| 采用双树复小波和混合概率模型的光学相干层析图像去噪 |
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| 引用本文： | 舒鹏,孙延奎,田小林.采用双树复小波和混合概率模型的光学相干层析图像去噪[J].应用科学学报,2011,29(5):467-472. |
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| 作者姓名： | 舒鹏 孙延奎 田小林 |
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| 作者单位： | 1. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
2. Faculty of Information Technology, Macau University of Science and Technology, Macao SAR 999078, China |
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| 基金项目： | 国家自然科学基金(No.60971006); 国家“863”高技术研究发展计划基金(No.2010AA122202); 澳门特别行政区科学技术发展基金(No.063/2010/A)资助 |
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| 摘 要： | 为了去除光学相干层析图像中的斑点噪声，提出了基于双树复小波变换的混合概率模型ProbShrink算法. 针对原始光学相干层析图像中信号和噪声的分布特点，在微观层面引入了混合概率模型：将OCT图像取对数后进行双树复小波变换，对于层状边缘中与边缘点“方向一致”的小波系数，采用广义高斯模型描述；对于其他小波系数，则采用高斯模型进行描述. 而后采用改进的ProbShrink算法进行去噪. 实验结果表明，该算法在大幅提升信噪比的情况下保持边缘锐度的相对稳定，优于传统的基于小波变换的去噪方法.
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| 关 键 词： | 光学相干层析 图像去噪 双树复小波变换 混合概率模型 ProbShrink算法 |
| 收稿时间： | 2010-09-06 |
| 修稿时间： | 2011-07-08 |
Denoising of Optical Coherence Tomography Image Using Dual-Tree Complex Wavelet Transform and Mixed Probability Model |
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| SHU Peng,SUN Yan-kui,TIAN Xiao-lin.Denoising of Optical Coherence Tomography Image Using Dual-Tree Complex Wavelet Transform and Mixed Probability Model[J].Journal of Applied Sciences,2011,29(5):467-472. |
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| Authors: | SHU Peng SUN Yan-kui TIAN Xiao-lin |
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| Institution: | 1. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;
2. Faculty of Information Technology, Macau University of Science and Technology, Macao SAR 999078, China |
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| Abstract: | To remove speckle noise in optical coherence tomography(OCT) images,the ProbShrink algorithm based on the dual-tree complex wavelet transform and a mixed probability model is employed.After studying the signal and noise distribution in OCT images,a mixed probability model in microscopic-level is introduced. Logarithm of the OCT image is first decomposed using dual-tree complex wavelet transform.The coefficients consistent with edges obey the generalized Gaussian distribution,while others obey the Gaussian d... |
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| Keywords: | optical coherence tomography image denoising dual-tree complex wavelet transform mixed probability model ProbShrink algorithm |
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