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Efficient Self-Adaptive Image Deblurring Based on Model Parameter Optimization
Yang, Haoyuan1,2; Su, Xiuqin1; Ju, Chunwu2; Wu, Shaobo2
2018
会议名称3rd IEEE International Conference on Image, Vision and Computing (ICIVC)
会议录名称2018 IEEE 3RD INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC)
页码384-388
会议日期2018-06-27
会议地点Chongqing, PEOPLES R CHINA
出版者IEEE
产权排序1
摘要

Natural images suffer from degradations in imaging system, and image blur is a major source of them. Most existing approaches aim to estimate a blur kernel via an alternating optimization method in multiscale space. However, in our practical project application, we need to deal with motion blurs come from moving conveyor belts. In this case, the degradation model and its orientation are known to us. In this paper, we propose a self-adaptive image deblurring method to deal with it. The model parameters are optimized by a heuristic algorithm, and the latent images are deblurred by a deconvolution technique based on l(1) -norm constraint. Simulation results show that our method not only acts on motion blur model, but also can deal with atmosphere turbulence model and defocus model, and the comparison results indicate that it outperforms others'. Furthermore, it is able to deal with motion blur in real scenes with high efficiency.

作者部门光电测量技术实验室
收录类别EI ; CPCI
ISBN号978-1-5386-4991-6
语种英语
WOS记录号WOS:000448170000074
EI入藏号20184706085943
引用统计
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/30706
专题光电测量技术实验室
通讯作者Yang, Haoyuan
作者单位1.Xian Inst Opt & Precis Mech, Xian 710119, Shanxi, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714
Yang, Haoyuan,Su, Xiuqin,Ju, Chunwu,et al. Efficient Self-Adaptive Image Deblurring Based on Model Parameter Optimization[C]:IEEE,2018:384-388.
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