目的 针对传统的单特征融合方法不足以衡量像素清晰度的问题，同时综合考虑非下采样Contourlet变换（NSCT）系数特点及人眼视觉感知特性，提出一种基于NSCT的多聚焦图像融合方法。方法 首先对来自同一场景待融合的源图像进行NSCT变换；然后对低频分量采用基于局部可见度、局部视觉特征对比度和局部纹理特征的综合特征信息进行融合；对高频分量采用基于邻域和兄弟信息归一化的关联权重局部视觉特征对比度进行融合；最后进行逆NSCT变换得到融合图像。结果 将本文方法与传统离散小波变换（DWT）、移不变小波变换（SIDWT）、CT（Contoural变换）、NSCT及基于邻域和兄弟信息的NSCT域多聚焦图像融合方法进行了实验对比，本文方法能获得更好的视觉效果以及较大的边缘信息保留值和互信息值。结论 定性和定量的实验结果表明了本文方法的有效性。

Objective To overcome the shortcoming of the traditional fusion methods that use single features to measure the pixel sharpness and consider the non-subsampled contourlet transform (NSCT) coefficients and the human visual perception characteristics, a novel NSCT-based multifocus image fusion method is presented.Method The method consists of three steps.In the first step, the source images that came from the same scene to be fused are performed by NSCT.In the second step, the lowpass subband coefficients are fused by a new combination of local visibility, local visual contrast and local texture features, while the bandpass sub-band coefficients are fused by a normalized and correlation weighted local visual feature contrast that utilizes the information of neighborhood and cousin coefficients.In the third step, the fused image is reconstructed based on the inverse NSCT.Result Compared with series of fusion methods, including discrete wavelet transform (DWT), shift invariant DWT (SIDWT), CT, NSCT, the method fused by the information of neighborhood and cousin coefficients, and the proposed method can get better visual effect and higher values of edge information retention and mutual information.Conclusion Experimental results can prove the effectiveness of the proposed method through both the qualitative and quantitative evaluation accordingly.