Image Denoising Based on the Surface Fitting Strategy

In this work, we propose a surface fitting strategy based on a two-step model to remove noise from digital images. In the first step, we minimize the total variation energy functional of an image by using the projection gradient method in order to obtain the dual variable as the smoothed normal vector. In the second step, we try to find a surface as the recovered image to fit the smoothed normal vector. Based on the projection gradient method and the variable splitting method, we propose an efficient numerical method to solve this two-step model and also give the convergence analysis of the proposed method. Some numerical comparisons are given to validate the effectiveness of our proposed model.