Research on spectral curve inversion algorithm based on multi-angle BRDF

To address the issue of low matching accuracy between the prior spectral library obtained through vertical nadir acquisition and the measured spectra acquired through tilted acquisition, a spectral curve inversion algorithm based on a kernel-driven BRDF model is proposed in this paper. This algorithm is capable of inverting spectral curves at specified angles, thereby enhancing the matching accuracy with spectra obtained through tilted acquisition. Through a field multi-angle spectral measurement system, we collected multi-angle spectral information of common features used in military target recognition, such as dry grasslands and desert camouflage nets. Subsequently, spectral feature analysis was conducted, and the performance of various inversion algorithms was compared. The results indicate: (1) The reflectance of both types of features changes individually in a similar trend with variations in detection angles. (2) Curve inversion algorithms demonstrate favorable results for tilted curves, with coefficients of determination above 0.83 between inverted and measured spectra at tilted angles. (3) According to Spectral Angle Mapping (SAM), the inversion algorithm reduces spectral angles between inverted spectra and measured spectra at tilted angles, thereby enhancing spectral matching accuracy. This study enriches the relevant field of multi-angle remote sensing and holds theoretical and practical significance for high-spectral target matching detection.