Sequence infrared image fusion algorithm using region segmentation

Aimed at the drawback of traditional fusion methods based on pixel and window strategy, which have not the ability to express the characters of fused image efficiently, a fusion algorithm of sequence infrared image using region segmentation was proposed. Firstly, the sequence images were divided into target area, background area and gray area. Then these different areas were mapped into the visible images. According to the characters of the different areas, the different rules were designed in non-subsampled Contourlet transform (NSCT) domain. The NSCT could provide a flexible multiresolution, local and directional image expansion, and a sparse representation for 2-D piecewise smooth signals, and then different fusion rules were applied to fuse the NSCT coefficients for given regions and optimize the quality of the fused image. Experimental results were compared both in subjective and objective standards. It is showed that the fusion algorithm not only keeps the background information of fusion image completely and richly, but also extracts the target characters of image accurately and effectively. The proposed algorithm is superior to conventional fusion methods, and is feasible and effective.