An Approximate Mie Scattering Function for Fog and Cloud Rendering
The Mie phase function describes the complex shapes that arise when light is scattered by water droplets. Inconvenient tables of data are required to include Mie scattering in a path tracer. To avoid this complexity, analytic models such as Cornette-Shanks (CS) or Henyey-Greenstein (HG) mixtures are often used instead, resulting in a lack of accuracy for fog, clouds, skies and tissue. We show that a blend of HG and Draine's phase function can accurately match 95% of the Mie phase function over a wide range of droplet sizes. We provide a practical parameter fit for this mapping and derive analytic CDF inversion of the Draine (and CS) phase function, to produce a parametric approximation with fully analytic evaluation and sampling. In this talk we describe our fitting procedure, sampling derivations, and compare the proposed model to several others.
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