A fusion algorithm for infrared and visible images based on saliency analysis and non-subsampled Shearlet transform

• The infrared target is detected based on saliency analysis.
• Super-pixels-based method is used to coarsely locate the infrared target region.
• The multi-directional detect operators are used to refine the contour of the target.
• Non-subsampled Shearlet transform is used to select fusion coefficients of the background.

This paper proposed a novel fusion method for the infrared and visible image based on the accurate extraction of the target region. Firstly, the super-pixels-based saliency analysis method is used to extract the salient regions of the infrared image and obtain the coarse contour of the infrared target. Then the multi-directional detection operators and the adaptive threshold algorithm are used to refine the boundary of the target region and obtain the fusion decision map. In order to capture the details of the visible image, non-subsampled Shearlet transform (NSST) is used to select the fusion coefficients of the background. Experimental results indicate that the proposed method is superior to other state of the-art methods in subjective visual and objective performance.