Overview of Blind Deblurring Methods for Single Image

• Published in: Jisuanji kexue yu tansuo Vol. 16; no. 3; pp. 552 - 564
• Main Author: LIU Liping, SUN Jian, GAO Shiyan
• Format: Journal Article
• Language: Chinese
• Published: Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press 01.03.2022
• Subjects: blind deblurring|motion blur|deep learning
• ISSN: 1673-9418
• DOI: 10.3778/j.issn.1673-9418.2106100

Image deblurring has been a research hotspot in computer vision and image processing for a long time. The motion blur or focus blur image caused by camera jitter, object motion or defocus will seriously affect the use and follow-up processing of the image. The traditional blind deblurring methods make use of different causes of image motion blur, dividing motion blur into global motion blur and local motion blur. This paper summarizes the methods and research status of image blind deblurring in recent years. Then, on the basis of deep learning image deblurring methods, the image deblurring methods and research status are summarized. At the same time, the traditional blind deblurring methods and deep learning blind deblurring methods are classified and summarized, and the three forms of datasets needed before image deblurring and the quality evaluation criteria after image deblurring are summarized. Then, some of the traditional deblurring and deep learning deblurring methods are quantitatively and qualitative