Literature DB >> 16147525

Sensory, computational and cognitive components of human colour constancy.

H E Smithson1.   

Abstract

When the illumination on a scene changes, so do the visual signals elicited by that scene. In spite of these changes, the objects within a scene tend to remain constant in their apparent colour. We start this review by discussing the psychophysical procedures that have been used to quantify colour constancy. The transformation imposed on the visual signals by a change in illumination dictates what the visual system must 'undo' to achieve constancy. The problem is mathematically underdetermined, and can be solved only by exploiting regularities of the visual world. The last decade has seen a substantial increase in our knowledge of such regularities as technical advances have made it possible to make empirical measurements of large numbers of environmental scenes and illuminants. This review provides a taxonomy of models of human colour constancy based first on the assumptions they make about how the inverse transformation might be simplified, and second, on how the parameters of the inverse transformation might be set by elements of a complex scene. Candidate algorithms for human colour constancy are represented graphically and pictorially, and the availability and utility of an accurate estimate of the illuminant is discussed. Throughout this review, we consider both the information that is, in principle, available and empirical assessments of what information the visual system actually uses. In the final section we discuss where in our visual systems these computations might be implemented.

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Year:  2005        PMID: 16147525      PMCID: PMC1609194          DOI: 10.1098/rstb.2005.1633

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  92 in total

1.  Invariant cone-excitation ratios may predict transparency.

Authors:  S Westland; C Ripamonti
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2000-02       Impact factor: 2.129

2.  Perception of three-dimensional shape influences colour perception through mutual illumination.

Authors:  M G Bloj; D Kersten; A C Hurlbert
Journal:  Nature       Date:  1999 Dec 23-30       Impact factor: 49.962

3.  Spectral properties of V4 neurons in the macaque.

Authors:  S J Schein; R Desimone
Journal:  J Neurosci       Date:  1990-10       Impact factor: 6.167

4.  Adaptation-level as frame of reference for prediction of psychophysical data.

Authors:  H HELSON
Journal:  Am J Psychol       Date:  1947-01

Review 5.  Bayesian color constancy.

Authors:  D H Brainard; W T Freeman
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  1997-07       Impact factor: 2.129

6.  Four issues concerning colour constancy and relational colour constancy.

Authors:  D H Foster; S M Nascimento; B J Craven; K J Linnell; F W Cornelissen; E Brenner
Journal:  Vision Res       Date:  1997-05       Impact factor: 1.886

7.  Method for computing the scene-illuminant chromaticity from specular highlights.

Authors:  H C Lee
Journal:  J Opt Soc Am A       Date:  1986-10       Impact factor: 2.129

8.  Simultaneous colour constancy revisited: an analysis of viewing strategies.

Authors:  F W Cornelissen; E Brenner
Journal:  Vision Res       Date:  1995-09       Impact factor: 1.886

9.  A device performing illuminant-invariant assessment of chromatic relations.

Authors:  M H Brill
Journal:  J Theor Biol       Date:  1978-04-06       Impact factor: 2.691

10.  Selective color constancy deficits after circumscribed unilateral brain lesions.

Authors:  L Rüttiger; D I Braun; K R Gegenfurtner; D Petersen; P Schönle; L T Sharpe
Journal:  J Neurosci       Date:  1999-04-15       Impact factor: 6.167

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  45 in total

1.  Slow updating of the achromatic point after a change in illumination.

Authors:  Robert J Lee; Kathryn A Dawson; Hannah E Smithson
Journal:  J Vis       Date:  2012-01-24       Impact factor: 2.240

2.  A Bayesian model of lightness perception that incorporates spatial variation in the illumination.

Authors:  Sarah R Allred; David H Brainard
Journal:  J Vis       Date:  2013-06-28       Impact factor: 2.240

Review 3.  The perception of colour and material in naturalistic tasks.

Authors:  David H Brainard; Nicolas P Cottaris; Ana Radonjić
Journal:  Interface Focus       Date:  2018-06-15       Impact factor: 3.906

4.  Illumination discrimination for chromatically biased illuminations: Implications for color constancy.

Authors:  Stacey Aston; Ana Radonjic; David H Brainard; Anya C Hurlbert
Journal:  J Vis       Date:  2019-03-01       Impact factor: 2.240

Review 5.  We infer light in space.

Authors:  James A Schirillo
Journal:  Psychon Bull Rev       Date:  2013-10

6.  Filling in, filling out, or filtering out: processes stabilizing color appearance near the center of gaze.

Authors:  Sean F O'Neil; Michael A Webster
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2014-04-01       Impact factor: 2.129

7.  Colour constancy in insects.

Authors:  Lars Chittka; Samia Faruq; Peter Skorupski; Annette Werner
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2014-03-20       Impact factor: 1.836

8.  Colour appearance and compensation in the near periphery.

Authors:  Michael A Webster; Kimberley Halen; Andrew J Meyers; Patricia Winkler; John S Werner
Journal:  Proc Biol Sci       Date:  2010-02-10       Impact factor: 5.349

9.  Metacontrast masking and the cortical representation of surface color: dynamical aspects of edge integration and contrast gain control.

Authors:  Michael E Rudd
Journal:  Adv Cogn Psychol       Date:  2008-07-15

10.  Low levels of specularity support operational color constancy, particularly when surface and illumination geometry can be inferred.

Authors:  Robert J Lee; Hannah E Smithson
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2016-03       Impact factor: 2.129

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