Adaptive total variation model for image denoising with fast solving algorithm
Tian Xu · Jisuanji yingyong yanjiu · 2011
This paper combined shock filter with anisotropic diffusion to preprocess the noisy images,and used the edge detection filters to choose the parameters adaptively based on the preprocessed images.Then introduced an adaptive total variation regularization model for image denoising based on the chosen parameters.The proposed model could keep the balance between noises smoothing and edges preserving adaptively.Furthermore,it proposed a fast iterative algorithm to solve the proposed adaptive model based on Bregman iteration regularization method.The numerical results show that the proposed model and fast algorithm can smooth the noises and preserve the edge and fine detail information properly with fast solving convergence rate,while the peak signal to noise ratio,mean structural similarity and subjective visual effect of the denoised images are improved obviously.