An efficient algorithm for adaptive total variation based image decomposition and restoration

International Journal of Applied Mathematics and Computer Science

Huang Lihong¹  Liu Xinwu² 

[1] ;School of Mathematics and Computational Science Hunan University of Science and Technology, Xiangtan, Hunan 411201, China;

关键词: image decomposition;    image restoration;    adaptive total variation;    h−1 norm;    split bregman method;   

DOI  :  10.2478/amcs-2014-0031

来源: DOAJ

【 摘 要 】

With the aim to better preserve sharp edges and important structure features in the recovered image, this article researches an improved adaptive total variation regularization and H−1 norm fidelity based strategy for image decomposition and restoration. Computationally, for minimizing the proposed energy functional, we investigate an efficient numerical algorithm—the split Bregman method, and briefly prove its convergence. In addition, comparisons are also made with the classical OSV (Osher–Sole–Vese) model (Osher et al., 2003) and the TV-Gabor model (Aujol et al., 2006), in terms of the edge-preserving capability and the recovered results. Numerical experiments markedly demonstrate that our novel scheme yields significantly better outcomes in image decomposition and denoising than the existing models.

【 授权许可】

Unknown