计算机科学 ›› 2013, Vol. 40 ›› Issue (3): 310-313.

• 图形图像与模式识别 • 上一篇    

基于非下采样Contourlet变换的医学图像融合方法

杨艳春,王晓明,党建武,王阳萍   

  1. (兰州交通大学电子与信息工程学院 兰州730070)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Method of Medical Image Fusion Based on Nonsubsampled Contourlet Transform

  • Online:2018-11-16 Published:2018-11-16

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,考虑到相部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。

关键词: 非下采样Contourlet变换,医学图像融合,区域能量,改进拉普拉斯能量和

Abstract: 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 frectuency sub-band,a fusion rule based on local area energy was adopted in low frequency sulrband coefficient according to characteristics of medical image. When choosing the bandpass directional sulrband coefficients, the paper made best use of directional characteristics of NSCT. A fusion rule based on sum-modified-laplacian (SMI)was presented in bandpass directional sulrband coefficients. 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.

Key words: Nonsubsampled contourlet transform(NSC7),Medical image fusion, Local area energy, Sum-modified-laplacian(SMI)

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