2013
DOI: 10.1364/josaa.31.000a38
|View full text |Cite
|
Sign up to set email alerts
|

The Verriest Lecture: Visual properties of metameric blacks beyond cone vision

Abstract: The generic framework of metamerism implies that the number of sensors is smaller than the dimension of the stimulus. The metameric black paradigm was introduced by Wyszecki [Farbe2, 39 (1953)] and developed by Cohen and Kappauf [Am. J. Psychol.95, 537 (1982)]. Within a multireceptor and multiprimary scheme, we investigate how far the choice of illumination can isolate a photoreceptor response. The spectral profiles of the fundamental metamers that correspond to a collection of (x,y) values over the chromatici… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
9
0

Year Published

2015
2015
2019
2019

Publication Types

Select...
4
1
1

Relationship

1
5

Authors

Journals

citations
Cited by 8 publications
(9 citation statements)
references
References 32 publications
0
9
0
Order By: Relevance
“…Viénot and associates (Viénot & Brettel, 2014;Viénot, Brettel, Dang, & Le Rohellec, 2012) developed a seven-primary system to study the rod and melanopsin inputs to pupil responses using a metameric black framework (Cohen & Kappauf, 1982;Wyszecki, 1958). They maintained cone excitations constant while searching for ''black metamers'' that activated both rods and melanopsin.…”
Section: Discussionmentioning
confidence: 99%
“…Viénot and associates (Viénot & Brettel, 2014;Viénot, Brettel, Dang, & Le Rohellec, 2012) developed a seven-primary system to study the rod and melanopsin inputs to pupil responses using a metameric black framework (Cohen & Kappauf, 1982;Wyszecki, 1958). They maintained cone excitations constant while searching for ''black metamers'' that activated both rods and melanopsin.…”
Section: Discussionmentioning
confidence: 99%
“…Premultiplying any 3×1 dimensional vectors of S by the p×3 matrix, L (L' L) -1 produce a p×1 dimensional vector of SFCS [18].…”
Section: Applying Matrix Qmentioning
confidence: 99%
“…The larger the absolute value of PLCC, the stronger the correlation; the closer the correlation coefficient is to 0, the weaker the correlation. 4. The root mean square error (RMSE) was calculated as the size of difference between a predictive nonlinear fit of the evaluation results of each MI and corresponding color difference evaluation results ΔE * ab .…”
Section: Kendall's Rank Correlation Coefficient (Krcc) Is a Non-mentioning
confidence: 99%
“…Obviously, facing metamerism, it is difficult for us to truly solve and eliminate this phenomenon . Therefore, making use of metamerism can bring great benefits to the relevant fields of light source quality control …”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation