Dif-Fusion: Towards High Color Fidelity in Infrared and Visible Image Fusion with Diffusion Models

Understand

Color plays an important role in human visual perception, reflecting the spectrum of objects.

• However, the existing infrared and visible image fusion methods rarely explore how to handle multi-spectral/channel data directly and achieve high color fidelity.
• This paper addresses the above issue by proposing a novel method with diffusion models, termed as Dif-Fusion, to generate the distribution of the multi-channel input data, which increases the ability of multi-source information aggregation and the fidelity of colors.
• In specific, instead of converting multi-channel images into single-channel data in existing fusion methods, we create the multi-channel data distribution with a denoising network in a latent space with forward and reverse diffusion process.