第18卷第3期 2010年3月
文章编号
1004-924X(2010)03-0756-08
光学精密工程
Optics and Precision Engineering
双树轮廓波变换域的磁共振图像降噪
金炜，俞建定，符冉迪，杨高波
（宁波大学信息科学与工程学院，浙江宁波315211）
Vol.18No.3 Mar.2010
摘要：为了改善磁共振（MR)图像的质量，提出一种基于双树轮廊波(DT-Contourlet)变换的MR图像降噪算法。研究了 MR图像的噪声分布模型，认为这种噪声服从菜斯分布，从而推导了MR模平方图像的噪声参数估计方法。通过分析 DT-Contourlet的塔型双树方向滤波器组结构，明确了DT-Contourlet不仅能保持轮廊波灵活的方向选择性，而且克服了传统轮廓波不具有平移不变性的缺点。在DT-Contourlet变换域，通过计算方差一致性测度，用局部自适应窗口估计阔值姜缩因子，对MR模平方图像的变换系数进行阔值萎缩。最后，经过DT-Contourlet反变换，实现了MR图像的降噪处理。实验结果表明，用本文算法降噪的MR仿真图像的峰值信噪比（PSNR)优于传统算法；与基于小波和轮廊波的方法相比，不同噪声方差下的PSNR平均提高了2.13dB和0.91dB。从视觉效果来看，该算法能在有效抑制MR图像噪
声的同时，更好地保持图像的细节信息。关键
词：磁共振图像；双树轮廉波变换；噪声参数估计；图像降噪
中图分类号：TP391
文献标识码：A
Magneticresonanceimagedenoisingindual-tree
Contourlet transform domain
JIN Wei, YU Jian-ding,FU Ran-di,YANG Gao-bo
(FacultyofInformationScience&Technology,NingboUniversity,Ningbo31521l,China)
Abstract: In order to improve the quality of Magnetic Resonance (MR) images, a denoising algorithm for a MR image using Dual-Tree Contourlet (DT-Contourlet) transform is proposed. The distribution model of noise of the MR image is investigated, and a method to estimate the noise parameters of the squared magnitude MR image is derived based on the assumption that such noise obeys Rician distribu-tion. Then, the pyramidal dual-tree directional filter bank of DT-Contourlet is analyzed to show that DT-Contourlet maintains the flexibility direction selectivity of the Contourlet transform, and over comes the shortcomes of the Contourlet in lack of shift invariance. After that, the locally adaptive win-dow is used to compute the shrinkage factor to shrink the DT-Contourlet coefficients of the squared magnitude MR image in the DT-Contourlet domain by calculating the Variance Homogeneity Measure-ment (VHM). Finally, the denoising algorithm to MR image is implemented via the inverse DT-Cont+ ourlet transform, Experimental results show that the Peak Signal-Noise Ratio (PSNR) of simulated MR images by proposed algorithm is superior to that by traditional algorithms. With different noise
收稿日期：2009-08-30；修订日期：2009-09-30.
基金项目：渐江省自然科学基全资助项目（No.Y1080778)：国家教育部科学技术研究重点项目(No.209155)；宁波市
自然科学基金资助项目（No.2008A610012)