This paper proposes a hyperspectral imaging simulation method based on a ray-tracing algorithm. The algorithm combines calculations based on solar and atmospheric visible light radiation as well as the spectral bidirectional reflection distribution function (BRDF) of the target surface material and can create its own scenarios for simulation calculations on demand. Considering the presence of multiple scattering between the target and background, using the ray-tracing algorithm enables the precise computation of results involving multiple scattering. To validate the accuracy of the algorithm, we compared the simulated results with the theoretical values of the visible light scattering intensity from a Lambertian sphere. The relative error obtained was 0.8%. Subsequently, a complex scene of engineering vehicles and grass was established. The results of different observation angles and different coating materials were calculated and analyzed. In summary, the algorithm presented in this paper has the following advantages. Firstly, it is applicable to geometric models composed of any triangular mesh elements and accurately computes the effects of multiple scattering. Secondly, the algorithm combines the spectral BRDF information of materials and improves the efficiency of multiple scattering calculations using nonuniform sampling. The computed hyperspectral scattering data can be applied to simulate airborne or space-borne remote sensing data.

Sea-surface foam and near-surface bubbles strongly affect the bidirectional reflectance distribution function (BRDF) of the ocean surface under high-sea-state conditions, but direct Monte Carlo radiative transfer is computationally prohibitive for repeated pixel-wise hyperspectral imaging simulations. This paper proposes a fast BRDF surrogate model for sea-surface foam media. A coupled foam–bubble photon-transport framework generates Monte Carlo BRDF and energy partitioning labels, and a physics-constrained surrogate model predicts directional reflectance from foam thickness, wavelength, temperature, salinity, and illumination–viewing geometry. Validation using independent Monte Carlo samples, parameter-response analysis, and computational efficiency tests shows that the model captures the main angular and spectral reflectance trends while substantially reducing computational cost.