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作 者:Tianlin Zhang Jinjiang Li Hui Fan
机构地区:[1]School of Information and Electronic Engineering,Shandong Technology and Business University,Yantai 264005,China [2]School of Computer Science and Technology,Shandong Technology and Business University,Yantai 264005,China [3]Institute of ZhongKe Network Technology,Yantai 264005,China
出 处:《Computational Visual Media》2022年第3期495-508,共14页计算可视媒体(英文版)
基 金:National Natural Science Foundation of China(61772319,62002200,61976125,61976124);Shandong Natural Science Foundation of China(ZR2017MF049)。
摘 要:Deblurring images of dynamic scenes is a challenging task because blurring occurs due to a combination of many factors.In recent years,the use of multi-scale pyramid methods to recover high-resolution sharp images has been extensively studied.We have made improvements to the lack of detail recovery in the cascade structure through a network using progressive integration of data streams.Our new multi-scale structure and edge feature perception design deals with changes in blurring at different spatial scales and enhances the sensitivity of the network to blurred edges.The coarse-to-fine architecture restores the image structure,first performing global adjustments,and then performing local refinement.In this way,not only is global correlation considered,but also residual information is used to significantly improve image restoration and enhance texture details.Experimental results show quantitative and qualitative improvements over existing methods.
关 键 词:image deblurring dynamic scenes multiscale edge features
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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