An Iterative Regularization Method for Total Variation-Based Image Restoration

An Iterative Regularization Method for Total Variation-Based Image Restoration

We introduce a new iterative regularization procedure for inverse problems based on the use of Bregman distances, with particular focus on problems arising in image processing. We are motivated by the problem of restoring noisy and blurry images via variational methods, by using total variation regularization. We obtain rigorous convergence results, and effective stopping criteria for the gener...

Iterative Nonlocal Total Variation Regularization Method for Image Restoration

In this paper, a Bregman iteration based total variation image restoration algorithm is proposed. Based on the Bregman iteration, the algorithm splits the original total variation problem into sub-problems that are easy to solve. Moreover, non-local regularization is introduced into the proposed algorithm, and a method to choose the non-local filter parameter locally and adaptively is proposed....

An Iterative Conjugate Gradient Regularization Method for Image Restoration

Image restoration is an ill-posed inverse problem, which has been introduced the regularization method to suppress over-amplification. In this paper, we propose to apply the iterative regularization method to the image restoration problem and present a nested iterative method, called iterative conjugate gradient regularization method. Convergence properties are established in detail. Based on [...

Iterative Methods for Total Variation Image Restoration 1

Total Variation Based Methods for Image Restoration

Contacts: Tel: (65)-6516-6250 Office: S14-05-21 Email: [email protected] I mage restoration refers to the process of recovering an ideal image from its corrupted version which is the one we actually observe. The corruptions may be due to noise along the way of acquisition, out-of-focus of the imaging device, or packet loss during transmission of an acquired image from one location to another. ...