A spectral-preserving resampling for spatial upscaling of hyperspectral imagery

This paper proposes a spectral-preserving hyperspectral image resampling method (Spectral-Preserving Resampling, SpePR) designed to effectively retain the diagnostic spectral features of minerals during spatial upscaling. In this method, the band correlation structure of hyperspectral imagery is utilized as an intrinsic representation of spectral features, and Tikhonov regularized pseudo-inversion is introduced to mitigate spectral distortion induced by resampling. Within the proposed framework, spectral structural information is initially characterized by band correlation matrices. Subsequently, during the spatial resampling stage, the spectral preservation and spatial resampling terms are jointly optimized to ensure coordinated preservation of spectral and spatial information. The performance of the method was validated by analyzing multi-scale hyperspectral imagery data, with flight altitudes ranging from 30m to 150m, acquired using unmanned aerial vehicles. The results indicate that as spatial resolution decreases, mineral spectral features exhibit a corresponding decrease in absorption depth and absorption area, while maintaining stable absorption positions. Compared with seven conventional interpolation algorithms, SpePR reduces errors by 8.2 %–15.7 % in spectral angular mapping (SAM) and by 23.6 %–27.9 % in spectral correlation relative to the best conventional method. The proposed method also demonstrated significant advantages in metrics such as spectral gradient angle (SGA) and spectral correlation, while also more accurately preserving key mineral absorption features. Concurrently, SpePR demonstrated superior spatial information retention compared to conventional methods, as its resulting spatial features more closely approximated the actual observational imagery. The research findings confirm that the SpePR approach effectively preserves diagnostic spectral features of minerals, thereby providing reliable technical support for multi-scale hyperspectral mineral mapping. • A novel spectral-preserving resampling method (SpePR) is proposed. • Uses band correlation structure to preserve subtle spectral features. • Outperforms traditional methods in preserving spectral and spatial fidelity. • Unsupervised model-driven approach requires no external training data.