Blind Image Restoration Based on Selected Gradients
Baichao Wang, Zhenan Sun, Haijun Su · 2010
This paper proposes a novel and improved method to restore latent clear image from a single blurred image using some specifically selected image gradients. This paper uses an alternative minimization method to optimize the objective function and obtain both the latent image and the point spread function(PSF). Most state-of-the-art blind image restoration methods need a time-consuming and noise-prone step to predict the strong edges of latent images. A great contribution of the proposed method is that such a step is avoided since our method can estimate the PSF efficiently through selected image gradients. Because the estimation model of PSF is well-posed,this paper presents a much faster algorithm to achieve the PSF estimation function. In some specific applications such as iris image restoration, the efficiency of our method can be further improved via selection of a representative image region for PSF estimation.