摘要
针对传统多尺度变换的医学图像融合问题,提出一种基于非下采样Contourlet变换的医学图像融合新方法。在低频子带系数的选取上,根据医学图像的特点,考虑到相邻低频子带系数之间存在的相关性,采用基于区域能量的融合规则;在选择带通方向子带系数时,充分利用非下采样Contourlet变换的方向特性,采用改进拉普拉斯能量和作为带通方向子带系数的融合规则。实验结果表明,与传统融合方法相比,该方法避免了图像失真,达到了良好的图像融合效果。
This paper proposed a novel method of medical image fusion based on nonsubsampled contourlet transform （NSCT） against the existing problems of medical image fusion by traditional multi-scale transform. Considering regional relativity of the adjacent low frequency sub-band, a fusion rule based on local area energy was adopted in low frequency sub-band coefficient according to characteristics of medical image. When choosing the bandpass directional sub-band co- efficients, the paper made best use of directional characteristics of NSCT. A fusion rule based on sum-modified-laplacian （SML） was presented in bandpass directional sub-band cosfficients. The experiment results show that the proposed method can avoid image distortion and achieve a good effect of image fusion compared with traditional fusion methods.
出处
《计算机科学》
CSCD
北大核心
2013年第3期310-312,F0003,共4页
Computer Science
基金
国家自然科学基金(60962004
61162016)资助
