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Wavelet-Based Speckil Filtering Comebining HMT and HMRF for SAR Images |
Song Heng Wang Shi-xi Yu Wen-xian Su Yi |
School of Electronic Science and Engineering, NUDT, Changsha 410073, China |
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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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Received: 11 June 2007
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Corresponding Authors:
Song Heng
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