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On the Convex Model of Speckle Reduction

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Imaging, Vision and Learning Based on Optimization and PDEs (IVLOPDE 2016)

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

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Abstract

Speckle reduction is an important issue in image processing realm. In this paper, we propose a novel model for restoring degraded images with multiplicative noise which follows a Nakagami distribution. A general penalty term based on the statistical property of the speckle noise is used to guarantee the convexity of the denoising model. Moreover, to deal with the minimizing problem, a generalized Bermudez-Moreno algorithm is adopted and its convergence is analysed. The experimental results on some images subject to multiplicative noise as well as comparisons to other state-of-the-art methods are also presented. The results can verify that the new model is reasonable.

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Acknowledgements

The authors would like to sincerely thank the reviewers for their valuable and constructive comments. This work is sponsored by “Chenguang Program” supported by Shanghai Education Development Foundation and Shanghai Municipal Education Commission, the key project of the National Natural Science Foundation of China (No. 61731009), the National Science Foundation of China (11271049, 61501188), RGC 12302714, and the Direct Grant for Research of the Chinese University of Hong Kong.

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Authors and Affiliations

  1. Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China

    Faming Fang

  2. Department of Computer Science & Technology, East China Normal University, Shanghai, China

    Faming Fang

  3. Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Yingying Fang

  4. Department of Mathematics, The Chinese University of Hong Kong, Ma Liu Shui, Hong Kong

    Tieyong Zeng

Authors
  1. Faming Fang
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  2. Yingying Fang
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  3. Tieyong Zeng
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Corresponding author

Correspondence to Tieyong Zeng .

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Editors and Affiliations

  1. Department of Mathematics, University of Bergen, Bergen, Norway

    Xue-Cheng Tai

  2. Norwegian Defence Research Establishment, Kjeller, Norway

    Egil Bae

  3. University of South-Eastern Norway, Porsgrunn, Norway

    Marius Lysaker

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Fang, F., Fang, Y., Zeng, T. (2018). On the Convex Model of Speckle Reduction. In: Tai, XC., Bae, E., Lysaker, M. (eds) Imaging, Vision and Learning Based on Optimization and PDEs. IVLOPDE 2016. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-91274-5_6

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