关键词: 图像去噪, 结构相似度, 梯度下降法, 交替迭代法

Abstract:

In this paper,we make one of the first attempts to incorporate the structural similarity as the fidelity term into the framework of image denoising in order to overcome the weakness that the fidelity term of the classical ROF model does not consider image structure,which leads to poor visual image restoration.This paper first proposes a new image denoising model (model 1) by introducing structural similarity as the fidelity term instead of the original.In promotion model 2,a nonconvex regularization rather than the classical TV regularization is used to preserve the edge better while removing noises.Experimental results show model 1 and model 2 achieve better performance than ROF model in image structural information and perceptual image quality.And model 2 plays a more important role in preserving image edge than model 1.

Key words: image denoising;structural similarity;gradient descent method;alternative iteration strategy