Image Reconstruction from Sparse Samples Using Directional Total Variation Minimization
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This paper considers reconstruction of missing pixels and formulates the problem under directional total variation (DTV) regularization. In order to devise an algorithm, forward-backward splitting method is used as a convex optimization tool, in conjunction with a fast projected gradient-based algorithm. The results are compared with the results of TV-based setting, and the utility of using DTV is shown in terms of accuracy, when an image with a dominant direction is the case.
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