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Fast boundary artifact reduction algorithm for image deconvolution
Ma Z.1; Liu X.1; Wu E.1
2014
Source PublicationJisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics
ISSN10039775
Volume26Issue:7
AbstractFrequency domain image deconvolution algorithms assume the periodicity of the input signals. But the discontinuities appeared along image boundaries can cause severe ringing artifacts in the restored results. This paper presents a fast and effective boundary artifact reduction method. Inspired by previous expansion based algorithms, this paper firstly simplifies the definition of expansion regions into three types, and then proposes an improved convolution pyramid model with symmetric coefficients. Based on this model, it trains the filter coefficients for each type of region on some special images, before it can be applied to compute expansions for arbitrary images. Experimental results show that the proposed method can avoid solving huge sparse linear systems, and bring an acceleration of two orders of magnitude without sacrificing the accuracy of the deconvolution, while reducing the ringing artifact effectively for all Fourier domain deconvolution methods.
KeywordBoundary artifacts Fourier transform Image deconvolution Image restoration
URLView the original
Language英語English
Fulltext Access
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Institute of Software Chinese Academy of Sciences
2.Universidade de Macau
3.University of Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Ma Z.,Liu X.,Wu E.. Fast boundary artifact reduction algorithm for image deconvolution[J]. Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics, 2014, 26(7).
APA Ma Z.., Liu X.., & Wu E. (2014). Fast boundary artifact reduction algorithm for image deconvolution. Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics, 26(7).
MLA Ma Z.,et al."Fast boundary artifact reduction algorithm for image deconvolution".Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics 26.7(2014).
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