| 改进的基于小波双变量模型的图像去噪算法 |
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| 引用本文： | 侯建华,熊承义,田金文,柳健. 改进的基于小波双变量模型的图像去噪算法[J]. 计算机工程与应用, 2006, 42(18): 29-31,75 |
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| 作者姓名： | 侯建华 熊承义 田金文 柳健 |
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| 作者单位： | 1. 华中科技大学图像识别与人工智能研究所,图像信息处理与智能控制教育部重点实验室,武汉,430074;中南民族大学电子信息工程学院,武汉,430074
2. 华中科技大学图像识别与人工智能研究所,图像信息处理与智能控制教育部重点实验室,武汉,430074 |
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| 基金项目： | 国家高技术研究发展计划(863计划) |
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| 摘 要： | 研究图像小波系数间的统计相关性并建立适当的模型,可以显著提高图像处理的质量。在贝叶斯最大后验估计理论框架下,讨论了Sendur提出的双变量模型,用MAP估计方法推导了对应的萎缩函数,分析了基于双变量模型去噪算法的不足,在此基础上进行了改进,利用MAP软阈值对第L级三个高频子带进行局部自适应处理。实验结果表明了改进后算法的有效性。
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| 关 键 词： | 小波系数 MAP估计 双变量模型 萎缩函数 图像去噪 |
| 文章编号： | 1002-8331-（2006）18-0029-03 |
| 收稿时间： | 2005-12-01 |
| 修稿时间： | 2005-12-01 |
An Improved Image Denoising Algorithm Based on Wavelet Bivariate Model |
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| Hou Jianhua,Xiong Chengyi,Tian Jinwen,Liu Jian. An Improved Image Denoising Algorithm Based on Wavelet Bivariate Model[J]. Computer Engineering and Applications, 2006, 42(18): 29-31,75 |
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| Authors: | Hou Jianhua Xiong Chengyi Tian Jinwen Liu Jian |
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| Abstract: | The quality of image processing can be significantly improved by exploiting the correlation among image wavelet coefficients and modeling the statistics for these coefficients.Under the framework of Bayesian MAP estimation theory,the bivafiate model presented by Sendur is investigated,and the corresponding shrinkage function is derived by MAP estimator.The paper pointes out some drawbacks of this bivariate model based on denoising algorithm and proposes an improved method,in which the coefficients of three high frequency sub-bands in the L-th wavelet decomposition level are modified by MAP soft thresholding rule via locally adaptive fashion.The validity of the proposed method is demonstrated by experiment results. |
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| Keywords: | wavelet coefficients MAP estimation bivariate model shrinkage function image denoising |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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