| 引用本文: | 闫河,何光敏,张小川.复小波包变换域混合统计模型图像降噪算法[J].控制理论与应用,2010,27(3):335~343.[点击复制] |
| YAN He,HE Guang-min,ZHANG Xiao-chuan.Image denoising algorithm using mixed statistical model in complex wavelet packet transform[J].Control Theory and Technology,2010,27(3):335~343.[点击复制] |
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| 复小波包变换域混合统计模型图像降噪算法 |
| Image denoising algorithm using mixed statistical model in complex wavelet packet transform |
| 摘要点击 1784 全文点击 1123 投稿时间：2008-12-04 修订日期：2009-11-05 |
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| DOI编号 |
| 2010,27(3):335-343 |
| 中文关键词 图像去噪 四树复小波包变换 层间相关性 非高斯双变量模型 零均值高斯分布模型 |
| 英文关键词 image denoising quad-tree complex wavelet packet transform inter-scale correlation non-Gaussian bivariate mode zero mean Gaussian distributing model |
| 基金项目 国家自然科学基金资助项目(60443004); 重庆市科委自然科学基金资助项目(CSTC,2008BB2340); 重庆市教委科学技术研究项目(KJ080621); 重庆理工大学科研启动基金项目(2009ZD12). |
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| 中文摘要 |
| 该方法利用四树复小波包变换具有的移不变性、良好的方向选择性和对高频信号的细致分析能力等特点, 把含噪图像分解成低频逼近子图和若干高频方向子图; 在保留低频逼近子图复系数不变的同时, 利用复系数层间相关性的强弱把高频方向子图分为主要类和次要类. 对主要类和次要类复系数分别进一步采用非高斯双变量模型和零均值高斯分布模型进行噪声抑制. 实验结果表明, 无论是峰值信噪比(PSNR)指标, 还是在视觉效果上, 本文方
法的去噪性能均好于传统的双树复小波变换去噪、四树复小波包变换去噪和小波域高斯尺度混合模型去噪, 在有效抑制噪声的同时, 具有很好的图像边缘和细节保护能力. |
| 英文摘要 |
| The noisy image is decomposed into low frequency approximate subimages and high frequency directional subimages by using the quad-tree complex wavelet packet transform(QCWPT) which has the advantages of shift-invariance, high directional resolution and fine discrimination of high frequency signals. The complex coefficients in low frequency approximate subimages are kept unchanged, while the high frequency directional subimages are categorized as major type and minor type according to their inter-scale correlation. Noises in both types are removed by using of the non-Gaussian bivariate model and the zero mean Gaussian distributing model, respectively. In comparing either the power signal-tonoise ratio(PSNR) index or the visual effects with other methods, the presented scheme outperforms the traditional dualtree complex wavelet transform, QCWPT and wavelet domain Gaussian scale mixtures. Experiments also show that the presented scheme achieves an excellent balance between the suppression of noises and the preservation of image details and edge. |
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