A Curious Problem with Using the Colour Checker Dataset for Illuminant Estimation

Graham Finlayson, Ghalia Hemrit, Arjan Gijsenij, Peter Gehler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)
58 Downloads (Pure)


In illuminant estimation, we attempt to estimate the RGB of the light. We then use this estimate on an image to correct for the light's colour bias. Illuminant estimation is an essential component of all camera reproduction pipelines. How well an illuminant estimation algorithm works is determined by how well it predicts the ground truth illuminant colour. Typically, the ground truth is the RGB of a white surface placed in a scene. Over a large set of images an estimation error is calculated and different algorithms are then ranked according to their average estimation performance. Perhaps the most widely used publically available dataset used in illuminant estimation is Gehler's Colour Checker set that was reprocessed by Shi and Funt. This image set comprises 568 images of typical everyday scenes.

Curiously, we have found three different ground truths for the Shi-Funt Colour Checker image set. In this paper, we investigate whether adopting one ground truth over another results in different rankings of illuminant estimation algorithms. We find that, depending on the ground truth used, the ranking of different algorithms can change, and sometimes dramatically. Indeed, it is entirely possible that much of the recent 'advances' made in illuminant estimation were achieved because authors have switched to using a ground truth where better estimation performance is possible.
Original languageEnglish
Title of host publication25th Color and Imaging Conference Final Program and Proceedings
PublisherSociety for Imaging Science and Technology
Number of pages6
Publication statusPublished - 1 Sep 2017
EventColor and Imaging Conference - , Norway
Duration: 11 Sep 201715 Sep 2017


ConferenceColor and Imaging Conference


  • Illuminant estimation
  • colour constancy

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