We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Overview of Blind Deblurring Methods for Single Image.
- Authors
LIU Liping; SUN Jian; GAO Shiyan
- Abstract
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 qualitatively analyzed and compared on the public deblurring dataset. Finally, the problems faced by the current image deblurring methods are analyzed, the research trend of image deblurring methods is prospected, and the main problems existing in single image blind deblurring are analyzed. The available solutions or ideas are explained one by one, which provides a theoretical basis for the follow-up research.
- Subjects
IMAGE stabilization; DEEP learning; COMPUTER vision; IMAGE processing
- Publication
Journal of Frontiers of Computer Science & Technology, 2022, Vol 16, Issue 3, p552
- ISSN
1673-9418
- Publication type
Article
- DOI
10.3778/j.issn.1673-9418.2106100