Using High-Level Visual Information for Color Constancy
J. van de Weijer,Cordelia Schmid,Jakob Verbeek +2 more
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TLDR
Experiments show that the use of high-level information improves illuminant estimation over a purely bottom-up approach, and the proposed method is shown to significantly improve semantic class recognition performance.Abstract:
We propose to use high-level visual information to improve illuminant estimation. Several illuminant estimation approaches are applied to compute a set of possible illuminants. For each of them an illuminant color corrected image is evaluated on the likelihood of its semantic content: is the grass green, the road grey, and the sky blue, in correspondence with our prior knowledge of the world. The illuminant resulting in the most likely semantic composition of the image is selected as the illuminant color. To evaluate the likelihood of the semantic content, we apply probabilistic latent semantic analysis. The image is modelled as a mixture of semantic classes, such as sky, grass, road, and building. The class description is based on texture, position and color information. Experiments show that the use of high-level information improves illuminant estimation over a purely bottom-up approach. Furthermore, the proposed method is shown to significantly improve semantic class recognition performance.read more
Citations
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Journal ArticleDOI
Computational Color Constancy: Survey and Experiments
TL;DR: A survey of many recent developments and state-of-the-art methods in computational color constancy, including a taxonomy of existing algorithms, and methods are separated in three groups: static methods, gamut- based methods, and learning-based methods.
Book
Color constancy
TL;DR: This book provides a comprehensive introduction to the field ofcolor constancy, describing all the major color constancy algorithms, as well as presenting cutting edge research in the area of color image processing.
Proceedings ArticleDOI
Bayesian color constancy revisited
TL;DR: This paper introduces a new tool in the form of a database of 568 high-quality, indoor and outdoor images, accurately labelled with illuminant, and preserved in their raw form, free of correction or normalisation, which shows that automatic selection of grey-world algorithms according to image properties is not nearly so effective as has been thought.
Journal ArticleDOI
Color Constancy Using Natural Image Statistics and Scene Semantics
Arjan Gijsenij,Theo Gevers +1 more
TL;DR: Natural image statistics are used to identify the most important characteristics of color images and it is shown that for certain scene categories, one specific color constancy algorithm can be used instead of the classifier considering several algorithms.
Journal ArticleDOI
Generalized Gamut Mapping using Image Derivative Structures for Color Constancy
TL;DR: It is analytically shown that the proposed gamut mapping framework is able to include any linear filter output and it is shown that derivatives have the advantage over pixel values to be invariant to disturbing effects (i.e. deviations of the diagonal model) such as saturated colors and diffuse light.
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