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A fast and adaptive method for complex-valued SAR image denoising based on l k norm regularization

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Abstract

This paper developed a fast and adaptive method for SAR complex image denoising based on l k norm regularization, as viewed from parameters estimation. We firstly establish the relationship between denoising model and ill-posed inverse problem via convex half-quadratic regularization, and compare the difference between the estimator variance obtained from the iterative formula and biased Cramer-Rao bound, which proves the theoretic flaw of the existent methods of parameter selection. Then, the analytic expression of the model solution as the function with respect to the regularization parameter is obtained. On this basis, we study the method for selecting the regularization parameter through minimizing mean-square error of estimators and obtain the final analytic expression, which resulted in the direct calculation, high processing speed, and adaptability. Finally, the effect of regularization parameter selection on the resolution of point targets is analyzed. The experiment results of simulation and real complex-valued SAR images illustrate the validity of the proposed method.

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Authors and Affiliations

  1. College of Information System and Management, National University of Defence Technology, Changsha, 410073, China

    WeiWei Wang

  2. College of Science, National University of Defence Technology, Changsha, 410073, China

    ZhengMing Wang, ZhenYu Yuan & MingShan Li

Authors
  1. WeiWei Wang
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  2. ZhengMing Wang
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  3. ZhenYu Yuan
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  4. MingShan Li
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Corresponding author

Correspondence to WeiWei Wang.

Additional information

Supported by the National Natural Science Foundation of China (Grant No. 60572136), the Fundamental Research Fund of NUDT (Grant No. JC0702005)

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Wang, W., Wang, Z., Yuan, Z. et al. A fast and adaptive method for complex-valued SAR image denoising based on l k norm regularization. Sci. China Ser. F-Inf. Sci. 52, 138–148 (2009). https://doi.org/10.1007/s11432-009-0013-0

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  • DOI: https://doi.org/10.1007/s11432-009-0013-0

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