Infrared and visible image fusion method based on saliency detection and target-enhancement

To resolve the issue of blurred backgrounds and fuzzy targets in using the infrared and visible image fusion algorithm, this paper proposes a new method for image fusion based on target-enhancement. First, average filtering is used to obtain rough estimation of the transmission rate, which is refined by calculating the images’ statistical information. Further, a final target-enhanced infrared image is obtained using the atmospheric scattering model. Then, the edge of the target-enhanced infrared image and the visible image is detected and separated using the improved edge detection. The fusion rule based on binary information is used for the edge part, and the fusion rule based on the ratio weighting analysis is used for the non-edge part. Experimental results show that the image fusion algorithm based on target-enhancement not only highlights the target information of an infrared image, but also retains the detailed information of the visible image as much as possible. Additionally, the fused image has better visual effects and higher objective quality evaluation indexes.