%0 Journal Article
%T Sparsity regularized image Laplace denosing based on Peaceman Rachford operator splitting algorithm<br>稀疏性正则化的图像Laplace去噪及PR算子分裂算法*
%A LV Zhan-qiang
%A SUN Yu-bao
%A <br>吕占强
%A 孙玉宝
%J 计算机应用研究
%D 2011
%I 
%X Adopting Bayesian-MAP estimation framework,this paper proposed a sparsity regularized non-smooth convex functional model to denosie Laplace noisy image.The L1 norm was used for data fidelity term and non-smooth regularization term constrains the sparse representation of the underlying image over the overcomplete dictionary.Inspired form the Peaceman-Rachford operator splitting method,proposed a multi-step fast iterative algorithm to solve the non-smooth model above numerically.By introducing the proximal op...
%K sparse representation
%K image denoising
%K Laplace noise
%K Peaceman-Rachford operator splitting<br>稀疏表示
%K 图像去噪
%K 拉普拉斯噪声
%K PR算子分裂算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=49438F68A18A4524EEB8ED2A69E53746&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=9CF7A0430CBB2DFD&sid=BC313C827ECD4E48&eid=AC3EDB9EE9017BD9&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=9