NDLI: Edge-Based Color Constancy

Content Provider	IEEE Xplore Digital Library
Author	van de Weijer, J. Gevers, T. Gijsenij, A.
Copyright Year	1992
Abstract	Color constancy is the ability to measure colors of objects independent of the color of the light source. A well-known color constancy method is based on the gray-world assumption which assumes that the average reflectance of surfaces in the world is achromatic. In this paper, we propose a new hypothesis for color constancy namely the gray-edge hypothesis, which assumes that the average edge difference in a scene is achromatic. Based on this hypothesis, we propose an algorithm for color constancy. Contrary to existing color constancy algorithms, which are computed from the zero-order structure of images, our method is based on the derivative structure of images. Furthermore, we propose a framework which unifies a variety of known (gray-world, max-RGB, Minkowski norm) and the newly proposed gray-edge and higher order gray-edge algorithms. The quality of the various instantiations of the framework is tested and compared to the state-of-the-art color constancy methods on two large data sets of images recording objects under a large number of different light sources. The experiments show that the proposed color constancy algorithms obtain comparable results as the state-of-the-art color constancy methods with the merit of being computationally more efficient.
Sponsorship	IEEE Signal Processing Society
Page Count	8
File Size	969710
Starting Page	2207
Ending Page	2214
File Format	PDF
ISSN	10577149
Volume Number	16
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Light sources Object recognition Image retrieval Color Reflectivity Layout Testing Photometry Computer vision Application software photometric invariance Color constancy object recognition
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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