A Nonmonotone Gradient Algorithm for Total Variation Image Denoising Problems. (15th September 2016)

• Record Type: Journal Article
• Authors: Wang, Peng; Yuan, Shifang; Xie, Xiangyun; Xiong, Shengwu
• Other Names: Solimene Raffaele Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2016(2016)
• Publication Date: 2016-09-15
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2016/4310612
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : The total variation (TV) model has been studied extensively because it is able to preserve sharp attributes and capture some sparsely critical information in images. However, TV denoising problem is usually ill-conditioned that the classical monotone projected gradient method cannot solve the problem efficiently. Therefore, a new strategy based on nonmonotone approach is digged out as accelerated spectral project gradient (ASPG) for solving TV. Furthermore, traditional TV is handled by vectorizing, which makes the scheme far more complicated for designing algorithms. In order to simplify the computing process, a new technique is developed in view of matrix rather than traditional vector. Numerical results proved that our ASPG algorithm is better than some state-of-the-art algorithms in both accuracy and convergence speed.