A fast algorithm for the total variation model of image denoising

The total variation model of Rudin, Osher, and Fatemi for image denoising is considered to be one of the best denoising models. In the past, its solutions were based on nonlinear partial differential equations and the resulting algorithms were very complicated. In this paper, we propose a fast algorithm for the solution of the total variation model. Our algorithm is very simple and does not involve partial differential equations. We also provide a rigorous proof for the convergence of our algorithm. Key words and phrases. total variation, optimization, image denoising. Supported in part by NSERC Canada under Grant OGP 121336 1 

• Type: Journal
• Year: 2010
• Where: ADCM
• Authors: Rong-Qing Jia, Hanqing Zhao
• Keywords: ADCM 2010, Algorithm, Denoising, Total Variation Model