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Publication Detail
Advances in daylight statistical colour modelling
  • Publication Type:
  • Authors:
    Alexander DC
  • Publisher:
    IEEE Computer Society Press
  • Publication date:
  • Place of publication:
    Los Alamitos, US
  • Pagination:
    313, 318
  • Published proceedings:
    Proceedings: 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition: June 23-25, 1999: Fort Collins, Colorado
  • Volume:
  • ISBN-10:
  • Status:
  • Language:
In this paper, parametric statistical modelling of distributions of colour camera data is discussed. A review is provided with some analysis of the properties of some common models, which are generally based on an assumption of independence of the chromaticity and intensity components of colour data. Results of an empirical comparison of the performance of various models are also reviewed. These results indicate that such models are not appropriate for situations other than highly controlled environments. In particular, they perform poorly for daylight imagery. Here, a modification to existing statistical colour models is proposed and the resultant new models are assessed using the same methodology as for the previous results. This simple modification, which is based on the inclusion of an ambient term in the underlying physical model, is shown to have a major impact on the performance of the models in less constrained daylight environments.
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