Research On The Key Technology Of Single Motion Blurred Image Restoration

Restoration of single blurred image is a key research topic in the field of digital multimedia.The phenomenon of motion blur is becoming more and more common within the image,in the daily life and work.However,the demand for high quality images is increasing.Therefore,research on single motion blurred image restoration technology has certain value and significance.Aiming at the restoration of single motion blurred image,the key technology of single motion blurred image restoration under the condition of unknown blurred kernel is studied in this paper.The main research content includes the following two aspects:To improve the efficiency of blur kernel estimation based on prior knowledge,a method of deblurring an image based on rich edge region extraction using a gray-level co-occurrence matrix is proposed.First,the relationship between the image edge information and the related coefficients of a gray-level co-occurrence matrix is analyzed,based on which,an index representing the amount of image edge information is proposed.Next,high-frequency layer information is extracted from the blurred image to be processed with a bilinear interpolation method in the luminance channel.Subsequently,the rich edge region index of each region is calculated based on a sliding window;then,the region with the richest edge information is extracted.Finally,the extracted rich edge region,instead of the entire motion blurred image,is used to estimate the blur kernel with LO-regularized intensity and gradient prior,based on which,the blurred image is blindly restored.Experimental results show that the proposed method can improve the recovery efficiency while ensuring the recovery quality as well.The proposed algorithm not only achieves the restoration of the actual blurred image,but also improves the recovery efficiency.To reduce the ringing effect caused by image boundary truncation in motion blurred image restoration,an algorithm based on the sine integral fitting mask function is proposed.First,the boundaries of blurred image to be restored are extended according to the size of blur kernel;second,mask function is calculated based on sine function integration for one-direction region and two-direction region;third,the mask function is applied to update the image;finally,the new image is restored and the original area is extracted.Experiments results show the proposed approach can preserve the image edge completely and ensure less calculation as well when it is used to suppress ringing effect,which is superior to other traditional methods.