文献类型：期刊文献

英文题名：Single-image motion deblurring using an adaptive image prior

作者：He, Ning[1];Lu, Ke[2];Bao, Bing-Kun[3];Zhang, Lu-Lu[1];Wang, Jin-Bao[1]

第一作者：何宁

通讯作者：He, N[1]

机构：[1]Beijing Union Univ, Coll Informat Technol, Beijing Key Lab Informat Serv Engn, Beijing 100101, Peoples R China;[2]Univ Chinese Acad Sci, Beijing 100049, Peoples R China;[3]Chinese Acad Sci, Inst Automat, Beijing 100080, Peoples R China

第一机构：北京联合大学北京市信息服务工程重点实验室|北京联合大学智慧城市学院

通讯机构：[1]corresponding author), Beijing Union Univ, Coll Informat Technol, Beijing Key Lab Informat Serv Engn, Beijing 100101, Peoples R China.|[11417103]北京联合大学北京市信息服务工程重点实验室;[11417]北京联合大学;[1141734]北京联合大学智慧城市学院;

年份：2014

卷号：281

起止页码：736-749

外文期刊名：INFORMATION SCIENCES

收录：;EI(收录号：20143117996588);Scopus(收录号：2-s2.0-84904758223);WOS:【SCI-EXPANDED(收录号:WOS:000340315600052)】；

基金：This work was supported by the National Natural Science Foundation of China (Grant Nos. 61370138, 61271435, 61202245, 61103130, U1301251); National Program on Key Basic Research Projects (973 programs) (Grant Nos. 2010CB731804-1, 2011CB706901-4); The Project of Construction of Innovative Teams and Teacher Career Development for Universities and Colleges Under Beijing Municipality (No. IDHT20130513, CIT&TCD20130513), Beijing Municipal Natural Science Foundation (No. 4141003).

语种：英文

外文关键词：Motion deblurring; Point spread function; Adapting image prior; Spatially varying motion

摘要：Blind deblurring is the restoration of a sharp image from a blurred image when the blur kernel is unknown. Most image deblurring algorithms impose a uniform sparse gradient prior on the whole image, and reconstruct the image with piecewise smooth characteristics. Although the sparse gradient prior removes ringing and noise artifacts, it inevitably removes mid-frequency structures, leading to poor visual quality. The gradient profile of fractal-like structures is close to a Gaussian distribution, and small gradients from such regions are severely penalized by the sparse gradient prior. In this paper, we introduce an image deblurring algorithm that adapts the image prior to the underlying detailed structures. The statistics of a local detailed structure can be different from those of the global structure. By identifying the correct image prior for each pixel in the image, our approach models the spatially varying motion blur exhibited by camera motion more effectively than conventional methods based on space-invariant blur kernels. Using different priors for the local region and the motion blur kernel, we derive a minimization energy function that alternates between blur kernel estimation and deblurring image restoration until convergence. Experimental results demonstrate that the proposed approach is efficient and effective in reducing motion blur in an arbitrary direction in a single image. (C) 2014 Elsevier Inc. All rights reserved.