Regularization with Adaptive Neighborhood Condition for Image Denoising

摘要: Image denoising by minimizing a similarity of neighborhood-based cost function is presented. This consists two parts, one related to data fidelity and the other structure preserving smoothing term. The latter controlled weight coefficient that measures neighborhood between pixels attaching an additional term penalizes it. Unlike most work in noise removal area, each pixel within not defined Gaussian function. obtained results show good performance our proposal, compared with some state-of-the-art algorithms.