SAR Speckle Denoising Based on Statistic Model Combined with Medication to Significant Wavelet Significant Coefficient

Yu Qiu-ze; Zhu Guang-xi; Liu Jian; Tian Jin-wen; Mao Hai-cen

doi:10.3724/SP.J.1146.2005.00754

Volume 29 Issue 3

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Article Navigation > Journal of Electronics & Information Technology > 2007 > 29(3): 513-516

Yu Qiu-ze, Zhu Guang-xi, Liu Jian, Tian Jin-wen, Mao Hai-cen. SAR Speckle Denoising Based on Statistic Model Combined with Medication to Significant Wavelet Significant Coefficient[J]. Journal of Electronics & Information Technology, 2007, 29(3): 513-516. doi: 10.3724/SP.J.1146.2005.00754

Citation:

Yu Qiu-ze, Zhu Guang-xi, Liu Jian, Tian Jin-wen, Mao Hai-cen. SAR Speckle Denoising Based on Statistic Model Combined with Medication to Significant Wavelet Significant Coefficient[J]. Journal of Electronics & Information Technology, 2007, 29(3): 513-516. doi: 10.3724/SP.J.1146.2005.00754

Citation:

Yu Qiu-ze, Zhu Guang-xi, Liu Jian, Tian Jin-wen, Mao Hai-cen. SAR Speckle Denoising Based on Statistic Model Combined with Medication to Significant Wavelet Significant Coefficient[J]. Journal of Electronics & Information Technology, 2007, 29(3): 513-516. doi: 10.3724/SP.J.1146.2005.00754

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SAR Speckle Denoising Based on Statistic Model Combined with Medication to Significant Wavelet Significant Coefficient

doi: 10.3724/SP.J.1146.2005.00754

Received Date: 2005-06-27
Rev Recd Date: 2006-01-16
Publish Date: 2007-03-19

Abstract

Abstract

This paper proposes a new method based on statistical model of wavelet coefficients combined with modification to them according to significant coefficient rule. In the method, wavelet coefficients of logarithmic image are firstly modeled as mixture density of two Gaussian distributions with zero mean. In order to incorporate the spatial dependencies into the denoising procedure，Hidden Markov Tree (HMT) model is explored and Expectation Maximization (EM) algorithm is proposed to estimate model parameters. Bayes Minimum Mean Square Error (Bayes MMSE)method is used to estimate the wavelet coefficients free of noise. The wavelet coefficients are updated according to a rule whether the coefficient is a significant one or not. 2D inverse DWT and exponential transform are performed on the updated coefficients to get denoised SAR image. Experimental Results using real SAR images demonstrate that the method can not only reduce the speckle but also preserve edges and radiometric scatter points.

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References(1)

References

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