Abstract

A colour quality metric based on memory colours is presented. The basic idea is simple. The colour quality of a test source is evaluated as the degree of similarity between the colour appearance of a set of familiar objects and their memory colours. The closer the match, the better the colour quality. This similarity was quantified using a set of similarity distributions obtained by Smet et al. in a previous study. The metric was validated by calculating the Pearson and Spearman correlation coefficients between the metric predictions and the visual appreciation results obtained in a validation experiment conducted by the authors as well those obtained in two independent studies. The metric was found to correlate well with the visual appreciation of the lighting quality of the sources used in the three experiments. Its performance was also compared with that of the CIE colour rendering index and the NIST colour quality scale. For all three experiments, the metric was found to be significantly better at predicting the correct visual rank order of the light sources (p < 0.1).

© 2010 OSA

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  41. H. Scheffé, “An analysis of variance for paired comparisons,” J. Am. Stat. Assoc. 47(259), 381–400 (1952).
    [CrossRef]
  42. A. T. Basilevsky, Statistical Factor Analysis and Related Methods: Theory and Applications (Wiley-Interscience, Chichester, 1994).
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    [CrossRef]

2010 (2)

P. van der Burgt and J. van Kemenade, “About color rendition of light sources: The balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2010).

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49(3), 033602 (2010).
[CrossRef]

2009 (2)

S. Jost-Boissard, M. Fontoynont, and J. Blanc-Gonnet, “Perceived lighting quality of LED sources for the presentation of fruit and vegetables,” J. Mod. Opt. 56(13), 1420 (2009).
[CrossRef]

W. Davis and Y. Ohno, “Approaches to color rendering measurement,” J. Mod. Opt. 56(13), 1412–1419 (2009).
[CrossRef]

2008 (1)

M. Olkkonen, T. Hansen, and K. R. Gegenfurtner, “Color appearance of familiar objects: effects of object shape, texture, and illumination changes,” J. Vis. 8(5), 13–16 (2008).
[CrossRef] [PubMed]

2007 (1)

K. Hashimoto, T. Yano, M. Shimizu, and Y. Nayatani, “New method for specifying color-rendering properties of light sources based on feeling of contrast,” Color Res. Appl. 32(5), 361–371 (2007).
[CrossRef]

2005 (1)

A. C. Hurlbert and Y. Ling, “If it's a banana, it must be yellow: The role of memory colors in color constancy,” J. Vis. 5(8), 787–787 (2005).
[CrossRef]

2001 (1)

P. Bodrogi and T. Tarczali, “Colour memory for various sky, skin, and plant colours: Effect of the image context,” Color Res. Appl. 26(4), 278–289 (2001).
[CrossRef]

1999 (2)

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Representation of memory prototype for an object color,” Color Res. Appl. 24(6), 393–410 (1999).
[CrossRef]

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Color reproduction and the naturalness constraint,” Color Res. Appl. 24(1), 52–67 (1999).
[CrossRef]

1998 (1)

J. Pérez-Carpinell, M. D. de Fez, R. Baldoví, and J. C. Soriano, “Familiar objects and memory color,” Color Res. Appl. 23(6), 416–427 (1998).
[CrossRef]

1994 (1)

L. L. Thurstone, “A law of comparative judgment,” Psychol. Rev. 101(2), 266–270 (1994).
[CrossRef]

1992 (1)

X. L. Meng, R. Rosenthal, and D. B. Rubin, “Comparing correlated correlation coefficients,” Psychol. Bull. 111(1), 172–175 (1992).
[CrossRef]

1983 (1)

P. Siple and R. M. Springer, “Memory and preference for the colors of objects,” Percept. Psychophys. 34(4), 363–370 (1983).
[CrossRef] [PubMed]

1972 (1)

W. A. Thornton, “A validation of the color preference index,” Illum. Eng. 62, 191–194 (1972).

1967 (1)

D. B. Judd, “A flattery index for artificial illuminants,” Illum. Eng. 62, 593–598 (1967).

1961 (1)

C. J. Bartleson, “Color in memory in relation to photographic reproduction,” Photon. Sci. Eng. 5, 327–331 (1961).

1960 (1)

C. J. Bartleson, “Memory colors of familiar objects,” J. Opt. Soc. Am. 50(1), 73–77 (1960).
[CrossRef] [PubMed]

1959 (2)

C. L. Sanders, “Colour preferences for natural objects,” Illum. Eng. 54, 452–456 (1959).

C. L. Sanders, “Assessment of color rendition under an iIlluminant using color tolerances for natural objects,” Illum. Eng. 54, 640–646 (1959).

1957 (1)

S. M. Newhall, R. W. Burnham, and J. R. Clark, “Comparison of Successive with Simultaneous Color Matching,” J. Opt. Soc. Am. 47(1), 43–54 (1957).
[CrossRef]

1952 (1)

H. Scheffé, “An analysis of variance for paired comparisons,” J. Am. Stat. Assoc. 47(259), 381–400 (1952).
[CrossRef]

Baldoví, R.

J. Pérez-Carpinell, M. D. de Fez, R. Baldoví, and J. C. Soriano, “Familiar objects and memory color,” Color Res. Appl. 23(6), 416–427 (1998).
[CrossRef]

Bartleson, C. J.

C. J. Bartleson, “Color in memory in relation to photographic reproduction,” Photon. Sci. Eng. 5, 327–331 (1961).

C. J. Bartleson, “Memory colors of familiar objects,” J. Opt. Soc. Am. 50(1), 73–77 (1960).
[CrossRef] [PubMed]

Blanc-Gonnet, J.

S. Jost-Boissard, M. Fontoynont, and J. Blanc-Gonnet, “Perceived lighting quality of LED sources for the presentation of fruit and vegetables,” J. Mod. Opt. 56(13), 1420 (2009).
[CrossRef]

Blommaert, F. J. J.

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Color reproduction and the naturalness constraint,” Color Res. Appl. 24(1), 52–67 (1999).
[CrossRef]

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Representation of memory prototype for an object color,” Color Res. Appl. 24(6), 393–410 (1999).
[CrossRef]

Bodrogi, P.

P. Bodrogi and T. Tarczali, “Colour memory for various sky, skin, and plant colours: Effect of the image context,” Color Res. Appl. 26(4), 278–289 (2001).
[CrossRef]

Burnham, R. W.

S. M. Newhall, R. W. Burnham, and J. R. Clark, “Comparison of Successive with Simultaneous Color Matching,” J. Opt. Soc. Am. 47(1), 43–54 (1957).
[CrossRef]

Clark, J. R.

S. M. Newhall, R. W. Burnham, and J. R. Clark, “Comparison of Successive with Simultaneous Color Matching,” J. Opt. Soc. Am. 47(1), 43–54 (1957).
[CrossRef]

Davis, W.

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49(3), 033602 (2010).
[CrossRef]

W. Davis and Y. Ohno, “Approaches to color rendering measurement,” J. Mod. Opt. 56(13), 1412–1419 (2009).
[CrossRef]

de Fez, M. D.

J. Pérez-Carpinell, M. D. de Fez, R. Baldoví, and J. C. Soriano, “Familiar objects and memory color,” Color Res. Appl. 23(6), 416–427 (1998).
[CrossRef]

de Ridder, H.

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Color reproduction and the naturalness constraint,” Color Res. Appl. 24(1), 52–67 (1999).
[CrossRef]

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Representation of memory prototype for an object color,” Color Res. Appl. 24(6), 393–410 (1999).
[CrossRef]

Fontoynont, M.

S. Jost-Boissard, M. Fontoynont, and J. Blanc-Gonnet, “Perceived lighting quality of LED sources for the presentation of fruit and vegetables,” J. Mod. Opt. 56(13), 1420 (2009).
[CrossRef]

Gegenfurtner, K. R.

M. Olkkonen, T. Hansen, and K. R. Gegenfurtner, “Color appearance of familiar objects: effects of object shape, texture, and illumination changes,” J. Vis. 8(5), 13–16 (2008).
[CrossRef] [PubMed]

Hansen, T.

M. Olkkonen, T. Hansen, and K. R. Gegenfurtner, “Color appearance of familiar objects: effects of object shape, texture, and illumination changes,” J. Vis. 8(5), 13–16 (2008).
[CrossRef] [PubMed]

Hashimoto, K.

K. Hashimoto, T. Yano, M. Shimizu, and Y. Nayatani, “New method for specifying color-rendering properties of light sources based on feeling of contrast,” Color Res. Appl. 32(5), 361–371 (2007).
[CrossRef]

Hurlbert, A. C.

A. C. Hurlbert and Y. Ling, “If it's a banana, it must be yellow: The role of memory colors in color constancy,” J. Vis. 5(8), 787–787 (2005).
[CrossRef]

Jost-Boissard, S.

S. Jost-Boissard, M. Fontoynont, and J. Blanc-Gonnet, “Perceived lighting quality of LED sources for the presentation of fruit and vegetables,” J. Mod. Opt. 56(13), 1420 (2009).
[CrossRef]

Judd, D. B.

D. B. Judd, “A flattery index for artificial illuminants,” Illum. Eng. 62, 593–598 (1967).

Ling, Y.

A. C. Hurlbert and Y. Ling, “If it's a banana, it must be yellow: The role of memory colors in color constancy,” J. Vis. 5(8), 787–787 (2005).
[CrossRef]

Meng, X. L.

X. L. Meng, R. Rosenthal, and D. B. Rubin, “Comparing correlated correlation coefficients,” Psychol. Bull. 111(1), 172–175 (1992).
[CrossRef]

Nayatani, Y.

K. Hashimoto, T. Yano, M. Shimizu, and Y. Nayatani, “New method for specifying color-rendering properties of light sources based on feeling of contrast,” Color Res. Appl. 32(5), 361–371 (2007).
[CrossRef]

Newhall, S. M.

S. M. Newhall, R. W. Burnham, and J. R. Clark, “Comparison of Successive with Simultaneous Color Matching,” J. Opt. Soc. Am. 47(1), 43–54 (1957).
[CrossRef]

Ohno, Y.

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49(3), 033602 (2010).
[CrossRef]

W. Davis and Y. Ohno, “Approaches to color rendering measurement,” J. Mod. Opt. 56(13), 1412–1419 (2009).
[CrossRef]

Olkkonen, M.

M. Olkkonen, T. Hansen, and K. R. Gegenfurtner, “Color appearance of familiar objects: effects of object shape, texture, and illumination changes,” J. Vis. 8(5), 13–16 (2008).
[CrossRef] [PubMed]

Pérez-Carpinell, J.

J. Pérez-Carpinell, M. D. de Fez, R. Baldoví, and J. C. Soriano, “Familiar objects and memory color,” Color Res. Appl. 23(6), 416–427 (1998).
[CrossRef]

Rosenthal, R.

X. L. Meng, R. Rosenthal, and D. B. Rubin, “Comparing correlated correlation coefficients,” Psychol. Bull. 111(1), 172–175 (1992).
[CrossRef]

Rubin, D. B.

X. L. Meng, R. Rosenthal, and D. B. Rubin, “Comparing correlated correlation coefficients,” Psychol. Bull. 111(1), 172–175 (1992).
[CrossRef]

Sanders, C. L.

C. L. Sanders, “Colour preferences for natural objects,” Illum. Eng. 54, 452–456 (1959).

C. L. Sanders, “Assessment of color rendition under an iIlluminant using color tolerances for natural objects,” Illum. Eng. 54, 640–646 (1959).

Scheffé, H.

H. Scheffé, “An analysis of variance for paired comparisons,” J. Am. Stat. Assoc. 47(259), 381–400 (1952).
[CrossRef]

Shimizu, M.

K. Hashimoto, T. Yano, M. Shimizu, and Y. Nayatani, “New method for specifying color-rendering properties of light sources based on feeling of contrast,” Color Res. Appl. 32(5), 361–371 (2007).
[CrossRef]

Siple, P.

P. Siple and R. M. Springer, “Memory and preference for the colors of objects,” Percept. Psychophys. 34(4), 363–370 (1983).
[CrossRef] [PubMed]

Soriano, J. C.

J. Pérez-Carpinell, M. D. de Fez, R. Baldoví, and J. C. Soriano, “Familiar objects and memory color,” Color Res. Appl. 23(6), 416–427 (1998).
[CrossRef]

Springer, R. M.

P. Siple and R. M. Springer, “Memory and preference for the colors of objects,” Percept. Psychophys. 34(4), 363–370 (1983).
[CrossRef] [PubMed]

Tarczali, T.

P. Bodrogi and T. Tarczali, “Colour memory for various sky, skin, and plant colours: Effect of the image context,” Color Res. Appl. 26(4), 278–289 (2001).
[CrossRef]

Thornton, W. A.

W. A. Thornton, “A validation of the color preference index,” Illum. Eng. 62, 191–194 (1972).

Thurstone, L. L.

L. L. Thurstone, “A law of comparative judgment,” Psychol. Rev. 101(2), 266–270 (1994).
[CrossRef]

van der Burgt, P.

P. van der Burgt and J. van Kemenade, “About color rendition of light sources: The balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2010).

van Kemenade, J.

P. van der Burgt and J. van Kemenade, “About color rendition of light sources: The balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2010).

Yano, T.

K. Hashimoto, T. Yano, M. Shimizu, and Y. Nayatani, “New method for specifying color-rendering properties of light sources based on feeling of contrast,” Color Res. Appl. 32(5), 361–371 (2007).
[CrossRef]

Yendrikhovskij, S. N.

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Color reproduction and the naturalness constraint,” Color Res. Appl. 24(1), 52–67 (1999).
[CrossRef]

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Representation of memory prototype for an object color,” Color Res. Appl. 24(6), 393–410 (1999).
[CrossRef]

Color Res. Appl. (6)

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Color reproduction and the naturalness constraint,” Color Res. Appl. 24(1), 52–67 (1999).
[CrossRef]

J. Pérez-Carpinell, M. D. de Fez, R. Baldoví, and J. C. Soriano, “Familiar objects and memory color,” Color Res. Appl. 23(6), 416–427 (1998).
[CrossRef]

S. N. Yendrikhovskij, F. J. J. Blommaert, and H. de Ridder, “Representation of memory prototype for an object color,” Color Res. Appl. 24(6), 393–410 (1999).
[CrossRef]

P. Bodrogi and T. Tarczali, “Colour memory for various sky, skin, and plant colours: Effect of the image context,” Color Res. Appl. 26(4), 278–289 (2001).
[CrossRef]

P. van der Burgt and J. van Kemenade, “About color rendition of light sources: The balance between simplicity and accuracy,” Color Res. Appl. 35, 85–93 (2010).

K. Hashimoto, T. Yano, M. Shimizu, and Y. Nayatani, “New method for specifying color-rendering properties of light sources based on feeling of contrast,” Color Res. Appl. 32(5), 361–371 (2007).
[CrossRef]

Illum. Eng. (4)

C. L. Sanders, “Assessment of color rendition under an iIlluminant using color tolerances for natural objects,” Illum. Eng. 54, 640–646 (1959).

D. B. Judd, “A flattery index for artificial illuminants,” Illum. Eng. 62, 593–598 (1967).

W. A. Thornton, “A validation of the color preference index,” Illum. Eng. 62, 191–194 (1972).

C. L. Sanders, “Colour preferences for natural objects,” Illum. Eng. 54, 452–456 (1959).

J. Am. Stat. Assoc. (1)

H. Scheffé, “An analysis of variance for paired comparisons,” J. Am. Stat. Assoc. 47(259), 381–400 (1952).
[CrossRef]

J. Mod. Opt. (2)

S. Jost-Boissard, M. Fontoynont, and J. Blanc-Gonnet, “Perceived lighting quality of LED sources for the presentation of fruit and vegetables,” J. Mod. Opt. 56(13), 1420 (2009).
[CrossRef]

W. Davis and Y. Ohno, “Approaches to color rendering measurement,” J. Mod. Opt. 56(13), 1412–1419 (2009).
[CrossRef]

J. Opt. Soc. Am. (2)

S. M. Newhall, R. W. Burnham, and J. R. Clark, “Comparison of Successive with Simultaneous Color Matching,” J. Opt. Soc. Am. 47(1), 43–54 (1957).
[CrossRef]

C. J. Bartleson, “Memory colors of familiar objects,” J. Opt. Soc. Am. 50(1), 73–77 (1960).
[CrossRef] [PubMed]

J. Vis. (2)

A. C. Hurlbert and Y. Ling, “If it's a banana, it must be yellow: The role of memory colors in color constancy,” J. Vis. 5(8), 787–787 (2005).
[CrossRef]

M. Olkkonen, T. Hansen, and K. R. Gegenfurtner, “Color appearance of familiar objects: effects of object shape, texture, and illumination changes,” J. Vis. 8(5), 13–16 (2008).
[CrossRef] [PubMed]

Opt. Eng. (1)

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49(3), 033602 (2010).
[CrossRef]

Percept. Psychophys. (1)

P. Siple and R. M. Springer, “Memory and preference for the colors of objects,” Percept. Psychophys. 34(4), 363–370 (1983).
[CrossRef] [PubMed]

Photon. Sci. Eng. (1)

C. J. Bartleson, “Color in memory in relation to photographic reproduction,” Photon. Sci. Eng. 5, 327–331 (1961).

Psychol. Bull. (1)

X. L. Meng, R. Rosenthal, and D. B. Rubin, “Comparing correlated correlation coefficients,” Psychol. Bull. 111(1), 172–175 (1992).
[CrossRef]

Psychol. Rev. (1)

L. L. Thurstone, “A law of comparative judgment,” Psychol. Rev. 101(2), 266–270 (1994).
[CrossRef]

Other (23)

Y. Ohno, “Spectral Colour Measurement,” in Colorimetry: Understanding the CIE System, J. Schanda, ed. (CIE Central Bureau, Vienna, Austria, 2007), pp. 5.1–5.30.

A. T. Basilevsky, Statistical Factor Analysis and Related Methods: Theory and Applications (Wiley-Interscience, Chichester, 1994).

A. Field, Discovering Statistics Using SPSS (SAGE Publications Ltd, London, UK, 2009).

M. D. Fairchild, Color Appearance Models, (John Wiley & Sons, Chichester, 2005), p. 158.

CIE, “Method of Measuring and Specifying Colour Rendering Properties of Light Sources,” in CIE13.2–1974(CIE, Vienna, Austria, 1974).

CIE, “Method of Measuring and Specifying Colour Rendering Properties of Light Sources,” in CIE13.2–1995(CIE, Vienna, Austria, 1995).

Y. Ohno, and W. Davis, “Color Quality and Spectra,” in Photonics Spectra (2008).
[PubMed]

P. Bodrogi, P. Csuti, P. Hotváth, and J. Schanda, “Why does the CIE Colour Rendering Index fail for White RGB LED Light Sources?” in CIE Expert Symposium on LED Light Sources: Physical Measurement and Visual and Photobiological Assessment(Tokyo, Japan, 2004).

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Figures (7)

Fig. 1
Fig. 1

(a) The rating distribution R(P,T) and the mean observer rating (dots) for a “green apple” in IPT colour space. (b) The memory colours and the 1d-contours of the similarity distributions in IPT space of the set of familiar objects.

Fig. 2
Fig. 2

Example of a spider web representation of a colour quality metric based on memory colours for illuminant D65 (blue) and Illuminant A (red).

Fig. 3
Fig. 3

The spectral radiance of the six light sources used in the paired comparison experiment: F4 (black), FG (magenta), Nd (cyan), LR (blue), H (green) and RGB (red).

Fig. 4
Fig. 4

The set of objects illuminated by light source “FG” as presented to the observer.

Fig. 5
Fig. 5

Factor analysis of the five colour quality descriptors investigated.

Fig. 6
Fig. 6

Correspondence of the metric predictions and the visual appreciation of the attractiveness of the lighting quality of the six light sources. The Scheffé scale values have been linearly rescaled to the range occupied by the metric values.

Fig. 7
Fig. 7

Correspondence of the metric predictions and the attractiveness of the lighting quality for the 3000K and 4000K sources. The Thurstone scale values have been linearly rescaled to the range occupied by the metric values.

Tables (9)

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Table 1 Similarity distribution parameters for each of the ten familiar objects. Parameters a 3-a 4 represent the distribution centre or memory colour in IPT colour space, while a 5-a 7 describe the shape, size and orientation of the similarity distributions

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Table 2 CCT, illuminance E, metric values S a, R a and CQS a of the sources used in the experiment. Ranking is also included

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Table 3 Scheffé scalings and rankings of the six light sources for the various quality descriptors. The average root-mean-square-differences (RMSD) between the individual observer ratings and the mean observer ratings are also given

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Table 4 Pearson correlation coefficients between the metric values and the various quality descriptors

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Table 5 Spearman correlation coefficients between the metric values and the various quality descriptors

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Table 6 Significance of the difference in predictive performance of the S a, R a and CQS a values using Meng, Rosenthals and Rubin's method for comparing correlated correlation coefficients. Values shown are the two-tailed p-values with the null hypothesis that the two compared correlation values are equal

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Table 7 Pearson and Spearman correlation coefficients of S a, R a and CQS a values with the visual appreciation results obtained by Jost-Boissard et al.

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Table 8 Pearson and Spearman correlation coefficients of the recalculated S a, R a and CQS a values, by using only special indices in the green-yellow-red region of the hue circle), with the visual appreciation results obtained by Jost-Boissard et al.

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Table 9 Significance of the difference in predictive performance of the S a, R a and CQS a values using Meng, Rosenthals and Rubin's method for comparing correlated correlation coefficients. Values shown are the two-tailed p-values with the null hypothesis that the two compared correlation values are equal

Equations (7)

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R ( P , T ) = a 1 + a 2 S ( P , T ) ; S ( P , T ) = exp ( 1 2 ( d 2 ( P , T ) ) ) ; d 2 ( P , T ) = ( X X c ) T Σ 1 ( X X c ) ;     X = ( P T ) ; X c = ( a 3 a 4 ) ; Σ 1 = [ a 5 a 7 a 7 a 6 ] ;
S i   ( X i ) =   e   1 2   [ ( X i a i , 3 ) T ( a i , 5 a i , 7 a i , 7 a i , 6 )   ( X i a i , 4 ) ]       ( i = 1 .. 1 0 )
S a = i=1 n S i n
p ( s , i j ) = 1 2 m ( k = 1 m x i j k k = 1 m x j i k )                             ( i , j = 1.. n ; k = 1.. m )
α i =   1 n j = 1 n p s , i j                                           ( i = 1.. n )
P T ( i > j ) =   ( p 11 p 12 p 21 p 22 p 1 n p n 1 p n n ) Z =   ( z 11 z 12 z 21 z 22 z 1 n z n 1 z n n )
s i =   j i , j = 1 n z i j                                               ( i = 1.. n )

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