Motion deblurring based on edge prior

Restoring clear image from degraded images has long been one challenging problem in digital imaging. In this paper, we present a deblurring method with edge prior and wavelet analysis. A preprocessing step is proposed to remove noise before deblurring, then uses shock filter to enhance edges and canny operation to detect edges for estimating kernel. After that, maximize the sparsity of clear image under tight wavelet frame system. Furthermore, the split Bregman method is proposed to solve the optimization problem. Finally, we will get the clear image. The experiments show that our algorithm can remove motion blurring effectively.