Title: | A Primal-Dual Active-Set Method for Non-negativity Constrained Total Variation Deblurring Problems |
Speaker: | Dr. Andy Ming-Ham Yip, Department of Mathematics, National University of Singapore, Singapore |
Time/Place: | 11:00 - 12:00 FSC 1217 |
Abstract: | We study image deblurring problems using a total variation based model, with a non-negativity constraint. The addition of the constraint improves the quality of the solutions but makes the solution process a difficult one. The contribution of our work is a fast and robust numerical algorithm to solve the non-negatively constrained problem. We formulate the constrained deblurring problem as a primal-dual program. Here, dual refers to a combination of Lagrangian and Fenchel duals. The problem is solved by a combination of the semi-smooth Newton's method and the primal-dual active-set method. The main advantages of our proposed scheme are: no parameters need significant adjustment, a standard inverse preconditioner works very well, quadratic rate of local convergence, numerical evidence of global convergence, and high accuracy of solving the optimality system. This is a joint work with Dilip Krishnan and Ping Lin. |
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