A note about the abnormal hue angle change in CIELAB space

Li, Changjun; Melgosa, Manuel

doi:10.1002/col.21733

Cited by 3 publications

(8 citation statements)

References 10 publications

(33 reference statements)

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“…(10). Thus, the chromaticity coordinates of the blue primary, denoted as P 12 , is the intersection point of the first and second lines in Eq. (10); the green primary, denoted as P 13 , is the intersection point of the first and third lines in Eq.…”

Section: Definitionsmentioning

confidence: 99%

“…This is indeed the case. In fact, if we let P be the convex combination of the two primary points P 12 Here, a and b satisfy:…”

Section: Cat02 Matrix Hpe Matrixmentioning

confidence: 99%

“…Currently, there are two kinds of adaptations in CIECAM02 which are completed in different spaces. The chromatic adaptation is completed in the sharp sensor space 12 via the CAT02 matrix and the luminance adaptation is done in the cone space via the HPE matrix. We expect to find a new CAT matrix so that it can transform from tristimulus space to cone space (behaves like the HPE matrix) and also fit the visual experiment results well.…”

Section: Introductionmentioning

confidence: 99%

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CAT02 and HPE triangles

Luo

et al. 2013

Color Research & Application

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Here, we investigated the CAT02 and HPE triangles in both x,y and u 0 ,v 0 spaces. It was found that in u 0 ,v 0 space, the HPE triangle is separated into two regions by the line 3u 0 2 8v 0 1 6 5 0, which is the u 0 ,v 0 image of X 1 Y 1 Z 5 0 under the mapping from (X,Y,Z) to (u 0 ,v 0 ). One of these two regions admits all-positive R,G,B triplets and the other all-negative R,G,B triplets, under the case of (X 1 Y 1 Z) > 0. The findings of this study explained the computation problems of CAT02 and provided methods for solving the Yellow-Blue and Purple problems simultaneously. V

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Section: Definitionsmentioning

confidence: 99%

“…This is indeed the case. In fact, if we let P be the convex combination of the two primary points P 12 Here, a and b satisfy:…”

Section: Cat02 Matrix Hpe Matrixmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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CAT02 and HPE triangles

Luo

et al. 2013

Color Research & Application

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“…First, the initial guess for the two variables were chosen at the centers of the intervals established by Eqs. (29) and (30). However, the automatic output message from MATLAB alerted us "local minimum possible, constraints satisfied" with u 0 R 50.6234 and u 0 G 520.2871, and the objective function F(u 0 R , u 0 G ) had a value of 6.4791.…”

Section: The Optimum Solutionmentioning

confidence: 96%

“…and it must be minimized, with variables u 0 R and u 0 G satisfying Eqs. (29) and (30) respectively.…”

Section: Fitting the Visual Experimental Datamentioning

confidence: 99%

Optimum solution of the CIECAM02 yellow–blue and purple problems

Jiang

Wang

Luo

et al. 2014

Color Research & Application

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Brill [Color Res Appl 2006;31:142-145] and Brill and S€ usstrunk [Color Res Appl 2008;33:424-426] found that CIECAM02 has the yellow-blue and purple problems and gave partial solutions to them. In this article we model the optimum solution to the yellow-blue and purple problems simultaneously as a constrained non-linear optimization problem. An optimum solution resulting in a new CAT02 matrix is numerically obtained. This new matrix satisfies the nesting rule and performs better than the Hunt-Pointer-Est evez (HPE) matrix in predicting both corresponding colours and colour appearance data sets. Specifically, it was found that the new and HPE matrices performed significantly different on nine (out of 21) corresponding colour data sets and on all corresponding colours data sets as a whole.

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Predictive performance of the standard and the modified von Kries chromatic adaptation transforms

Ma¹,

Teunissen

Smet³

2022

Opt. Express

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To investigate chromatic adaptation and develop chromatic adaptation transforms (CATs), many psychophysical experiments have been conducted to collect corresponding colors (CC) under various illumination conditions. Most modern CATs have been developed based on a database of CC sets collected in the 20th century. More recently, several additional CC sets have been collected by Smet et al., Wei et al., and Ma et al. using memory color matching or achromatic matching methods. The analysis of these CC data indicates that for yellowish (located on or close to the Planckian locus) and greenish illuminations, the short-wave (S) sensitive cones show a lower degree of adaptation compared to the long-wave (L) and medium-wave (M) sensitive cones. This can result in a large prediction error of the standard von Kries CAT, which adopts a single degree of adaptation value for all three cone types. A modified von Kries CAT is proposed that accounts for these differences between the L-, M- and S-cone signals by applying a compression to the rescaling factor for the S-cones. It outperforms the standard von Kries CAT for the Breneman-C, Smet, Wei, and Ma data, while for other data sources the two CATs have similar performance.

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A note about the abnormal hue angle change in CIELAB space

Cited by 3 publications

References 10 publications

CAT02 and HPE triangles

CAT02 and HPE triangles

Optimum solution of the CIECAM02 yellow–blue and purple problems

Predictive performance of the standard and the modified von Kries chromatic adaptation transforms

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