Dictionary-Based Image Denoising by Fused-Lasso Atom Selection. (28th August 2014)

• Record Type: Journal Article
• Authors: Li, Ao; Shouno, Hayaru
• Other Names: Roque Carla Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2014(2014)
• Publication Date: 2014-08-28
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2014/368602
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : We proposed an efficient image denoising scheme by fused lasso with dictionary learning. The scheme has two important contributions. The first one is that we learned the patch-based adaptive dictionary by principal component analysis (PCA) with clustering the image into many subsets, which can better preserve the local geometric structure. The second one is that we coded the patches in each subset by fused lasso with the clustering learned dictionary and proposed an iterative Split Bregman to solve it rapidly. We present the capabilities with several experiments. The results show that the proposed scheme is competitive to some excellent denoising algorithms.