单图像盲去模糊方法概述

图像去模糊长期以来一直是计算机视觉和图像处理中的研究热点。由相机抖动、物体运动或失焦引起的运动模糊或焦点模糊图像会严重影响图像的使用和后续处理。传统的盲去模糊方法利用图像运动模糊产生的不同原因,可将运动模糊分为全局运动模糊和局部运动模糊。概述了近年来图像盲去模糊的方法和研究现状。在深度学习图像去模糊方法的基础上,总结了图像去模糊的方法及研究现状。同时,对传统的盲去模糊方法和深度学习的盲去模糊方法进行了分类总结,归纳了图像去模糊前所需数据集的三种构成方式和图像去模糊后的质量评价标准,然后在公共去模糊数据集上对部分传统去模糊和深度学习去模糊的方法进行了定量和定性的分析比较。最后,分析了当前图像去模糊方法面临的问题,展望了图像去模糊方法的研究趋势,并且对目前单图像盲去模糊存在的主要问题进行了拓展分析,逐一细化地说明了可用的解决方法或解决思路,为后续的研究提供了一定的理论依据。

Overview of Blind Deblurring Methods for Single Image

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.