CBFM: Contrast Balance Infrared and Visible Image Fusion Based on Contrast-Preserving Guided Filter

Infrared (IR) and visible image fusion is an important data processing technique that can accurately comprehensively integrate the thermal radiation texture details of source images. However, existing methods neglect high-contrast problem, leading to suboptimal performance when target information in IR images replaced by To address this limitation, we propose a contrast-balanced framework for fusion. Specifically, novel contrast balance strategy proposed process reduce energy while allowing detailed compensation overexposed areas. Moreover, contrast-preserving guided filter decompose into energy-detail layers high information. effectively extract active detail layer brightness layer, new weighted energy-of-Laplacian operator Gaussian distribution entropy scheme fuse layers, respectively. The fused result was obtained adding layers. Extensive experimental results demonstrate method highlighted simultaneously preserving details. In addition, exhibited superior compared state-of-the-art both qualitative quantitative assessments.