An image restoration method based on PDEs and a new gradient model
Lei Xu, Xiaoling Zhang, Kin‐Man Lam · 2010
The goal of image restoration is to eliminate noise and insignificant details from a blurred or noise-affected image, without blurring important semantic structures such as edges. In this paper, we propose a new approach based on partial differential equations (PDEs) by adjusting the threshold when iteration proceeds, and a new gradient model based on the idea of bilateral filtering, which can retain more visual details than other methods. With this new approach, the noise can be removed efficiently while preserving important semantic structures such as edges.