Sparsity Constrained Image Restoration: An Approach Using the Newton Projection Method

Abstract : Image restoration under sparsity constraints has received increased attention in recent years. This problem can be formulated as a nondifferentiable convex optimization problem whose solution is challenging. In this work, the non-differentiability of the objective is addressed by reformulating the image restoration problem as a nonnegatively constrained quadratic program which is then solved by a specialized Newton projection method where the search direction computation only requires matrix-vector operations. A comparative study with state-of-the-art methods is performed in order to illustrate the efficiency and effectiveness of the proposed approach.
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Communication dans un congrès
Lorena Bociu; Jean-Antoine Désidéri; Abderrahmane Habbal. 27th IFIP Conference on System Modeling and Optimization (CSMO), Jun 2015, Sophia Antipolis, France. Springer International Publishing, IFIP Advances in Information and Communication Technology, AICT-494, pp.341-350, 2016, System Modeling and Optimization. 〈10.1007/978-3-319-55795-3_32〉
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Germana Landi. Sparsity Constrained Image Restoration: An Approach Using the Newton Projection Method. Lorena Bociu; Jean-Antoine Désidéri; Abderrahmane Habbal. 27th IFIP Conference on System Modeling and Optimization (CSMO), Jun 2015, Sophia Antipolis, France. Springer International Publishing, IFIP Advances in Information and Communication Technology, AICT-494, pp.341-350, 2016, System Modeling and Optimization. 〈10.1007/978-3-319-55795-3_32〉. 〈hal-01626912〉

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