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Colour constancy in natural images through colour naming and sensor sharpening

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dc.contributor.author Vazquez-Corral, Javier
dc.date.accessioned 2016-02-19T09:22:07Z
dc.date.available 2016-02-19T09:22:07Z
dc.date.issued 2014
dc.identifier.citation Vazquez-Corral J. Colour constancy in natural images through colour naming and sensor sharpening. Electronic Letters on Computer Vision and Image Analysis. 2014;13(2). DOI: 10.5565/rev/elcvia.627.
dc.identifier.issn 1577-5097
dc.identifier.uri http://hdl.handle.net/10230/25905
dc.description.abstract Colour is derived from three physical properties: incident light, object reflectance and sensor sensitivities./nIncident light varies under natural conditions; hence, recovering scene illuminant is an important issue in com-/nputational colour. One way to deal with this problem under calibrated conditions is by following three steps, 1)/nbuilding a narrow-band sensor basis to accomplish the diagonal model, 2) building a feasible set of illuminants,/nand 3) defining criteria to select the best illuminant. In this work we focus on colour constancy for natural/nimages by introducing perceptual criteria in the first and third stages./nTo deal with the illuminant selection step, we hypothesize that basic colour categories can be used as anchor/ncategories to recover the best illuminant. These colour names are related to how the human visual system has/nevolved to encode relevant natural colour statistics. Therefore the recovered image provides the best represen-/ntation of the scene labelled with the basic colour terms. We demonstrate with several experiments how this/nselection criterion achieves current state-of-art results in computational colour constancy. In addition to this/nresult, we psychophysically prove that usual angular error used in colour constancy does not correlate with/nhuman preferences, and we propose a new perceptual colour constancy evaluation./nThe implementation of this selection criterion strongly relies on the use of a diagonal model for illuminant/nchange. Then, the second contribution focuses on building an appropriate narrow-band sensor basis to represent/nnatural images. We propose to use the spectral sharpening technique to compute a unique narrow-band basis/noptimized to represent a large set of natural reflectances under natural illuminants and given in the basis of hu-/nman cones. The proposed sensors allow predicting unique hues and the World colour Survey data independently/nof the illuminant by using a compact singularity function. Additionally, we studied different families of sharp/nsensors to minimize different perceptual measures. This study brought us to extend the spherical sampling/nprocedure from 3D to 6D./nSeveral research lines remain still open, such as, measuring the effects of using the computed sharp sen-/nsors on the category hypothesis; or inserting spatial contextual information to improve category hypothesis./nFinally,to explore how individual sensors can be adjusted to the colours in a scene.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Computer Vision Center Press
dc.relation.ispartof Electronic Letters on Computer Vision and Image Analysis. 2014;13(2)
dc.rights This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/
dc.title Colour constancy in natural images through colour naming and sensor sharpening
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.5565/rev/elcvia.627
dc.subject.keyword Colour and texture
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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