Spatio-Spectral Pattern Illumination for Direct and Indirect Separation from a Single Hyperspectral Image

Hyperspectral imaging has proven effective for appearance inspection because it can identify material compositions and reveal hidden features. Similarly, direct/indirect separation provides essential information about surface appearance and internal conditions, including layer structures and scattering behaviors. This paper presents a novel illumination system incorporating dispersive optics to unify both advantages for scene analyses. In general, achieving distinct direct/indirect separation requires multiple images with varying patterns. In a hyperspectral scenario, using a hyperspectral camera or tunable filters extends exposure and measurement times, hindering practical application.Our proposed system enables the illumination of a wavelength-dependent, spatially shifted pattern. With proper consideration of reflectance differences, we demonstrate robust separation of direct and indirect components for each wavelength can be achieved using a single hyperspectral image taken under one illumination pattern. Furthermore, we demonstrate analyzing the observed differences across wavelengths contributes to estimating depth.