Wavelet-Based Speckil Filtering Comebining HMT and HMRF for SAR Images

Song  Hang; Wang  Shi-Xi; Yu  Wen-Xian; Su  Yi

doi:10.3724/SP.J.1146.2007.00928

Volume 30 Issue 12

Jan. 2011

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Article Navigation > Journal of Electronics & Information Technology > 2008 > 30(12): 2822-2826

Song Hang, Wang Shi-Xi, Yu Wen-Xian, Su Yi. Wavelet-Based Speckil Filtering Comebining HMT and HMRF for SAR Images[J]. Journal of Electronics & Information Technology, 2008, 30(12): 2822-2826. doi: 10.3724/SP.J.1146.2007.00928

Citation:

Song Hang, Wang Shi-Xi, Yu Wen-Xian, Su Yi. Wavelet-Based Speckil Filtering Comebining HMT and HMRF for SAR Images[J]. Journal of Electronics & Information Technology, 2008, 30(12): 2822-2826. doi: 10.3724/SP.J.1146.2007.00928

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Wavelet-Based Speckil Filtering Comebining HMT and HMRF for SAR Images

doi: 10.3724/SP.J.1146.2007.00928

Received Date: 2007-06-11
Rev Recd Date: 2007-11-25
Publish Date: 2008-12-19

Abstract

Abstract

A novel iterative algorithm to estimate the hidden states of wavelet coefficients of SAR images is proposed by combing the Hidden Markov Tree (HMT) and the Hidden Markov Random Field (HMRF) model. Inter-scale and intra-scale correlation of the coefficients are utilized efficiently in the new approach so the estimation for states is more accurate. With states known the Bayesian estimation is applied to the coefficients to eliminate noises infection. Experiments show that not only the image is despeckled efficiently but also the details are preserved well.
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References(1)

References

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