Two-scale Image Fusion of Visible and Infrared Images Using Guided Filter

Abstract

Infrared (IR) and visible (VIS) image fusion techniques can get a new image which can represent the scene exactly, entirely and reliably. Combined the advantages of the two-scale decomposition (TSD) with the characteristic of guided filter, a novel IR and VIS image fusion framework is proposed in this paper. Firstly, both IR and VIS images are decomposed with a two-scale average filter to generate the base layers and detail layers. Second, phase congruency (PC) with guided filtering fusion rule is applied to base layer and the larger Sum Modified Laplacian (SML) with guided filtering fusion rule is applied to detail layer. Finally, the resultant image is reconstructed by adding the base and detail layers. The proposed method not only preserves the details of source IR and VIS images but also suppress the artifacts effectively. Experimental results show that the proposed approach can achieve excellent performance in terms of subjective visual effect and objective assessment for infrared and visible image fusion.