New total variation regularized L1 model for image restoration

Authors:
Yuying Shi;Xiaozhong Yang
Affiliations:
Department of Mathematics and Physics, North China Electric Power University, Beijing 102206, China;Department of Mathematics and Physics, North China Electric Power University, Beijing 102206, China
Venue:
Digital Signal Processing
Year:
2010

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Abstract

In this paper, we propose three new time dependent models based on total variation regularized L^1 model for solving total variation minimization problems in image restoration. The main idea is to apply a priori smoothness on the solution image and to regularize the parabolic term. We propose a kind of continuous boundary conditions, i.e. mean boundary conditions. Numerical experimental results demonstrate that the three new models need far less iterations than the original total variation L^1 model and mean boundary conditions are efficient for image restoration.