Why You Should Forget Luminance Conversion and Do Something Better
Abstract
One of the most frequently applied low-level operations in computer vision is the conversion of an RGB camera image into its luminance representation. This is also one of the most incorrectly applied operations. Even our most trusted softwares, Matlab and OpenCV, do not perform luminance conversion correctly. In this paper, we examine the main factors that make proper RGB to luminance conversion difficult, in particular: 1) incorrect white-balance, 2) incorrect gamma/tone-curve correction, and 3) incorrect equations. Our analysis shows errors up to 50% for various colors are not uncommon. As a result, we argue that for most computer vision problems there is no need to attempt luminance conversion; instead, there are better alternatives depending on the task.
Cite
Text
Nguyen and Brown. "Why You Should Forget Luminance Conversion and Do Something Better." Conference on Computer Vision and Pattern Recognition, 2017. doi:10.1109/CVPR.2017.627Markdown
[Nguyen and Brown. "Why You Should Forget Luminance Conversion and Do Something Better." Conference on Computer Vision and Pattern Recognition, 2017.](https://mlanthology.org/cvpr/2017/nguyen2017cvpr-you/) doi:10.1109/CVPR.2017.627BibTeX
@inproceedings{nguyen2017cvpr-you,
title = {{Why You Should Forget Luminance Conversion and Do Something Better}},
author = {Nguyen, Rang M. H. and Brown, Michael S.},
booktitle = {Conference on Computer Vision and Pattern Recognition},
year = {2017},
doi = {10.1109/CVPR.2017.627},
url = {https://mlanthology.org/cvpr/2017/nguyen2017cvpr-you/}
}