Infrared and visible image fusion with the use of multi-scale edge-preserving decomposition and guided image filter

Abstract

Infrared (IR) and visible (VIS) image fusion techniques enhance visual perception capability by integrating IR and VIS images into a single fused image under various environments. This process serves an important function in image processing applications. In this paper, a novel IR and VIS image fusion framework is proposed by combining multi-scale decomposition and guided filter. The proposed scheme could not only preserve the details of source IR and VI images but could also suppress the artifacts effectively by combining the advantages of multi-scale decomposition and guided filter. First, both IR and VIS images are decomposed with a multi-scale edge-preserving filter. Saliency maps of IR and VIS images are then calculated on the basis of phase congruency. Subsequently, the guided filtering is adopted to generate weighting maps. Finally, the resultant image is reconstructed with the weighting maps. Experiments show that the proposed approach can achieve better performance than other methods in terms of subjective visual effect and objective assessment.