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International Conference on Intelligent Computing

ICIC 2016: Intelligent Computing Theories and Application pp 409–417Cite as

Feature Extraction with Radon Transform for Block Matching and 3D Filtering

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9772))

Abstract

We propose a novel modification to patch matching in block matching and 3D filtering (BM3D), which is the state-of-the-art in image denoising. The BM3D calculates the distance between two patches by taking the sum of square of the pixel difference. However, when the noise level is very high, this patch matching technique will be less effective. It is well known that Radon transform is very good at suppressing Gaussian white noise and hence in this paper we use it to extract robust features from the two patches for patch matching in BM3D. Experimental results confirm the effectiveness of our proposed modification to BM3D for image denoising in heavily noisy scenarios.

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Acknowledgments

The authors would like to thank the authors of [1, 5, 9] for posting their denoising software on their websites.

Author information

Authors and Affiliations

  1. Department of Mathematics and Statistics, Concordia University, Montreal, QC, H3G 1M8, Canada

    Guang Yi Chen

  2. Department of Mechanical and Industrial Engineering, Concordia University, Montreal, QC, H3G 1M8, Canada

    Wen Fang Xie

Authors
  1. Guang Yi Chen
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  2. Wen Fang Xie
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Corresponding author

Correspondence to Guang Yi Chen .

Editor information

Editors and Affiliations

  1. Tongji University , Shanghai, China

    De-Shuang Huang

  2. University of Ulsan , Ulsan, Korea (Republic of)

    Kang-Hyun Jo

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© 2016 Springer International Publishing Switzerland

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Chen, G.Y., Xie, W.F. (2016). Feature Extraction with Radon Transform for Block Matching and 3D Filtering. In: Huang, DS., Jo, KH. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9772. Springer, Cham. https://doi.org/10.1007/978-3-319-42294-7_36

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  • DOI: https://doi.org/10.1007/978-3-319-42294-7_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42293-0

  • Online ISBN: 978-3-319-42294-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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