Single Space Shift Invariant Motion Blur Image Restoration Technology Research

How to restore clear images from degraded images is a challenging problem in the field of digital image processing. The purpose of image restore is to resume the distortion images to be similar with the original image. So it is necessary to measure the quality of restored image. If there is noise in the image, the image quality will be affected seriously. Therefore, we must consider the influence of noise.This paper introduce the noise effect on image and common noise model detailedly, analyzes the formation process of motion blurred image deeply and establish image degradation model and restoration model. After that, it presents the evaluation criterion of image quality. Then, it describes the common restore algorithm and analyzes on experiments. Finally, it suggests the importance of noise removing.This paper proposes a restoration algorithm for motion blurred image based on edge prior and wavelet analysis. We apply a preprocessing procedure before deblurring to remove noise, then use shock filter to enhance edges and Canny edge detection to get clear edges for estimating kernel by alternating iterative. After that, we set up minimum optimization model by using the sparsity of image in tight wavelet framelet. Furthermore, the adapted split Bregman method is proposed to solve the optimization problem. Finally, we will get the clear image. The experimental results show that the proposed method can effectively remove the motion blur.