Infrared and visible image fusion based on FDST and dual-channel PCNN

To enhance fusion effects of infrared and visible images in detail preservation and information redundancy, a novel fusion method based on Finite Discrete Shearlet Transform (FDST) and dual-channel Pulse Coupled Neuron Network (PCNN) was proposed. Firstly, the original images were decomposed into low-frequency and high-frequency subband images by FDST; Secondly, low-frequency and high-frequency subband images were fused by modified-spatial-frequency motivated dual-channel PCNN with different linking strengths; Finally, the final fused image was reconstructed from fused subband images by inverse FDST. Experimental results indicate that the proposed fusion method can improve the overall visual performance and the image quality. Compared with other fusion methods, the proposed fusion method gets significant improvement in objective evaluation criteria of mutual information, edge information preservation and standard deviation.