Research on Varitional Pan-Sharpening Model with Adaptive Regex Coefficients

Pansharpening enhances the resolution of multispectral images by fusing them with higher-resolution panchromatic images, improving spatial resolution while retaining spectral information. This technique is valuable for visual interpretation and advanced processing. Recent advancements focus on enhancing spatial resolution through variational optimization, which transforms image fusion into an extremum problem. This paper introduces non-negative adaptive mixing coefficients to the pansharpening variational model by Fang et al., aiming to better align gradient curves of panchromatic and multispectral images, enhancing spatial information extraction while maintaining spectral quality. The proposed model’s efficacy is verified through numerical experiments on Quickbird and GaoFen images, demonstrating superior spatial quality compared to traditional methods.