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《Acta Photonica Sinica》 2018-10
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Blind Image Deblurring via Multi-local Kernels′Fusion

CHEN Chun-lei;YE Dong-yi;CHEN Zhao-jiong;College of Mathematics and Computer Science,Fuzhou University;Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing,Fuzhou University;Key Laboratory of Spatial Data Mining and Information Sharing,Ministry of Education,Fuzhou University;  
A multi-local kernels′fusion algorithm is proposed to solve the problem of high complexity of dark channel priors.In this algorithm,the local kernels are computed and solved in parallel,and then merged into a global kernel(point spread function)by using the shape similarity of local kernels.For the noise that has appeared on the initially merged global kernel,the relevance adjustment is introduced using the neighboring information to further improve the fusion effect.Experiments show that the proposed algorithm can effectively improve the speed of image deblurring while guaranteeing the deblurring effect.It also has better effect on the local detail restoration of some real blurred images,and can handle largesize blurred images well.
【Fund】: 国家自然科学基金项目(No.61672158);; 福建省自然基金(No.2018J1798)资助~~
【CateGory Index】: TP391.41
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