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Variational Methods for Gamut Mapping in Cinema and Television

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Imaging, Vision and Learning Based on Optimization and PDEs (IVLOPDE 2016)

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

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Abstract

The cinema and television industries are continuously working in the development of image features that provide a better visual experience to viewers, increasing spatial resolution, frame rate, contrast, and recently, with emerging display technologies, much more vivid colors. For this reason there is a pressing need to develop fast, automatic and reliable gamut mapping algorithms that can transform the colors of the original content, adapting it to the capabilities of the display or projector system in which it is going to be viewed while at the same time respecting the artistic intent of the creator. In this article we present a review of our work on variational methods for gamut mapping that comply with some basic global and local properties of the human visual system, producing state-of-the-art results that appear natural and are perceptually faithful to the original material.

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References

  1. A. Alsam, I. Farup, Spatial colour gamut mapping by orthogonal projection of gradients onto constant hue lines, in Proceedings of 8th International Symposium on Visual Computing (2012), pp. 556–565

    Google Scholar 

  2. H. Anderson, E. Garcia, M. Gupta, Gamut expansion for video and image sets, in International Conference on Image Analysis and Processing Workshops (2007), pp. 188–191

    Google Scholar 

  3. S. Andriani, H. Brendel, T. Seybold, J. Goldstone, Beyond the Kodak image set: a new reference set of color image sequences, in IEEE International Conference on Image Processing (2013), pp. 2289–2293

    Google Scholar 

  4. R. Bala, R. Dequeiroz, R. Eschbach, W. Wu, Gamut mapping to preserve spatial luminance variations. J. Imaging Sci. Technol. 45, 122–128 (2001)

    Google Scholar 

  5. D. Bankston, The color-space conundrum, part one. American Cinematographer (2005), p. 6

    Google Scholar 

  6. Z. Barańczuk, P. Zolliker, J. Giesen, Image quality measures for evaluating gamut mapping, in Color and Imaging Conference (2009), pp. 21–26

    Google Scholar 

  7. R.S. Berns, The mathematical development of CIE TC 1–29 proposed colour difference equation: CIELCH, in Proceedings of the Seventh Congress of International Colour Association, B, C19.1–19.4 (1993)

    Google Scholar 

  8. M. Bertalmío, Image Processing for Cinema, vol. 4 (CRC Press/Taylor & Francis, Boca Raton, 2014)

    Book  Google Scholar 

  9. M. Bertalmío, V. Caselles, E. Provenzi, A. Rizzi, Perceptual color correction through variational techniques. IEEE Trans. Image Process. 16(4), 1058–1072 (2007)

    Article  MathSciNet  Google Scholar 

  10. M. Bertalmío, V. Caselles, E. Provenzi, Issues about Retinex theory and contrast enhancement. Int. J. Comput. Vis. 83(1), 101–119 (2009)

    Article  Google Scholar 

  11. N. Bonnier, F. Schmitt, H. Brettel, S. Berche, Evaluation of spatial gamut mapping algorithms, in Proceedings of IS&T/SID 14th Color Imaging Conference (2006), pp. 56–61

    Google Scholar 

  12. G.J. Braun, A paradigm for color gamut mapping of pictorial images. Ph.D. thesis, Rochester Institute of Technology, Rochester, 1999

    Google Scholar 

  13. S.E. Casella, R.L. Heckaman, M.D. Fairchild, Mapping standard image content to wide-gamut displays, in Color and Imaging Conference (2008), pp. 106–111

    Google Scholar 

  14. X. Chen, Investigation of gamut extension algorithms. Master’s thesis, University of Derby, Derby, 2002

    Google Scholar 

  15. H.-C. Cheng, I. Ben-David, S.-T. Wu, Five-primary-color LCDs. J. Disp. Technol. 6(1), 3–7 (2010)

    Article  Google Scholar 

  16. E. Chino, K. Tajiri, H. Kawakami, H. Ohira, K. Kamijo, H. Kaneko, S. Kato, Y. Ozawa, T. Kurumisawa, K. Inoue, K. Endo, H. Moriya, T. Aragaki, K. Murai, Development of wide-color-gamut mobile displays with four-primary-color LCDs. SID Symp. Dig. Tech. Pap. 37(1), 1221–1224 (2006)

    Article  Google Scholar 

  17. CIE, Guidelines for the evaluation of gamut mapping algorithms. Technical report, CIE 156 (2004)

    Google Scholar 

  18. F. Dugay, I. Farup, J.Y. Hardeberg, Perceptual evaluation of color gamut mapping algorithms. Color Res. Appl. 33(6), 470–476 (2008)

    Article  Google Scholar 

  19. A.M. Eskicioglu, P.S. Fisher, Image quality measures and their performance. IEEE Trans. Commun. 43(12), 2959–2965 (1995)

    Article  Google Scholar 

  20. E.A. Fedorovskaya, H. de Ridder, F.J.J. Blommaert, Chroma variations and perceived quality of color images of natural scenes. Color Res. Appl. 22(2), 96–110 (1997)

    Article  Google Scholar 

  21. A. Ford, A. Roberts, Colour space conversions. http://www.poynton.com/PDFs/coloureq.pdf (1998)

  22. J. Froehlich, S. Grandinetti, B. Eberhardt, S. Walter, A. Schilling, H. Brendel, Creating cinematic wide gamut HDR-video for the evaluation of tone mapping operators and HDR-displays, in Proceedings of IS&T/SPIE Electronic Imaging (2014)

    Google Scholar 

  23. R.S. Gentile, E. Walowitt, J.P. Allebach, A comparison of techniques for color gamut mismatch compensation. J. Imaging Technol. 16, 176–181 (1990)

    Google Scholar 

  24. J.Y. Hardeberg, E. Bando, M. Pedersen, Evaluating colour image difference metrics for gamut-mapped images. Color. Technol. 124(4), 243–253 (2008)

    Article  Google Scholar 

  25. R.L. Heckaman, J. Sullivan, Rendering digital cinema and broadcast TV content to wide gamut display media. SID Symp. Dig. Tech. Pap. 42(1), 225–228 (2011)

    Article  Google Scholar 

  26. P.G. Herzog, M. Müller, Gamut mapping using an analytical color gamut representation, in Proceedings of Color Imaging: Device-Independent Color, Color Hard Copy, and Graphic Arts (1997), pp. 117–128

    Google Scholar 

  27. T. Hoshino, A preferred color reproduction method for the HDTV digital still image system, in Proceedings of IS&T Symposium on Electronic Photography (1991), pp. 27–32

    Google Scholar 

  28. T. Hoshino, Color estimation method for expanding a color image for reproduction in a different color gamut, May 1994. US Patent 5,317,426

    Google Scholar 

  29. ITU-R Recommendation BT.709-5, Parameter values for the HDTV standards for production and international programme exchange (2002)

    Google Scholar 

  30. ITU-R Recommendation BT.2020, Parameter values for ultra high definition television systems for production and international programme exchange (2012)

    Google Scholar 

  31. A.J. Johnson, Perceptual requirements of digital picture processing. Paper Presented at IARAIGAI Symposium and Printed in Part in Printing World (1979)

    Google Scholar 

  32. B.H. Kang, J. Morovič, M.R. Luo, M.S. Cho, Gamut compression and extension algorithms based on observer experimental data. ETRI J. 25(3), 156–170 (2003)

    Article  Google Scholar 

  33. N. Katoh, M. Ito, Gamut mapping for computer generated images (ii), in Proceedings of 4th IS&T/SID Color Imaging Conference (1996), pp. 126–129

    Google Scholar 

  34. G. Kennel, Color and Mastering for Digital Cinema: Digital Cinema Industry Handbook Series (Taylor & Francis, New York, 2007)

    Book  Google Scholar 

  35. M.C. Kim, Y.C. Shin, Y.R. Song, S.J. Lee, I.D. Kim, Wide gamut multi-primary display for HDTV, in Proceedings of 2nd European Conference on color Graphics, Imaging and Vision (2004), pp. 248–253

    Google Scholar 

  36. R. Kimmel, D. Shaked, M. Elad, I. Sobel, Space-dependent color gamut mapping: a variational approach. IEEE Trans. Image Process. 14, 796–803 (2005)

    Article  Google Scholar 

  37. Kodak, http://r0k.us/graphics/kodak/ (1993)

  38. Y. Kusakabe, Y. Iwasaki, Y. Nishida, Wide-color-gamut super hi-vision projector, in Proceedings ITE Annual Convention (in Japanese) (2013)

    Google Scholar 

  39. J. Laird, R. Muijs, J. Kuang, Development and evaluation of gamut extension algorithms. Color Res. Appl. 34(6), 443–451 (2009)

    Article  Google Scholar 

  40. C. Lau, W. Heidrich, R. Mantiuk, Cluster-based color space optimizations, in Proceedings of IEEE International Conference on Computer Vision, ICCV ’11 (2011), pp. 1172–1179

    Google Scholar 

  41. Y. Li, G. Song, H. Li, A multilevel gamut extension method for wide gamut displays, in Proceedings of International Conference on Electric Information and Control Engineering (ICEICE) (2011), pp. 1035–1038

    Google Scholar 

  42. Y. Ling, Investigation of a gamut extension algorithm. Master’s thesis, University of Derby, Derby, 2001

    Google Scholar 

  43. I. Lissner, J. Preiss, P. Urban, M.S. Lichtenauer, P. Zolliker, Image-difference prediction: from grayscale to color. IEEE Trans. Image Process. 22(2), 435–446 (2013)

    Article  MathSciNet  Google Scholar 

  44. Y. Liu, G. Song, H. Li, A hue-preserving gamut expansion algorithm in CIELUV color space for wide gamut displays, in Proceedings of the 3rd International Congress on Image and Signal Processing (CISP) (2010), pp. 2401–2404

    Google Scholar 

  45. M.R. Luo, G. Cui, B. Rigg, The development of the CIE 2000 colour-difference formula: CIEDE2000. Color Res. Appl. 26(5), 340–350 (2001)

    Article  Google Scholar 

  46. G. Marcu, S. Abe, Gamut mapping for color simulation on CRT devices, in Proceedings of Color Imaging: Device-Independent Color, Color Hard Copy, and Graphic Arts (1996)

    Google Scholar 

  47. K. Masaoka, Y. Kusakabe, T. Yamashita, Y. Nishida, T. Ikeda, M. Sugawara, Algorithm design for gamut mapping from UHDTV to HDTV. J. Disp. Technol. 12(7), 760–769 (2016)

    Article  Google Scholar 

  48. J.J. McCann, Lessons learned from mondrians applied to real images and color gamuts, in Proceedings of Color Imaging Conference (1999), pp. 1–8

    Google Scholar 

  49. J.J. McCann, A spatial colour gamut calculation to optimize colour appearance, in Colour Image Science: Exploiting Digital Media (2002), pp. 213–233

    Google Scholar 

  50. X. Meng, G. Song, H. Li, A human skin-color-preserving extension algorithm for wide gamut displays, in Proceedings of International Conference on Information Technology and Software Engineering. Lecture Notes in Electrical Engineering (Springer, Berlin, 2013), pp. 705–713

    Google Scholar 

  51. J. Meyer, B. Barth, Color gamut matching for hard copy, in Proceedings of SID Digest (1989), pp. 86–89

    Google Scholar 

  52. E.D. Montag, M.D. Fairchild, Psychophysical evaluation of gamut mapping techniques using simple rendered images and artificial gamut boundaries. IEEE Trans. Image Process. 6(7), 977–989 (1997)

    Article  Google Scholar 

  53. J. Morovič, To develop a universal Gamut mapping algorithm. Ph.D. thesis, University of Derby, Derby, 1998

    Google Scholar 

  54. J. Morovič, Color Gamut Mapping, vol. 10 (Wiley, Chichester, 2008)

    Book  Google Scholar 

  55. J. Morovič, Y. Wang, A multi-resolution, full-colour spatial gamut mapping algorithm, in Proceedings of Color Imaging Conference (2003), pp. 282–287

    Google Scholar 

  56. R. Muijs, J. Laird, J. Kuang, S. Swinkels, Subjective evaluation of gamut extension methods for wide-gamut displays, in Proceedings of the 13th International Display Workshop (2006), pp. 1429–1432

    Google Scholar 

  57. G.M. Murch, J.M. Taylor, Color in computer graphics: manipulating and matching color, in Eurographics Seminar: Advances in Computer Graphics V (1989), pp. 41–47

    Google Scholar 

  58. S. Nakauchi, S. Hatanaka, S. Usui, Color gamut mapping based on a perceptual image difference measure. Color Res. Appl. 24(4), 280–291 (1999)

    Article  Google Scholar 

  59. H. Pan, S. Daly, A gamut-mapping algorithm with separate skin and non-skin color preference controls for wide-color-gamut TV. SID Symp. Dig. Tech. Pap. 39(1), 1363–1366 (2008)

    Article  Google Scholar 

  60. M.R. Pointer, The gamut of real surface colours. Color Res. Appl. 5(3), 145–155 (1980)

    Article  Google Scholar 

  61. C. Poynton, Contrast, brightness, and the naming of things. Poynton’s Vector 1 (2010)

    Google Scholar 

  62. J. Preiss, P. Urban, Image-difference measure optimized gamut mapping, in Proceedings of IS&T/SID 20th Color Imaging Conference (2012), pp. 230–235

    Google Scholar 

  63. J. Preiss, F. Fernandes, P. Urban, Color-image quality assessment: from prediction to optimization. IEEE Trans. Image Process. 23(3), 1366–1378 (2014)

    Article  MathSciNet  Google Scholar 

  64. S. Roth, I. Ben-David, M. Ben-Chorin, D. Eliav, O. Ben-David, Wide gamut, high brightness multiple primaries single panel projection displays. SID Symp. Dig. Tech. Pap. 34(1), 118–121 (2003)

    Article  Google Scholar 

  65. J.J. Sara, The automated reproduction of pictures with nonreproducible colors. Ph.D. thesis, Massachusetts Institute of Technology, Cambridge, 1984

    Google Scholar 

  66. F. Schweiger, T. Borer, M. Pindoria, Luminance-preserving colour conversion, in SMPTE Annual Technical Conference and Exhibition (2016), pp. 1–9

    Google Scholar 

  67. B.D. Silverstein, A.F. Kurtz, J.R. Bietry, G.E. Nothhard, A laser-based digital cinema projector. SID Symp. Dig. Tech. Pap. 42(1), 326–329 (2011)

    Article  Google Scholar 

  68. SMPTE RP 431-2:2011, D-cinema quality – reference projector and environment (2011)

    Google Scholar 

  69. G. Song, H. Cao, H. Huang, Hue preserving multi-level expansion method based on saturation for wide gamut displays. J. Inf. Comput. Sci. 11(2), 461–472 (2014)

    Article  Google Scholar 

  70. G. Song, X. Meng, H. Li, Y. Han, Skin color region protect algorithm for color gamut extension. J. Inf. Comput. Sci. 11(6), 1909–1916 (2014)

    Article  Google Scholar 

  71. J.M. Taylor, G.M. Murch, P. McManus, Tektronix HVC: a uniform perceptual color system for display users, in SID Symposium Digest of Technical Papers (1989)

    Google Scholar 

  72. W.S. Torgerson, A law of categorical judgment, consumer behaviour, in Consumer Behaviour (New York University Press, New York, 1954), pp. 92–93

    Google Scholar 

  73. S. Ueki, K. Nakamura, Y. Yoshida, T. Mori, K. Tomizawa, Y. Narutaki, Y. Itoh, K. Okamoto, Five-primary-color 60-inch LCD with novel wide color gamut and wide viewing angle. SID Symp. Dig. Tech. Pap. 40(1), 927–930 (2009)

    Article  Google Scholar 

  74. UGRA, UGRA GAMCOM version 1.1: Program for the color gamut compression and for the comparison of calculated and measured values. Technical report, UGRA, St. Gallen, 17 July 1995

    Google Scholar 

  75. Y.-C. Yang, K. Song, S.G. Rho, N.-S. Rho, S.J. Hong, K.B. Deul, M. Hong, K. Chung, W.H. Choe, S. Lee, C.Y. Kim, S.-H. Lee, H.-R. Kim, Development of six primary-color LCD. SID Symp. Dig. Tech. Pap. 36(1), 1210–1213 (2005)

    Article  Google Scholar 

  76. S. W. Zamir, J. Vazquez-Corral, M. Bertalmío, Gamut mapping in cinematography through perceptually-based contrast modification. IEEE J. Sel. Top. Sign. Process. 8(3), 490–503 (2014)

    Article  Google Scholar 

  77. S.W. Zamir, J. Vazquez-Corral, M. Bertalmío, Gamut extension for cinema: psychophysical evaluation of the state of the art, and a new algorithm, in Proceedings of IS&T/SPIE Electronic Imaging (2015), pp. 1–12

    Google Scholar 

  78. S.W. Zamir, J. Vazquez-Corral, M. Bertalmío, Perceptually-based gamut extension algorithm for emerging wide color gamut display and projection technologies, in SMPTE Annual Technical Conference and Exhibition (2016), pp. 1–11

    Google Scholar 

  79. S.W. Zamir, J. Vazquez-Corral, M. Bertalmío, Gamut extension for cinema. IEEE Trans. Image Process. 26(4), 1595–1606 (2017)

    Article  MathSciNet  Google Scholar 

  80. S.W. Zamir, J. Vazquez-Corral, M. Bertalmío, Gamut reduction through local saturation reduction, in Color and Imaging Conference (2017), pp. 214–218

    Google Scholar 

  81. P. Zolliker, K. Simon, Retaining local image information in gamut mapping algorithms. IEEE Trans. Image Process. 16(3), 664–672 (2007)

    Article  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain

    Syed Waqas Zamir, Javier Vazquez-Corral & Marcelo Bertalmío

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  1. Syed Waqas Zamir
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  2. Javier Vazquez-Corral
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  3. Marcelo Bertalmío
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Correspondence to Syed Waqas Zamir .

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Editors and Affiliations

  1. Department of Mathematics, University of Bergen, Bergen, Norway

    Xue-Cheng Tai

  2. Norwegian Defence Research Establishment, Kjeller, Norway

    Egil Bae

  3. University of South-Eastern Norway, Porsgrunn, Norway

    Marius Lysaker

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Zamir, S.W., Vazquez-Corral, J., Bertalmío, M. (2018). Variational Methods for Gamut Mapping in Cinema and Television. In: Tai, XC., Bae, E., Lysaker, M. (eds) Imaging, Vision and Learning Based on Optimization and PDEs. IVLOPDE 2016. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-91274-5_4

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