%0 Journal Article
%T Bayesian image denoising using HMT models in complex Daubechies wavelet domain<br>复Daubechies小波域HMT模型Bayesian图像去噪*
%A CHU Biao
%A LI Xin
%A ZHU Gong qin
%A WANG Jin ju
%A <br>褚标
%A 李昕
%A 朱功勤
%A 汪金菊
%J 计算机应用研究
%D 2008
%I 
%X This paper presented a Bayesian image denoising algorithm based on hidden Markov trees models in complex Daubechies wavelet domain.The complex Daubechies wavelet had some good properties such as compact support,orthogonality,symmetry and approximate linear phase.The HMT models in complex Daubechies wavelet domain capture the key features of the joint statistics of the wavelet coefficients of image.The experimental results show the presented image denoising algorithm is effective.
%K complex Daubechies wavelet
%K HMT model
%K linear phase
%K Bayesian denoising<br>复Daubechies小波
%K 隐马尔可夫树模型
%K 线性相位
%K 贝叶斯去噪
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=4C47C87E0D74C49957F25BC0F260F1F0&yid=67289AFF6305E306&vid=C5154311167311FE&iid=E158A972A605785F&sid=17FE7A1C78626A81&eid=E26AA41AE15D3061&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=7