caa a22 4500 467914400 CHVBK 20180406152858.0 cr unu---uuuuu 170328e20060401xx s 000 0 eng 10.1007/s11263-006-4100-z doi (NATIONALLICENCE)springer-10.1007/s11263-006-4100-z Gamut Constrained Illuminant Estimation [Elektronische Daten] [G. Finlayson, S. Hordley, I. Tastl] This paper presents a novel solution to the illuminant estimation problem: the problem of how, given an image of a scene taken under an unknown illuminant, we can recover an estimate of that light. The work is founded on previous gamut mapping solutions to the problem which solve for a scene illuminant by determining the set of diagonal mappings which take image data captured under an unknown light to a gamut of reference colours taken under a known light. Unfortunately, a diagonal model is not always a valid model of illumination change and so previous approaches sometimes return a null solution. In addition, previous methods are difficult to implement. We address these problems by recasting the problem as one of illuminant classification: we define a priori a set of plausible lights thus ensuring that a scene illuminant estimate will always be found. A plausible light is represented by the gamut of colours observable under it and the illuminant in an image is classified by determining the plausible light whose gamut is most consistent with the image data. We show that this step (the main computational burden of the algorithm) can be performed simply and efficiently by means of a non-negative least-squares optimisation. We report results on a large set of real images which show that it provides excellent illuminant estimation, outperforming previous algorithms. Springer Science + Business Media, Inc., 2006 colour constancy nationallicence illuminant estimation nationallicence gamut mapping nationallicence Finlayson G. School of Computing Sciences, University of East Anglia, UK aut Hordley S. School of Computing Sciences, University of East Anglia, UK aut Tastl I. Hewlett Packard Incorporated, Palo Alto, USA aut International Journal of Computer Vision Kluwer Academic Publishers 67/1(2006-04-01), 93-109 0920-5691 67:1<93 2006 67 11263 https://doi.org/10.1007/s11263-006-4100-z text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11263-006-4100-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Finlayson G. School of Computing Sciences, University of East Anglia, UK aut NATIONALLICENCE 700 1- Hordley S. School of Computing Sciences, University of East Anglia, UK aut NATIONALLICENCE 700 1- Tastl I. Hewlett Packard Incorporated, Palo Alto, USA aut NATIONALLICENCE 773 0- International Journal of Computer Vision Kluwer Academic Publishers 67/1(2006-04-01), 93-109 0920-5691 67:1<93 2006 67 11263 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer