An Adaptive Image Denoising Model Based on Tikhonov and TV Regularizations. (4th August 2014)

• Record Type: Journal Article
• Authors: Liu, Kui; Tan, Jieqing; Su, Benyue
• Other Names: Fan Jianping Academic Editor.
• Is Part Of: Advances in multimedia. Volume 2014(2014)
• Publication Date: 2014-08-04
• Subjects: Multimedia systems -- Periodicals; Computer networks -- Periodicals; Multimédia; Réseaux d'ordinateurs; Computer networks; Multimedia systems; Periodicals; 006.7
• DOI: 10.1155/2014/934834
• Languages: English
• ISSNs: 1687-5680

Abstract

Abstract : To avoid the staircase artifacts, an adaptive image denoising model is proposed by the weighted combination of Tikhonov regularization and total variation regularization. In our model, Tikhonov regularization and total variation regularization can be adaptively selected based on the gradient information of the image. When the pixels belong to the smooth regions, Tikhonov regularization is adopted, which can eliminate the staircase artifacts. When the pixels locate at the edges, total variation regularization is selected, which can preserve the edges. We employ the split Bregman method to solve our model. Experimental results demonstrate that our model can obtain better performance than those of other models.