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A SAR Image Despeckling Method Based on Dual Tree Complex Wavelet Transform

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Book cover Advances in Intelligent Computing (ICIC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3644))

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Abstract

Based on the dual tree complex wavelet transform and edge detection, a SAR image despeckling algorithm is proposed. It can be used to remove white Gauss additive noise (WGAN) too. The DT-CWT has the properties of shift invariance and more directions. Edges are effectively extracted based on this complex transform and adjacent scales coefficients multiplication. According to the statistical property of the edge and non edge wavelet coefficients, Laplacian and Gaussian distribution are used to describe them respectively. Bayesian MAP estimator is used to estimate the noiseless wavelet coefficient values. Analysis and experiments illustrate the effectiveness of the proposed algorithm.

Supported by the National Science Foundation of China under Grant No.60133010.

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Author information

Authors and Affiliations

  1. School of Computer Science, Shannxi Normal University, 710062, Xi’an, China

    Xi-li Wang

  2. Institute of Intelligent Information Processing, Xidian University, 710071, Xi’an, China

    Li-cheng Jiao

Authors
  1. Xi-li Wang
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  2. Li-cheng Jiao
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Editor information

Editors and Affiliations

  1. Intelligent Computing Lab, Institute of Intelligent Machines, Chinese Academy of Sciences,, China

    De-Shuang Huang

  2. School of Computer & Information Technology, Beijing Jiaotong University, 100044, Beijing, P.R. China

    Xiao-Ping Zhang

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, P.O. Box, Singapore

    Guang-Bin Huang

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© 2005 Springer-Verlag Berlin Heidelberg

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Wang, Xl., Jiao, Lc. (2005). A SAR Image Despeckling Method Based on Dual Tree Complex Wavelet Transform. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538059_7

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  • DOI: https://doi.org/10.1007/11538059_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28226-6

  • Online ISBN: 978-3-540-31902-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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