Infrared and Visible Image Fusion Enhancement Technology Based on Multi-Scale Directional Analysis

The paper provides an Infrared and visible image fusion algorithm based on the non-subsampled contourlet transform (NSCT). Getting the mean of the low frequency coefficients, choosing the maximum value of the highest level's coefficients from the high frequency coefficients, applying the local variance maximum principle to other resolution level's coefficients, thereby the fusion coefficients of the fused image can be acquired. The experiment indicates that the fusion algorithm can extract the original image features better. The fused image's representation capacity in spatial detail information is also improved, via combing the advantages of the multi-resolution, multi-direction, and translation invariance of the NSCT. Compared with the traditional fusion algorithms, the fusion algorithm presented in this paper provides better subjective visual effect, and the standard deviation and entropy value would be somewhat increased.