Specularity, the Zeta-image, and Information-Theoretic Illuminant Estimation

  • Mark S. Drew
  • Hamid Reza Vaezi Joze
  • Graham D. Finlayson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7584)


Identification of illumination is an important problem in imaging. In this paper we present a new and effective physics-based colour constancy algorithm which makes use of a novel log-relative-chromaticity planar constraint. We call the new feature the Zeta-image. We show that this new feature is tied to a novel application of the Kullback-Leibler Divergence, here applied to chromaticity values instead of probabilities. The new method requires no training data or tunable parameters. Moreover it is simple to implement and very fast. Our experimental results across datasets of real images show the proposed method significantly outperforms other unsupervised methods while its estimation accuracy is comparable with more complex, supervised, methods. As well, the new planar constraint can be used as a post-processing stage for any candidate colour constancy method in order to improve its accuracy.


Angular Error Colour Constancy Planar Constraint Specular Component Specular Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mark S. Drew
    • 1
  • Hamid Reza Vaezi Joze
    • 1
  • Graham D. Finlayson
    • 2
  1. 1.School of Computing ScienceSimon Fraser UniversityCanada
  2. 2.School of Computing SciencesUniversity of East AngliaUK

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