期刊文献+

基于非下采样Contourlet变换的医学CT图像去噪 被引量:5

Medical CT image denoising method based on nonsubsampled Contourlet transform
下载PDF
导出
摘要 为克服Contourlet变换的非平移不变性及频谱混叠等缺陷,提出了一种基于非下采样Contourlet变换的医学CT图像去噪方法。对含噪的CT图像进行非下采样Contourlet变换,得到不同尺度及各个方向上的变换系数,利用Context模型将每个尺度每个方向子带分级,不同分级采用相应的阈值去噪。实验表明,该方法适宜于处理含有更多高斯噪声的医学CT图像,与其他方法相比提高了PSNR值,更好地保留了图像细节,改善了医学CT图像的质量。 To overcome the Contourlet transform non translation invariance and spectrum aliasing defects, this pa- per presents a method based on nonsubsampled Contourlet transform for medical CT image denoising method. The noisy CT images are conducted by nonsubsampled Contourlet transform. Transform coefficients are obtained from different scales and different directions. Using Context model, subband of each scale and each direction is graded. Different classification uses the corresponding threshold denoising. Experiments show that this method is suitable to processing the medical CT image which contains more Gaussian noise. Compared with other methods, the PSNR value is improved, the image details are better retained, and CT image quality is improved.
出处 《计算机工程与应用》 CSCD 2012年第27期150-154,共5页 Computer Engineering and Applications
基金 国家自然科学基金(No.60603027) 天津市应用基础研究计划(No.05YFJMJC11700)
关键词 图像处理 去噪 非下采样CONTOURLET变换 Context模型 image processing denoising nonsubsampled Contourlet transform Context model
  • 相关文献

参考文献14

  • 1Donoho D L, Johnstone I M.Adapting to unknown smooth- ness via wavelet shrinkage[J].JASA, 1995,90 : 1200-1223.
  • 2Jing Yinan,Zhang Chunwang, Wang Xueping.An empiri- cal study on performance comparison of Lucerne and relational database[C]//Proceedings of the 2009 Interna- tional Conference on Communication Software and Net- works, 2009 : 336-340.
  • 3Do M N,Vetterli M.Contourlet:a directional multiresolu- tion image representation[C]//Proc IEEE International Con- ference on Image Processing, Rochester, NY, 2002 : 357-360.
  • 4Do M N,Vetterli M.The contourlet transform:an effi- cient directional multiresolution image representation[J]. IEEE Trans on Image Processing,2005,14: 1-16.
  • 5Cunhaa L,Zhou Jiangping,DO M N.The nonsubsampled contourlet transform: theory, design, and applications[J]. IEEE Transactions on Image Processing, 2006, 15 (10): 3089-3101.
  • 6Chang S G,Yu B,Vetterli M.Spatially Adaptive wavelet thresholding with context modeling for image denoising[J]. IEEE Trans on Image Processing, 2000,9(9) : 1522-1531.
  • 7李松年.现代全身CT诊断学[M].北京:中国医药出版社,2007:1167-1168.
  • 8Mallat S G.A theory for multiresolution signal decompo- sition: the wavelet representation[J].lEEE Transaction on Pattern Analysis and Machine Intelligence, 1989, 11 (7): 674-693.
  • 9Westerink P H,Biemond J,Boekee D E.An optimal bit allocation algorithm for sub-band coding[C]//1CASSP, 1988.
  • 10Chang S G, Yu B, Vetterli M.Image denoising via lossy compression and wavelet thresholding[C]//Intemational Conf on Image Processing, 1997.

共引文献87

同被引文献56

引证文献5

二级引证文献10

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部