Abstract
Image denoising is one of the fundamental problems in the image processing. In a PDE based approach for image processing, the simplest possible method for denoising is to solve the heat equation. However such a diffusion equation will destroy sharp edges in the image. An approach known for preserving the edges while denoising is called the classical Rudin-Osher-Fatemi (ROF) method based on the total variation (TV) regularization. Recently, an algorithm, also known as the TV-Stokes, based on two minimization steps involving the smoothing of the tangential field and then the reconstruction of the image has been proposed. The latter produces images without the blocky effect which we observe in the case of the ROF model. An iterative regularization method for the total variation based image restoration has recently been proposed giving significant improvement over the classical method in the quality of the restored image. In this paper we propose a similar algorithm for the TV-Stokes denoising algorithm.
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