University of Amsterdam, Amsterdam 1098 XG, The Netherlands.
IEEE Trans Image Process. 2011 Sep;20(9):2475-89. doi: 10.1109/TIP.2011.2118224. Epub 2011 Feb 22.
Computational color constancy is a fundamental prerequisite for many computer vision applications. This paper presents a survey of many recent developments and state-of-the-art methods. Several criteria are proposed that are used to assess the approaches. A taxonomy of existing algorithms is proposed and methods are separated in three groups: static methods, gamut-based methods, and learning-based methods. Further, the experimental setup is discussed including an overview of publicly available datasets. Finally, various freely available methods, of which some are considered to be state of the art, are evaluated on two datasets.
计算颜色恒常性是许多计算机视觉应用的基本前提。本文综述了许多最新的发展和最新方法。提出了几个用于评估方法的标准。提出了一种现有的算法分类法，并将方法分为三组：静态方法、色域方法和基于学习的方法。此外，还讨论了实验设置，包括对公共可用数据集的概述。最后，在两个数据集上评估了各种免费提供的方法，其中一些被认为是最先进的方法。
