Different matrices for CIECAM02

Li, Changjun; Luo, Ming Ronnier; Wang, Zhifeng

doi:10.1002/col.21765

Cited by 9 publications

(12 citation statements)

References 10 publications

(28 reference statements)

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“…The accuracy of the predictions of the visual results using the M HPE and M CAM matrices, however, became worse compared with that obtained using the original CIECAM02 and CAT02 models. 20 Brill and S€ usstrunk [34][35][36] also found that the CIECAM02 model exhibited the so-called "yellow-blue problem" and the "purple problem," and they devised a rule for correcting them, which they called the nesting rule. If we let X M be the chromaticity domain of all X, Y, and Z values giving nonnegative R, G, and B response signals with the transformation defined by the matrix M (see Equation 3), and similarly for X HPE , then the nesting rule can be exactly stated as 37 :…”

Section: Illuminant Luminance Adaptationmentioning

confidence: 99%

“…Li et al has pointed that if the matrix

boldM

equals the matrix

M_{H P E}

, the inequality in Equation holds for all colors with chromaticity coordinates located inside the domain (named as

Ω_{C I E}

) enclosed by the CIE spectrum locus and the purple line. In addition, Li et al defined another matrix. named as

M_{C A M}

, under the conditions: (a) the

M_{C A M}

matrix satisfies the inequality in Equation ; and (b) with the

M_{C A M}

matrix the new CAM and new CAT fit the color appearance datasets and corresponding color datasets as closely as possible.…”

Section: Introductionmentioning

confidence: 99%

“…named as

M_{C A M}

, under the conditions: (a) the

M_{C A M}

matrix satisfies the inequality in Equation ; and (b) with the

M_{C A M}

matrix the new CAM and new CAT fit the color appearance datasets and corresponding color datasets as closely as possible. The accuracy of the predictions of the visual results using the

M_{H P E}

and

M_{C A M}

matrices, however, became worse compared with that obtained using the original CIECAM02 and CAT02 models …”

Section: Introductionmentioning

confidence: 99%

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Comprehensive color solutions: CAM16, CAT16, and CAM16‐UCS

Wang

et al. 2017

Color Research & Application

Self Cite

181

195

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The CIECAM02 color‐appearance model enjoys popularity in scientific research and industrial applications since it was recommended by the CIE in 2002. However, it has been found that computational failures can occur in certain cases such as during the image processing of cross‐media color reproduction applications. Some proposals have been developed to repair the CIECAM02 model. However, all the proposals developed have the same structure as the original CIECAM02 model and solve the problems concerned at the expense of losing accuracy of predicted visual data compared with the original model. In this article, the structure of the CIECAM02 model is changed and the color and luminance adaptations to the illuminant are completed in the same space rather than in two different spaces, as in the original CIECAM02 model. It has been found that the new model (named CAM16) not only overcomes the previous problems, but also the performance in predicting the visual results is as good as if not better than that of the original CIECAM02 model. Furthermore the new CAM16 model is simpler than the original CIECAM02 model. In addition, if considering only chromatic adaptation, a new transformation, CAT16, is proposed to replace the previous CAT02 transformation. Finally, the new CAM16‐UCS uniform color space is proposed to replace the previous CAM02‐UCS space. A new complete solution for color‐appearance prediction and color‐difference evaluation can now be offered.

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Section: Illuminant Luminance Adaptationmentioning

confidence: 99%

“…Li et al has pointed that if the matrix

boldM

equals the matrix

M_{H P E}

, the inequality in Equation holds for all colors with chromaticity coordinates located inside the domain (named as

Ω_{C I E}

) enclosed by the CIE spectrum locus and the purple line. In addition, Li et al defined another matrix. named as

M_{C A M}

, under the conditions: (a) the

M_{C A M}

matrix satisfies the inequality in Equation ; and (b) with the

M_{C A M}

matrix the new CAM and new CAT fit the color appearance datasets and corresponding color datasets as closely as possible.…”

Section: Introductionmentioning

confidence: 99%

“…named as

M_{C A M}

, under the conditions: (a) the

M_{C A M}

matrix satisfies the inequality in Equation ; and (b) with the

M_{C A M}

matrix the new CAM and new CAT fit the color appearance datasets and corresponding color datasets as closely as possible. The accuracy of the predictions of the visual results using the

M_{H P E}

and

M_{C A M}

matrices, however, became worse compared with that obtained using the original CIECAM02 and CAT02 models …”

Section: Introductionmentioning

confidence: 99%

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Comprehensive color solutions: CAM16, CAT16, and CAM16‐UCS

Wang

et al. 2017

Color Research & Application

Self Cite

181

195

View full text Add to dashboard Cite

show abstract

“…CIE TC8‐11, chartered to grapple with mathematical problems of CIECAM02, has found that reversion to a nonsharpened primary CAT (that of Hunt, Pointer, and Estévez [HPE]) would eliminate most of these problems. However, some investigators have found that HPE primaries substantially degrade the agreement with experiment that is enjoyed by CIECAT02 . That is what we call the “sharpening dilemma.”…”

Section: The Sharpening Dilemmamentioning

confidence: 90%

“…However, some investigators have found that HPE primaries substantially degrade the agreement with experiment that is enjoyed by CIECAT02. 6 That is what we call the "sharpening dilemma. "…”

Section: The Sharpening Dilemmamentioning

confidence: 99%

Chromatic adaptation by illuminant matrix products: An alternative to sharpened von kries primaries

Brill¹,

Oleari

2013

Color Research & Application

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Previous attempts to predict chromatic-adaptation correspondence have led to a sharpening dilemma-i.e., Von Kries primaries are chosen that do not include in the positive octant all the realizable (x,y) chromaticities. This leads to paradoxical adaptation predictions for the colors that have negative Von Kries coordinates. A solution is proposed here that expresses the asymmetric-matching relation of chromatic adaptation as the product of two matrix transformations, given source illuminant 1 and destination illuminant 2: from source tristimulus values via adaptation matrix 1 to the adapted state coordinates, and from the adapted state via the inverse of adaptation matrix 2 to the destination illuminant tristimulus values. To avoid the sharpening instability, the entire spectrum locus must lie within the positive octant of the adapted state tristimulus space.

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Bibliography

2019

Billmeyer and Saltzman's Principles of Color Technology

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Different matrices for CIECAM02

Cited by 9 publications

References 10 publications

Comprehensive color solutions: CAM16, CAT16, and CAM16‐UCS

Comprehensive color solutions: CAM16, CAT16, and CAM16‐UCS

Chromatic adaptation by illuminant matrix products: An alternative to sharpened von kries primaries

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