A novel fusion algorithm for infrared image and visible light image based on non-subsampled contourlet transform

Aiming at the different characteristics of the infrared image and visible light image, the paper proposed a kind of fusion algorithm for the infrared image and visible light image based on non-subsampled contourlet transform. Firstly, the source images are made multiscale and multi-direction decomposition by using non-subsampled contourlet transform (NSCT). Secondly, to decomposed low frequency subband, a decision-making value with regional energy and variance is constructed and used in fusing the coefficients by choosing larger decision-making value. And for the decomposed high frequency subband, different fusion rules are employed for different levels. The fusion rule of selecting large absolute value of pixel is used for the highest level, and the fusion rule of selecting large regional variance based on regional energy matching degree is used to fuse the other levels. Finally, the final fused image is reconstructed by using the non-subsampled contourlet inverse transform. The experimental results have shown that the proposed algorithm can get more detail information and can exhibit better fusion performance. Key words: Fusion algorithm, regional energy matching degree, image fusion, non-subsampled contourlet transform, infrared image, visible light image, shift invariant.