Abstract: Based on the properties of NSCT，multi-scale，multi-directional expansion，multi-resolution analysis and shift invariant，with the fusion problem of SAR and color visible images，a multisensor fusion algorithm using NSCT and HIS transform is presented.In the experiment，the ku-band SAR and color visible images under the same scenario are used to validate this algorithm.The selection principles of the low frequency subband coefficients and bandpass directional subband coefficients are discussed respectively.For the low frequency subband coefficients，a“weighted averaging”scheme based on the physical features of SAR images and color visible images is presented；while for the bandpass directional subband coefficients，a selection principle based on the absolute value of selected major is developed.Evaluation of experimental results according to both the subjective and objective criteria，including the entropy，average，correlation coefficient，deviation index and cross entropy，demonstrates that algorithms grounded on the NSCT are more effective.

Key words: image fusion, Nonsubsampled Contourlet Transform（NSCT）, physical feature, HIS transform

摘要： 非下采样Contourlet变换同时具有多尺度、多方向选择性、多分辨分析和平移不变性质的特点，对SAR和彩色可见光图像融合的问题，提出一种基于非下采样Contourlet变换和HIS变换相结合的多传感器融合算法。通过对经非下采样Contourlet变换分解得到的不同频域子带系数选择方案的分析，对低频子带系数的选择，提出了一种基于SAR图像与彩色可见光图像物理特征的“加权平均”的系数选择方案；针对各带通方向子带系数的选择，采用绝对值选大多分辨率融合算法。实验以同一场景下ku波段的SAR图像和彩色可见光图像进行算法验证，实验结果和信息熵、均值、相关系数、偏差指数和交叉熵等客观评价数据表明，方法具有较好的融合效果。

关键词: 图像融合, 非下采样Contourlet变换, 物理特征, HIS变换