计算机工程与应用2012，Vol.48Issue(27)：150-154,5.DOI:10.3778/j.issn.1002-8331.2012.27.032
基于非下采样Contourlet变换的医学CT图像去噪
Medical CT image denoising method based on nonsubsampled Contourlet transform
摘要
Abstract
To overcome the Contourlet transform non translation invariance and spectrum aliasing defects, this paper 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.关键词
图像处理/去噪/非下采样Contourlet变换/Context模型Key words
image processing/ denoising/ nonsubsampled Contourlet transform/ Context model分类
信息技术与安全科学引用本文复制引用
王昊,康晓东,刘玲玲,耿佳佳..基于非下采样Contourlet变换的医学CT图像去噪[J].计算机工程与应用,2012,48(27):150-154,5.基金项目
国家自然科学基金(No.60603027) （No.60603027）
天津市应用基础研究计划(No.05YFJMJC11700). （No.05YFJMJC11700）
