A Novel Lightweight Infrared and Visible Image Fusion Algorithm

Abstract

Aiming at some usage scenarios that have strict requirements on the scale of fusion operation, this paper proposes a lightweight infrared and visible image fusion algorithm. The algorithm first uses bilateral filtering to decompose the image into the detail layer and the base layer. Secondly, the fusion of detail layers is achieved through regional variance. Then, the LC saliency detection method is performed on the original image to generate a saliency map. A weight map is generated from the saliency map of the original image to guide the base layer to perform fusion. Finally, the fusion image is obtained through linear transformation of the detail layer and the base layer. The proposed algorithm architecture is simplified, and only bilateral filtering is used to realize multi-scale decomposition, which reduces the operation scale. In terms of the fusion quality, after experimental verification, the proposed algorithm has certain advantages in the clarity and edge transition of the fused image compared with the comparison algorithm.