| 基于平稳小波变换的邻域依赖自适应软阈值图像降噪 |
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| 作者单位： | 青岛大学信息工程学院 山东青岛266071(矫媛，赵志刚)，北京邮电大学计算机科学与技术学院 中国北京100876(黄斌文) |
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| 摘 要： | 传统正交小波变换降噪方法会引起图像边缘失真,针对其不足,研究了平稳小波变换图像降噪。平稳小波变换去除了下抽样处理,包含在小波系数中的信息是冗余的,同时结合贝叶斯估计的自适应软阈值,提出了一种新的图像降噪算法。通过仿真实验将该方法与Winner2,VisuShrink,BayesShrink方法进行比较,试验结果表明,该方法不仅有效地去除了噪声,而且提高了图像的峰值信噪比。
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| 关 键 词： | 平稳小波变换 图像降噪 自适应阈值 邻域依赖 |
Adaptive Soft Threshold Image De-noising Based on Stationary Wavelet Transform and Neighbor Dependency |
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| Jiao Yuan Zhao Zhigang Huang Binwen. Adaptive Soft Threshold Image De-noising Based on Stationary Wavelet Transform and Neighbor Dependency[J]. Science, 2007, 0(28) |
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| Authors: | Jiao Yuan Zhao Zhigang Huang Binwen |
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| Affiliation: | Jiao Yuan1 Zhao Zhigang1 Huang Binwen2 |
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| Abstract: | Traditional orthogonal wavelet transform de-noising methods can bring visual artifacts.Aiming at its disadvantage,stationary wavelet transform image de-noising is researched.Stationary wavelet transform is non-decimated and the information contained in wavelet coefficients is redundant.Also,a new image de-noising algorithm is proposed by combining Bayesian adaptive soft threshold.Comparing this method with Winner2 method,VisuShrink method and BayesShrink method,experiment results show that this method can effectively eliminate image noise and the Peak Signal to Noise Ratio is improved. |
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| Keywords: | stationary wavelet transform image de-noising adaptive threshold neighbor dependency |
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