http://popups.lib.uliege.be/1373-5411/index.php?id=1713 Image restoration is a typical ill-posed problem. Regularization technic represented by a regularized MP-Inverse filter (RMPIF) is widely used to deal with the ill-posedness. In order to derive the best performance of the filter, the parameter, which controls the regularizability, should be appropriately chosen. In this paper, we present a new criterion for parameter choosing based on modifying the subspace information criterion which is first proposed for model selection of supervised learning problems. Some numerical examples are also shown to verify the efficacy of the proposed criterion. Full text issues Volume 12 Soft Computing and Computational Intelligence fr Tue, 16 Jul 2024 12:03:55 +0200 Tue, 16 Jul 2024 12:04:06 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=1713 0