A Qualitative and Quantitative Evaluation of 8 Clear Sky Models

TL;DR

This paper evaluates eight clear sky models in computer graphics through qualitative, quantitative, and perceptual analyses, comparing their accuracy and computational complexity against measurements and a physics-based reference model.

Contribution

It provides a comprehensive comparison and assessment of existing sky models, highlighting the impact of physical simplifications on accuracy and suggesting avenues for improvement.

Findings

More physically accurate models yield better results.

Models with fewer simplifications are more precise.

Perceptual study supports quantitative findings.

Abstract

We provide a qualitative and quantitative evaluation of 8 clear sky models used in Computer Graphics. We compare the models with each other as well as with measurements and with a reference model from the physics community. After a short summary of the physics of the problem, we present the measurements and the reference model, and how we "invert" it to get the model parameters. We then give an overview of each CG model, and detail its scope, its algorithmic complexity, and its results using the same parameters as in the reference model. We also compare the models with a perceptual study. Our quantitative results confirm that the less simplifications and approximations are used to solve the physical equations, the more accurate are the results. We conclude with a discussion of the advantages and drawbacks of each model, and how to further improve their accuracy.