Move space based total variation image denoising

The total variation model is widely used in computer vision and image processing. This paper presents a total variation image denoising method based on move space. In this method, the minimum problem of energy function based on total variation model is mapped to an optimal label problem in move space, which could be solved by minimum cut/maximum flow algorithm. This method avoids the computing trouble occurred in classical minimization methods. In addition, the regularization parameter can be adaptively set according to the local character of the noised image. In this way, the minimization method proposed avoids the staircase effect and over smoothing occurred in some classical total variation minimization methods. Experimental results show that the method proposed is preferable to classical total variation minimization methods in image denoising performance.