is introduced. The spatial information in different image regions is incorporated into regularization by using the edge indicator called difference eigenvalue to distinguish flat areas from edges. Meanwhile, the split Bregman method is used to optimize the proposed SATV model. The proposed algorithm integrates the spatial constraint and parametric blur-kernel and thus effectively reduces the
doi:10.1155/2014/606170
fatcat:ttpcn2uldjacbikcyo4xgf7gxe