Abstract

This paper describes an investigation into the performance of different gamut compression algorithms (GCAs) in different uniform colour spaces (UCSs) between small and large colour gamuts. Gamut mapping is a key component in a colour management system and has drawn much attention in the last two decades. Two new GCAs, i.e. vividness-preserved (VP) and depth-preserved (DP), based on the concepts of ‘vividness’ and ‘depth’ are proposed and compared with the other commonly used GCAs with the exception of spatial GCAs since the goal of this study was to develop an algorithm that could be implemented in real time for mobile phone applications. In addition, UCSs including CIELAB, CAM02-UCS, and a newly developed UCS, Jzazbz, were tested to verify how they affect the performance of the GCAs. A psychophysical experiment was conducted and the results showed that one of the newly proposed GCAs, VP, gave the best performance among different GCAs and the Jzazbz is a promising UCS for gamut mapping.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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2017 (2)

Y. J. Cho, L. C. Ou, G. Cui, and R. Luo, “New Colour Appearance Scales for Describing Saturation, Vividness, Blackness, and Whiteness,” Color Res. Appl. 42(5), 552–563 (2017).
[Crossref]

M. Safdar, G. Cui, Y. J. Kim, and M. R. Luo, “Perceptually Uniform Color Space for Image Signals Including High Dynamic Range and Wide Gamut,” Opt. Express 25(13), 15131–15151 (2017).
[Crossref] [PubMed]

2016 (1)

Y. J. Cho, L. C. Ou, and R. Luo, “A Cross-Cultural Comparison of Saturation, Vividness, Blackness and Whiteness Scales,” Color Res. Appl. 42(2), 203–215 (2016).
[Crossref]

2014 (1)

R. S. Berns, “Extending CIELAB: Vividness,Vab*Dab*Tab*,” Color Res. Appl. 39(4), 322–330 (2014).
[Crossref]

2010 (1)

K. McLaren, “An Introduction to Instrumental Shade Passing and Sorting and a Review of Recent Developments,” Color. Technol. 92(9), 317–326 (2010).

2007 (1)

M. Bertalmío, V. Caselles, E. Provenzi, and A. Rizzi, “Perceptual Color Correction Through Variational Techniques,” IEEE Trans. Image Process. 16(4), 1058–1072 (2007).
[Crossref] [PubMed]

2006 (1)

M. R. Luo, G. Cui, and C. Li, “Uniform Colour Spaces Based on CIECAM02 Colour Appearance Model,” Color Res. Appl. 31(4), 320–330 (2006).
[Crossref]

2002 (1)

L. MacDonald, J. Morovic, and K. Xiao, “A Topographic Gamut Compression Algorithm,” J. Imaging Sci. Technol. 46(3), 228–236 (2002).

2001 (2)

R. Bala, R. Dequeiroz, R. Eschbach, and W. Wu, “Gamut Mapping to Preserve Spatial Luminance Variations,” J. Imaging Sci. 45(5), 436–443 (2001).

J. Morovic and M. R. Luo, “Evaluating Gamut Mapping Algorithms for Universal Applicability,” Color Res. Appl. 26(1), 85–102 (2001).
[Crossref]

1996 (1)

R. S. Berns, “Methods for Characterizing CRT Displays,” Displays 16(4), 173–182 (1996).
[Crossref]

1995 (1)

L. MacDonald, J. Morovic, and D. Saunders, “Evaluation of Colour Fidelity for Reproductions of Fine Art Paintings,” Mus. Manag. Curator. 14(3), 253–281 (1995).
[Crossref]

1991 (1)

M. R. Luo, A. A. Clarke, P. A. Rhodes, A. Schappo, S. A. R. Scrivener, and C. J. Tait, “Quantifying Colour Appearance. Part I. LUTCHI Colour Appearance Data,” Color Res. Appl. 16(3), 166–180 (1991).
[Crossref]

1981 (1)

A. Hård and L. Sivik, “NCS-Natural Color System: A Swedish Standard for Color Notation,” Color Res. Appl. 6(3), 129–138 (1981).
[Crossref]

1927 (1)

L. L. Thurstone, “A Law of Comparative Judgment,” Psychol. Rev. 34(4), 273–286 (1927).
[Crossref]

Abe, S.

G. G. Marcu and S. Abe, “Gamut Mapping for Color Simulation on CRT Devices,” in Proceedings of SPIE-The International Society for Optical Engineering (1996), pp. 308–315.
[Crossref]

Bala, R.

R. Bala, R. Dequeiroz, R. Eschbach, and W. Wu, “Gamut Mapping to Preserve Spatial Luminance Variations,” J. Imaging Sci. 45(5), 436–443 (2001).

Berns, R. S.

R. S. Berns, “Extending CIELAB: Vividness,Vab*Dab*Tab*,” Color Res. Appl. 39(4), 322–330 (2014).
[Crossref]

R. S. Berns, “Methods for Characterizing CRT Displays,” Displays 16(4), 173–182 (1996).
[Crossref]

Bertalmío, M.

M. Bertalmío, V. Caselles, E. Provenzi, and A. Rizzi, “Perceptual Color Correction Through Variational Techniques,” IEEE Trans. Image Process. 16(4), 1058–1072 (2007).
[Crossref] [PubMed]

S. W. Zamir, J. Vazquez-Corral, and M. Bertalmío, “Gamut Mapping through Perceptually-Based Contrast Reduction,” in Pacific-Rim Symposium on Image and Video Technology (2013), pp. 1–11.

Caselles, V.

M. Bertalmío, V. Caselles, E. Provenzi, and A. Rizzi, “Perceptual Color Correction Through Variational Techniques,” IEEE Trans. Image Process. 16(4), 1058–1072 (2007).
[Crossref] [PubMed]

Cho, M. S.

B. H. Kang, M. S. Cho, J. Morovic, and M. R. Luo, “Gamut Compression Algorithm Development Using Observer Experimental Data,” in Proceedings of the 7th Color Imaging Conference (2000), pp. 295–300.

Cho, Y. J.

Y. J. Cho, L. C. Ou, G. Cui, and R. Luo, “New Colour Appearance Scales for Describing Saturation, Vividness, Blackness, and Whiteness,” Color Res. Appl. 42(5), 552–563 (2017).
[Crossref]

Y. J. Cho, L. C. Ou, and R. Luo, “A Cross-Cultural Comparison of Saturation, Vividness, Blackness and Whiteness Scales,” Color Res. Appl. 42(2), 203–215 (2016).
[Crossref]

Clarke, A. A.

M. R. Luo, A. A. Clarke, P. A. Rhodes, A. Schappo, S. A. R. Scrivener, and C. J. Tait, “Quantifying Colour Appearance. Part I. LUTCHI Colour Appearance Data,” Color Res. Appl. 16(3), 166–180 (1991).
[Crossref]

Cui, G.

Y. J. Cho, L. C. Ou, G. Cui, and R. Luo, “New Colour Appearance Scales for Describing Saturation, Vividness, Blackness, and Whiteness,” Color Res. Appl. 42(5), 552–563 (2017).
[Crossref]

M. Safdar, G. Cui, Y. J. Kim, and M. R. Luo, “Perceptually Uniform Color Space for Image Signals Including High Dynamic Range and Wide Gamut,” Opt. Express 25(13), 15131–15151 (2017).
[Crossref] [PubMed]

M. R. Luo, G. Cui, and C. Li, “Uniform Colour Spaces Based on CIECAM02 Colour Appearance Model,” Color Res. Appl. 31(4), 320–330 (2006).
[Crossref]

Dequeiroz, R.

R. Bala, R. Dequeiroz, R. Eschbach, and W. Wu, “Gamut Mapping to Preserve Spatial Luminance Variations,” J. Imaging Sci. 45(5), 436–443 (2001).

Eschbach, R.

R. Bala, R. Dequeiroz, R. Eschbach, and W. Wu, “Gamut Mapping to Preserve Spatial Luminance Variations,” J. Imaging Sci. 45(5), 436–443 (2001).

Fairchild, M. D.

N. Moroney, M. D. Fairchild, R. W. G. Hunt, C. Li, M. R. Luo, and T. Newman, “The CIECAM02 Color Appearance Model,” in Color and Imaging Conference (2002), pp. 23–27.

Hård, A.

A. Hård and L. Sivik, “NCS-Natural Color System: A Swedish Standard for Color Notation,” Color Res. Appl. 6(3), 129–138 (1981).
[Crossref]

Hunt, R. W. G.

N. Moroney, M. D. Fairchild, R. W. G. Hunt, C. Li, M. R. Luo, and T. Newman, “The CIECAM02 Color Appearance Model,” in Color and Imaging Conference (2002), pp. 23–27.

Kang, B. H.

B. H. Kang, M. S. Cho, J. Morovic, and M. R. Luo, “Gamut Compression Algorithm Development Using Observer Experimental Data,” in Proceedings of the 7th Color Imaging Conference (2000), pp. 295–300.

Kim, Y. J.

Li, C.

M. R. Luo, G. Cui, and C. Li, “Uniform Colour Spaces Based on CIECAM02 Colour Appearance Model,” Color Res. Appl. 31(4), 320–330 (2006).
[Crossref]

N. Moroney, M. D. Fairchild, R. W. G. Hunt, C. Li, M. R. Luo, and T. Newman, “The CIECAM02 Color Appearance Model,” in Color and Imaging Conference (2002), pp. 23–27.

Luo, M. R.

M. Safdar, G. Cui, Y. J. Kim, and M. R. Luo, “Perceptually Uniform Color Space for Image Signals Including High Dynamic Range and Wide Gamut,” Opt. Express 25(13), 15131–15151 (2017).
[Crossref] [PubMed]

M. R. Luo, G. Cui, and C. Li, “Uniform Colour Spaces Based on CIECAM02 Colour Appearance Model,” Color Res. Appl. 31(4), 320–330 (2006).
[Crossref]

J. Morovic and M. R. Luo, “Evaluating Gamut Mapping Algorithms for Universal Applicability,” Color Res. Appl. 26(1), 85–102 (2001).
[Crossref]

M. R. Luo, A. A. Clarke, P. A. Rhodes, A. Schappo, S. A. R. Scrivener, and C. J. Tait, “Quantifying Colour Appearance. Part I. LUTCHI Colour Appearance Data,” Color Res. Appl. 16(3), 166–180 (1991).
[Crossref]

B. H. Kang, M. S. Cho, J. Morovic, and M. R. Luo, “Gamut Compression Algorithm Development Using Observer Experimental Data,” in Proceedings of the 7th Color Imaging Conference (2000), pp. 295–300.

N. Moroney, M. D. Fairchild, R. W. G. Hunt, C. Li, M. R. Luo, and T. Newman, “The CIECAM02 Color Appearance Model,” in Color and Imaging Conference (2002), pp. 23–27.

C. Sano, T. Song, and M. R. Luo, “Colour Differences for Complex Images,” in Color Imaging Conference (2003), pp. 121–126.

Luo, R.

Y. J. Cho, L. C. Ou, G. Cui, and R. Luo, “New Colour Appearance Scales for Describing Saturation, Vividness, Blackness, and Whiteness,” Color Res. Appl. 42(5), 552–563 (2017).
[Crossref]

Y. J. Cho, L. C. Ou, and R. Luo, “A Cross-Cultural Comparison of Saturation, Vividness, Blackness and Whiteness Scales,” Color Res. Appl. 42(2), 203–215 (2016).
[Crossref]

MacDonald, L.

L. MacDonald, J. Morovic, and K. Xiao, “A Topographic Gamut Compression Algorithm,” J. Imaging Sci. Technol. 46(3), 228–236 (2002).

L. MacDonald, J. Morovic, and D. Saunders, “Evaluation of Colour Fidelity for Reproductions of Fine Art Paintings,” Mus. Manag. Curator. 14(3), 253–281 (1995).
[Crossref]

Marcu, G. G.

G. G. Marcu and S. Abe, “Gamut Mapping for Color Simulation on CRT Devices,” in Proceedings of SPIE-The International Society for Optical Engineering (1996), pp. 308–315.
[Crossref]

McLaren, K.

K. McLaren, “An Introduction to Instrumental Shade Passing and Sorting and a Review of Recent Developments,” Color. Technol. 92(9), 317–326 (2010).

Moroney, N.

N. Moroney, M. D. Fairchild, R. W. G. Hunt, C. Li, M. R. Luo, and T. Newman, “The CIECAM02 Color Appearance Model,” in Color and Imaging Conference (2002), pp. 23–27.

Moroney, N. M.

J. A. Viggiano and N. M. Moroney, “Color Reproduction Algorithms and Intent,” in Color and Imaging Conference (1995), pp. 152–154.

Morovic, J.

L. MacDonald, J. Morovic, and K. Xiao, “A Topographic Gamut Compression Algorithm,” J. Imaging Sci. Technol. 46(3), 228–236 (2002).

J. Morovic and M. R. Luo, “Evaluating Gamut Mapping Algorithms for Universal Applicability,” Color Res. Appl. 26(1), 85–102 (2001).
[Crossref]

L. MacDonald, J. Morovic, and D. Saunders, “Evaluation of Colour Fidelity for Reproductions of Fine Art Paintings,” Mus. Manag. Curator. 14(3), 253–281 (1995).
[Crossref]

J. Morovic and P. L. Sun, “Non-Iterative Minimum Gamut Clipping,” in Proceedings of the 9th Color Imaging Conference (2001), pp. 251–256.

B. H. Kang, M. S. Cho, J. Morovic, and M. R. Luo, “Gamut Compression Algorithm Development Using Observer Experimental Data,” in Proceedings of the 7th Color Imaging Conference (2000), pp. 295–300.

J. Morovic and Y. Wang, “A Multi-Resolution, Full-Colour Spatial Gamut Mapping Algorithm,” in Proceedings of Color Imaging Conference (2003), pp. 282–287.

Newman, T.

N. Moroney, M. D. Fairchild, R. W. G. Hunt, C. Li, M. R. Luo, and T. Newman, “The CIECAM02 Color Appearance Model,” in Color and Imaging Conference (2002), pp. 23–27.

Ou, L. C.

Y. J. Cho, L. C. Ou, G. Cui, and R. Luo, “New Colour Appearance Scales for Describing Saturation, Vividness, Blackness, and Whiteness,” Color Res. Appl. 42(5), 552–563 (2017).
[Crossref]

Y. J. Cho, L. C. Ou, and R. Luo, “A Cross-Cultural Comparison of Saturation, Vividness, Blackness and Whiteness Scales,” Color Res. Appl. 42(2), 203–215 (2016).
[Crossref]

Provenzi, E.

M. Bertalmío, V. Caselles, E. Provenzi, and A. Rizzi, “Perceptual Color Correction Through Variational Techniques,” IEEE Trans. Image Process. 16(4), 1058–1072 (2007).
[Crossref] [PubMed]

Rhodes, P. A.

M. R. Luo, A. A. Clarke, P. A. Rhodes, A. Schappo, S. A. R. Scrivener, and C. J. Tait, “Quantifying Colour Appearance. Part I. LUTCHI Colour Appearance Data,” Color Res. Appl. 16(3), 166–180 (1991).
[Crossref]

Rizzi, A.

M. Bertalmío, V. Caselles, E. Provenzi, and A. Rizzi, “Perceptual Color Correction Through Variational Techniques,” IEEE Trans. Image Process. 16(4), 1058–1072 (2007).
[Crossref] [PubMed]

Safdar, M.

Sano, C.

C. Sano, T. Song, and M. R. Luo, “Colour Differences for Complex Images,” in Color Imaging Conference (2003), pp. 121–126.

Saunders, D.

L. MacDonald, J. Morovic, and D. Saunders, “Evaluation of Colour Fidelity for Reproductions of Fine Art Paintings,” Mus. Manag. Curator. 14(3), 253–281 (1995).
[Crossref]

Schappo, A.

M. R. Luo, A. A. Clarke, P. A. Rhodes, A. Schappo, S. A. R. Scrivener, and C. J. Tait, “Quantifying Colour Appearance. Part I. LUTCHI Colour Appearance Data,” Color Res. Appl. 16(3), 166–180 (1991).
[Crossref]

Scrivener, S. A. R.

M. R. Luo, A. A. Clarke, P. A. Rhodes, A. Schappo, S. A. R. Scrivener, and C. J. Tait, “Quantifying Colour Appearance. Part I. LUTCHI Colour Appearance Data,” Color Res. Appl. 16(3), 166–180 (1991).
[Crossref]

Sivik, L.

A. Hård and L. Sivik, “NCS-Natural Color System: A Swedish Standard for Color Notation,” Color Res. Appl. 6(3), 129–138 (1981).
[Crossref]

Song, T.

C. Sano, T. Song, and M. R. Luo, “Colour Differences for Complex Images,” in Color Imaging Conference (2003), pp. 121–126.

Sun, P. L.

J. Morovic and P. L. Sun, “Non-Iterative Minimum Gamut Clipping,” in Proceedings of the 9th Color Imaging Conference (2001), pp. 251–256.

Tait, C. J.

M. R. Luo, A. A. Clarke, P. A. Rhodes, A. Schappo, S. A. R. Scrivener, and C. J. Tait, “Quantifying Colour Appearance. Part I. LUTCHI Colour Appearance Data,” Color Res. Appl. 16(3), 166–180 (1991).
[Crossref]

Thurstone, L. L.

L. L. Thurstone, “A Law of Comparative Judgment,” Psychol. Rev. 34(4), 273–286 (1927).
[Crossref]

Vazquez-Corral, J.

S. W. Zamir, J. Vazquez-Corral, and M. Bertalmío, “Gamut Mapping through Perceptually-Based Contrast Reduction,” in Pacific-Rim Symposium on Image and Video Technology (2013), pp. 1–11.

Viggiano, J. A.

J. A. Viggiano and N. M. Moroney, “Color Reproduction Algorithms and Intent,” in Color and Imaging Conference (1995), pp. 152–154.

Wang, Y.

J. Morovic and Y. Wang, “A Multi-Resolution, Full-Colour Spatial Gamut Mapping Algorithm,” in Proceedings of Color Imaging Conference (2003), pp. 282–287.

Wu, W.

R. Bala, R. Dequeiroz, R. Eschbach, and W. Wu, “Gamut Mapping to Preserve Spatial Luminance Variations,” J. Imaging Sci. 45(5), 436–443 (2001).

Xiao, K.

L. MacDonald, J. Morovic, and K. Xiao, “A Topographic Gamut Compression Algorithm,” J. Imaging Sci. Technol. 46(3), 228–236 (2002).

Zamir, S. W.

S. W. Zamir, J. Vazquez-Corral, and M. Bertalmío, “Gamut Mapping through Perceptually-Based Contrast Reduction,” in Pacific-Rim Symposium on Image and Video Technology (2013), pp. 1–11.

Color Res. Appl. (7)

J. Morovic and M. R. Luo, “Evaluating Gamut Mapping Algorithms for Universal Applicability,” Color Res. Appl. 26(1), 85–102 (2001).
[Crossref]

R. S. Berns, “Extending CIELAB: Vividness,Vab*Dab*Tab*,” Color Res. Appl. 39(4), 322–330 (2014).
[Crossref]

M. R. Luo, A. A. Clarke, P. A. Rhodes, A. Schappo, S. A. R. Scrivener, and C. J. Tait, “Quantifying Colour Appearance. Part I. LUTCHI Colour Appearance Data,” Color Res. Appl. 16(3), 166–180 (1991).
[Crossref]

Y. J. Cho, L. C. Ou, and R. Luo, “A Cross-Cultural Comparison of Saturation, Vividness, Blackness and Whiteness Scales,” Color Res. Appl. 42(2), 203–215 (2016).
[Crossref]

Y. J. Cho, L. C. Ou, G. Cui, and R. Luo, “New Colour Appearance Scales for Describing Saturation, Vividness, Blackness, and Whiteness,” Color Res. Appl. 42(5), 552–563 (2017).
[Crossref]

M. R. Luo, G. Cui, and C. Li, “Uniform Colour Spaces Based on CIECAM02 Colour Appearance Model,” Color Res. Appl. 31(4), 320–330 (2006).
[Crossref]

A. Hård and L. Sivik, “NCS-Natural Color System: A Swedish Standard for Color Notation,” Color Res. Appl. 6(3), 129–138 (1981).
[Crossref]

Color. Technol. (1)

K. McLaren, “An Introduction to Instrumental Shade Passing and Sorting and a Review of Recent Developments,” Color. Technol. 92(9), 317–326 (2010).

Displays (1)

R. S. Berns, “Methods for Characterizing CRT Displays,” Displays 16(4), 173–182 (1996).
[Crossref]

IEEE Trans. Image Process. (1)

M. Bertalmío, V. Caselles, E. Provenzi, and A. Rizzi, “Perceptual Color Correction Through Variational Techniques,” IEEE Trans. Image Process. 16(4), 1058–1072 (2007).
[Crossref] [PubMed]

J. Imaging Sci. (1)

R. Bala, R. Dequeiroz, R. Eschbach, and W. Wu, “Gamut Mapping to Preserve Spatial Luminance Variations,” J. Imaging Sci. 45(5), 436–443 (2001).

J. Imaging Sci. Technol. (1)

L. MacDonald, J. Morovic, and K. Xiao, “A Topographic Gamut Compression Algorithm,” J. Imaging Sci. Technol. 46(3), 228–236 (2002).

Mus. Manag. Curator. (1)

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Figures (11)

Fig. 1
Fig. 1 Left is an illustration of the SGCK algorithm, where the source color o is mapped to the destination color r. Point E is the focal point having the same lightness as the CUSP. On the right is an illustration of the TOPO algorithm, where there are multi mapping directions such as from S29% to C29%, and S71% to C71%.
Fig. 2
Fig. 2 Illustration of lightness mapping. P is the colour to be mapped, P' is the point with lightness mapped.
Fig. 3
Fig. 3 Illustration of mapping towards the focal point (VP).
Fig. 4
Fig. 4 Illustration of mapping towards the lightness axis.
Fig. 5
Fig. 5 The illustration of the original and reproduction gamuts in CIELAB space.
Fig. 6
Fig. 6 Illustration of the gamuts of display, standard DCI-P3 and sRGB.
Fig. 7
Fig. 7 The six test images: (1) Fruit basket, (2) Threads, (3) Musician, (4) Colour patches, (5) Picnic, and (6) Ski.
Fig. 8
Fig. 8 Experimental setup for comparison of the original image (centre) with reproduction images (left and right).
Fig. 9
Fig. 9 Z-scores of different GCA and UCS combinations (5*3) for the repeated image.
Fig. 10
Fig. 10 Overall z-scores for the 5 GCAs and 3 UCSs.
Fig. 11
Fig. 11 Disability of HPMINDE (left: HPMINDE, right: VP).

Tables (4)

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Table 1 Summary of the GCAs introduced.

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Table 2 Wrong decisions of intra-observer and inter-observer in percentage.

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Table 3 Ranking of GCAs and UCSs Performance versus Image. A mean rank of 1 denotes the best and of 15 denotes the worst, L = CIELAB, C = CAM02-UCS, J = Jzazbz.

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Table 4 Image Dependency for GCAs and UCSs.

Equations (3)

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L ' = Lmin( L o ) max( L o )min( L o ) *(max( L r )min( L r ))+min( L r )
E P ' ¯ ={ EP ¯ ; EP ¯ 0.9* E P d ¯ 0.9* E P d ¯ + EP ¯ 0.9* E P d ¯ E P s ¯ 0.9* E P d ¯ * E P d ¯ 10 ; EP ¯ >0.9* E P d ¯
CI=A±1.96 σ N

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