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An improved speckle-reduction algorithm for SAR images based on anisotropic diffusion

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Abstract

This paper mainly studies the algorithm of anisotropic diffusion for speckle noise removal of SAR images. Because the Gauss curvature driven diffusion method is sensitive to the noise and is of low efficiency on suppressing the speckle noise, an improved denoising algorithm is proposed. The new algorithm introduces the difference curvature as the diffusion coefficients of the function, which solves the problem that Gauss curvature driven diffusion is sensitive to the speckle noise, further, Tukey’s biweight function is used to control the curvature diffusion model, which can not only better protect edges, but also automatically control the diffusion. Numerical experiments show that the improved algorithm can preserve the information of textures, edges while inhibiting the speckle of SAR images.

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Acknowledgments

This work was supported by the National Natural Science Foundation of People’s Republic of China (Grant No. 91026005). I wish to thank Professor Wang LingYan who has contributed to the paper improvement.

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Authors and Affiliations

  1. School of Aeronautics and Astronautics, University of Electronic Science and technology of China, Sichuan, 611731, China

    Li Gun, Li Cuihua & Zhu Yingpan

  2. Department of Electronic Information and Electrical Engineering, Changsha University, Changsha, 410022, China

    Huang Feijiang

Authors
  1. Li Gun
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  2. Li Cuihua
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  3. Zhu Yingpan
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  4. Huang Feijiang
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Correspondence to Li Gun.

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Gun, L., Cuihua, L., Yingpan, Z. et al. An improved speckle-reduction algorithm for SAR images based on anisotropic diffusion. Multimed Tools Appl 76, 17615–17632 (2017). https://doi.org/10.1007/s11042-015-2810-3

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  • DOI: https://doi.org/10.1007/s11042-015-2810-3

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