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Many animals exhibit structural colors, which are often iridescent, meaning that the perceived colors change with illumination conditions and viewing perspectives. Biological iridescence is usually caused by multilayers or other periodic structures in animal tissues, which selectively reflect light of certain wavelengths and often result in a shiny appearance---which almost always comes with spatially varying highlights, thanks to randomness and irregularities in the structures. Previous models for biological iridescence tend to each target one specific structure, and most models only compute large-area averages, overlooking spatial variation in iridescent appearance. In this work, we build appearance models for biological iridescence using bird feathers as our case study, investigating different types of feathers with a variety of structural coloration mechanisms. We propose an approximate wave simulation method that takes advantage of quasi-regular structures while efficiently modeling the effects of natural structural irregularities. We further propose a method to distill our simulation results into distributions of BRDFs, generated using noise functions, that preserve relevant statistical properties of the simulated BRDFs. This allows us to model the spatially varying, glittery appearance commonly seen on feathers. Our BRDFs are practical and efficient, and we present renderings of multiple types of iridescent feathers with comparisons to photographic images. 

Stochastic geometry models have enjoyed immense success in graphics for modeling interactions of light with complex phenomena such as participating media, rough surfaces, fibers, and more. Although each of these models operates on the same principle of replacing intricate geometry by a random process and deriving the average light transport across all instances thereof, they are each tailored to one specific application and are fundamentally distinct. Each type of stochastic geometry present in the scene is firmly encapsulated in its own appearance model, with its own statistics and light transport average, and no cross-talk between different models or deterministic and stochastic geometry is possible. In this paper, we derive a theory of light transport on stochastic implicit surfaces, a geometry model capable of expressing deterministic geometry, microfacet surfaces, participating media, and an exciting new continuum in between containing aggregate appearance, non-classical media, and more. Our model naturally supports spatial correlations, missing from most existing stochastic models. Our theory paves the way for tractable rendering of scenes in which all geometry is described by the same stochastic model, while leaving ample future work for developing efficient sampling and rendering algorithms.