An improved image blind deblurring based on dark channel prior

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...

Full description

Saved in:
Bibliographic Details
Published in:Optoelectronics letters 2021, Vol.17 (1), p.40-46
Main Authors: Wang, Man-wei, Zhu, Fu-zhen, Bai, Yu-yang
Format: Article
Language:English
Subjects:
Algorithms
Image enhancement
Image quality
Image restoration
Lasers
Optical Devices
Optics
Photonics
Physics
Physics and Astronomy
Signal to noise ratio
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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 estimation more accurate. A combination of super Laplacian prior and dark channel prior is introduced to estimate the potential clear image. Then the accurate blur kernel is estimated through alternate iterations from coarse to fine. In the image restoration stage, a weighted least square filter is introduced to suppress the ringing effect of the original clear image to further improve the quality of image restoration. Finally, image deconvolution based on Laplace priors and L 0 regularized priors is used to restore clear images. Experimental results show that our approach improves the peak signal-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.
ISSN:1673-1905
1993-5013
DOI:10.1007/s11801-021-0081-y