Infrared and Visible Image Fusion Using Multi-scale Decomposition and Partial Differential Equations

Infrared and visible image fusion is an important task in many applications, such as surveillance, remote sensing, and medical imaging. This paper proposes a novel algorithm for infrared and visible image fusion using partial differential equations (PDEs). Specifically, we use second- and fourth-order PDEs in a multi-scale framework to achieve effective smoothing, edge preservation, and detail enhancement in the fused image. We evaluate the performance of our algorithm on several benchmark datasets and compare it to existing state-of-the-art methods. The results demonstrate that our algorithm achieves high-quality fused images with improved edge and texture details.