Why You Should Forget Luminance Conversion and Do Something Better

被引:10
作者
Nguyen, Rang M. H. [1 ]
Brown, Michael S. [2 ]
机构
[1] Natl Univ Singapore, Singapore, Singapore
[2] York Univ, N York, ON, Canada
来源
30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) | 2017年
关键词
COLOR; ENHANCEMENT;
D O I
10.1109/CVPR.2017.627
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:5920 / 5928
页数:9
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