An image restoration model combining mixed L1/L2 fidelity terms

Image restoration is a common problem in visual process. In this paper, a modified minimization model is presented, which combines the L-1 and L-2 fidelity terms with a combined quadratic L-2 and TV regularizer just as the regularizer of Cai et al. (2013). The combined regularizer has the priorities of preserving desirable edges and ensuring several kinds of noises can be removed clearly. Split-Bregman algorithm is efficiently employed to solve this model and convergence analysis is also discussed. Moreover, we extend the proposed model and algorithm for image restoration involving blurry images and color images. Experimental results show that our proposed model and algorithm have good performance both in visual and ISNR values for different kinds of blurs and noises including mixed noise. (C) 2016 Elsevier Inc. All rights reserved.