An improved image blind deblurring based on dark channel prior

• 作者: WANG Man-wei ZHU Fu-zhen BAI Yu-yang
• 来源期刊: 光电子快报（英文版）
• 年，卷（期）: 2021,（1）
• 所属期刊栏目: Image and Information Processing
• 页码范围: 40-46
• 页数: 7页
• 语种: 英文
• DOI: 10.1007/s11801-021-0081-y

摘要

In order to solve the ringing effect caused by the incorrect estimation of the blur kernel,an improved blind image deblurring algorithm based on the dark channel prior is proposed.First,in the blur kernel estimation stage,high-pass filtering is introduced to enhance the image quality and enhance the edge information to make the blur kernel estima-tion more accurate.A combination of super Laplacian prior and dark channel prior is introduced to estimate the poten-tial clear image.Then the accurate blur kernel is estimated through alternate iterations from coarse to fine.In the im-age restoration stage,a weighted least square filter is introduced to suppress the ringing effect of the original clear im-age to further improve the quality of image restoration.Finally,image deconvolution based on Laplace priors and Lo regularized priors is used to restore clear images.Experimental results show that our approach improves the peak sig-nal-to-noise ratio(PSNR)by about 0.4 dB and structural similarity(SSIM)by about 0.01,respectively.Compared with the existing image deblurring algorithms,this method can estimate the blur information more accurately,so that the restored image can achieve the effect of keeping the edges and removing ringing.