Shadow-based Light Detection for HDR Environment Maps
Andrew Chalmers, Taehyun James Rhee · 2020
High dynamic range (HDR) environment maps (EMs) are spherical textures containing HDR pixels used for illuminating virtual scenes with high realism. Detecting as few necessary pixels as possible within the EM is important for a variety of tasks, such as real-time rendering and EM database management. To address this, we propose a shadow-based algorithm for detecting the most dominant light sources within an EM. This algorithm takes into account the relative impact of all other light sources within the upper-hemisphere of the texture. This is achieved by decomposing an EM into superpixels, sorting the superpixels from brightest to least, and using ℓ0-norm minimisation to keep only the necessary superpixels that maintains the shadow quality of the EM with respect to the just noticeable difference (JND) principle. We show that our method improves upon prior methods in detecting as few lights as possible while still preserving the shadow-casting properties of EMs.