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.
https://hal.inria.fr/hal-01626912 Contributor : Hal IfipConnect in order to contact the contributor Submitted on : Tuesday, October 31, 2017 - 2:41:18 PM Last modification on : Thursday, February 7, 2019 - 3:56:09 PM Long-term archiving on: : Thursday, February 1, 2018 - 1:08:49 PM
Germana Landi. Sparsity Constrained Image Restoration: An Approach Using the Newton Projection Method. 27th IFIP Conference on System Modeling and Optimization (CSMO), Jun 2015, Sophia Antipolis, France. pp.341-350, ⟨10.1007/978-3-319-55795-3_32⟩. ⟨hal-01626912⟩