An Improved Infrared and Visible Image Fusion Algorithm Based On Curvelet Transform

The fusion of infrared images and visible images can combine complementary information in an image, so we can better describe a scene, and it is helpful for some tasks such as target detection, target localization and environment recognition. In this paper, we use the Second Generation Curvelet Transform (SGCT) to decompose infrared images and grayscale visible images to propose a new image fusion algorithm. This algorithm uses a multi-resolution decomposition of different tools and different fusion rules implementation. The simulation results show that, compared with existing algorithms, this algorithm have improved to some extent in the evaluation of fused images