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. 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. 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. Experimental results can prove the effectiveness of the proposed method through both the qualitative and quantitative evaluation accordingly.