CASIA OpenIR  > 模式识别国家重点实验室  > 图像与视频分析
An adaptive pointwise P-norm regularization for image deconvolution
Binbin, Ma1,2; Xiyuan, Hu1; Silong, Peng1
2019-04
Conference NameInternational Conference on Digital Signal Processing
Conference Date2019年4月23日
Conference PlaceJeju Island, Korea
Abstract

We propose a pointwise P-Norm based nonparametric image deconvolution method. In our algorithm, a pointwise p-norm based regular term is used to deal with the different types of regions in a blurry image such as edges, texture and smooth areas. A new hyper-parameter updating method is also adopted to improve the effectiveness and robustness of the proposed algorithm. The experimental results show that the quality of our restored images can outperform the results derived by other algorithms. In addition, our algorithm has a wide adaptation to different blur kernels.

KeywordImage Deblurring Non-parametric Pointwise P-norm Hyper-parameter
MOST Discipline Catalogue工学::计算机科学与技术(可授工学、理学学位)
DOIhttps://doi.org/10.1145/3316551.3316563
Indexed ByEI
Funding ProjectNational Natural Science Foundation of China[61571438]
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23700
Collection模式识别国家重点实验室_图像与视频分析
Affiliation1.中国科学院自动化研究所
2.中国科学院大学
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Binbin, Ma,Xiyuan, Hu,Silong, Peng. An adaptive pointwise P-norm regularization for image deconvolution[C],2019.
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