EON: A practical energy-preserving rough diffuse BRDF

TL;DR

The paper presents EON, an energy-preserving rough diffuse BRDF model that improves physical accuracy and efficiency through analytical energy compensation and a novel sampling technique, with practical implementation details.

Contribution

Introduction of the EON model, which ensures energy preservation in rough diffuse reflection and includes a new importance sampling method and implementation code.

Findings

EON maintains energy conservation in rough diffuse BRDFs.

The CLTC sampling technique improves rendering efficiency.

EON outperforms traditional models in physical accuracy.

Abstract

We introduce the "Energy-preserving Oren--Nayar" (EON) model for reflection from rough surfaces. Unlike the popular qualitative Oren--Nayar model (QON) and its variants, our model is energy-preserving via analytical energy compensation. We include self-contained GLSL source code for efficient evaluation of the new model and importance sampling based on a novel technique we term "Clipped Linearly Transformed Cosine" (CLTC) sampling.