Web of Science: 7 cites, Scopus: 9 cites, Google Scholar: cites
Spectral sharpening by spherical sampling
Finlayson, Graham D. (University of East Anglia)
Vázquez i Corral, Javier (Universitat Autònoma de Barcelona. Departament de Ciències de la Computació)
Süsstrunk, Sabine (École Polytechnique Fédéral de Lausanne)
Vanrell i Martorell, Maria Isabel (Centre de Visió per Computador (Bellaterra, Catalunya))

Data: 2012
Resum: There are many works in color that assume illumination change can be modeled by multiplying sensor responses by individual scaling factors. The early research in this area is sometimes grouped under the heading "von Kries adaptation": the scaling factors are applied to the cone responses. In more recent studies, both in psychophysics and in computational analysis, it has been proposed that scaling factors should be applied to linear combinations of the cones that have narrower support: they should be applied to the so-called "sharp sensors. " In this paper, we generalize the computational approach to spectral sharpening in three important ways. First, we introduce spherical sampling as a tool that allows us to enumerate in a principled way all linear combinations of the cones. This allows us to, second, find the optimal sharp sensors that minimize a variety of error measures including CIE Delta E (previous work on spectral sharpening minimized RMS) and color ratio stability. Lastly, we extend the spherical sampling paradigm to the multispectral case. Here the objective is to model the interaction of light and surface in terms of color signal spectra. Spherical sampling is shown to improve on the state of the art.
Ajuts: Ministerio de Ciencia e Innovación TIN2010-21771-C02-1
Ministerio de Educación y Ciencia CSD2007- 00018
Drets: Tots els drets reservats.
Llengua: Anglès
Document: Article ; recerca ; Versió acceptada per publicar
Publicat a: Journal of the Optical Society of America A: Optics and Image Science, and Vision, Vol. 29, Issue 7 (July 2012) , p. 1199-1210, ISSN 1520-8532

DOI: 10.1364/JOSAA.29.001199


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