High Order Total Variational Denoising Algorithm Based on l_0 Overlapping Combination Sparse

Abstract

Abstract:For addressing impulse noise in images, this paper proposes a denoising algorithm for non-convex impulse noise images based on the  norm fidelity term. Since the total variation of the  norm has a better denoising effect on the pulse noise, it is chosen as the model fidelity term, and the overlapping group sparse term combined with non-convex higher term is used as the regularization term of the model to protect the image edge texture and suppress the staircase effect. At the same time, the alternating direction method of multipliers, the majorization–minimization method and the mathematical program with equilibrium constraints were used to solve the model. Experimental results show that the proposed model can effectively suppress the staircase effect in smooth regions, protect the image edge details, and perform better in terms of the peak signal-to-noise ratio and the structural similarity index measure.