Motion-Blurred Image Restoration Based on Joint Invertibility of PSFs  

作　　者：Yuye Zhang Jingli Huang Jiandong Liu Hakeel Ahmed Chohan 

机构地区：[1]Qingdao Branch,Navy Aeronautical and Astronautical University,Qingdao,266041,China [2]Dazzle Color Flower Core Speech Training School,Qingdao,266041,China

出　　处：《Computer Systems Science & Engineering》2021年第2期407-416,共10页计算机系统科学与工程（英文）

基　　金：funding of Natural Science Foundation of Shandong Province(ZR2013F0025),www.sdnsf.gov.cn.

摘　　要：To implement restoration in a single motion blurred image,the PSF(Point Spread Function)is difficult to estimate and the image deconvolution is ill-posed as a result that a good recovery effect cannot be obtained.Considering that several different PSFs can get joint invertibility to make restoration wellposed,we proposed a motion-blurred image restoration method based on joint invertibility of PSFs by means of computational photography.Firstly,we designed a set of observation device which composed by multiple cameras with the same parameters to shoot the moving target in the same field of view continuously to obtain the target images with the same background.The target images have the same brightness,but different exposure time and different motion blur length.It is easy to estimate the blur PSFs of the target images make use of the sequence frames obtained by one camera.According to the motion blur superposition feature of the target and its background,the complete blurred target images can be extracted from the observed images respectively.Finally,for the same target images with different PSFs,the iterative restoration is solved by joint solution of multiple images in spatial domain.The experiments showed that the moving target observation device designed by this method had lower requirements on hardware conditions,and the observed images are more convenient to use joint-PSF solution for image restoration,and the restoration results maintained details well and had lower signal noise ratio(SNR).

关 键 词：Motion-blurred image restoration PSF invertibility ill-posed problem computational photography 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]