Fast rendering for radiometrically correct clouds

Reproducing realistic cloud clutter in simulated imagery is a useful tool for analyzing both sensor and algorithm performance. Additionally, as machine learning becomes more prevalent, realistic cloud imagery will be important in training algorithms to reject them as clutter. We briefly describe the theory of multiple scattering and then discuss the volumetric Monte Carlo method for physically-accurate rendering of clouds. We then describe a simple method that allows radiance data to be precomputed under certain assumptions. The resulting dataset can be leveraged to accelerate rendering from any view point. We conclude with a few results.