An Efficient Algorithm to Highlight Details in Infrared and Visible Image Fusion

Abstract

To improve the fusion quality of infrared and visible images and highlight target and scene details, in this paper, a novel infrared and visible image fusion algorithm is proposed. First, a method for combining dynamic range compression and contrast restoration based on a guided filter is adopted to enhance the contrast of visible source images. Second, guided filter-based image multiscale decomposition is used to decompose images into base layers and detail layers. For base layer fusion, a fusion strategy based on the detail and energy measurements of the source image is proposed to determine the pixel value of the fused image base layer such that the energy loss of the fusion can be reduced and the texture detail features are highlighted to obtain more source image details. Finally, recursive separation and weighted histogram equalization methods are applied to optimize the fused image. Experimental results show that the fusion algorithm and fusion strategy proposed in this paper can effectively improve fusion image clarity, while more detailed target and scene information can still be retained.

Fusion of infrared and visible sensor images based on anisotropic diffusion and fast guided filter

“…Gradient filter-based infrared and visible image fusion 13 , multi-scale infrared and visible image fusion based on phase coherence and saliency 14 , methods based on guided filter 2 and anisotropic diffusion 3 , respectively There are a lot more. For example, fusion methods using guided wave methods 6,7,10 and anisotropic methods 8,16,17 , as well as potential low-rank representation fusion methods have also received much attention 11,12 .…”