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Intelligent Transfer of Thematic Harmonic Color Palettes
Michel Alves dos Santos ∗
January, 2014
Abstract
This theme has as main objective to introduce a method of "smart"
transfer of harmonic color palettes based on a particular theme or color
expression model. The "smart" part would be shaped by the retention ca-
pability information of the original input image, ie, the number of percep-
tible colors must not be changed beyond be combined with other existing
color model. The "thematic" part would be for the account of a research
core of palettes that would read a certain base of images and would ex-
tract the n best ranked palettes in the base.
Keywords: color transfer, color space, progressive transfer, visual per-
ception, scene content analysis, pattern clustering, cluster recognition,
color similarity, colormap clustering, intelligent system design, natural
color transfer methods, objective evaluation parameter, colour grading,
transforms, recoloring, local color information, histogram analysis, cor-
relation, image colour analysis, image processing, mathematical models,
color harmony, harmonic template, harmonic analysis, signal processing,
visual artifact, segmentation, human visual system.
∗Michel Alves dos Santos - Alves, M. - malves@cos.ufrj.br - http://www.michelalves.com. MSc. Candidate in
Computer Graphics, Image Processing and Computer Vision. http://www.lcg.ufrj.br - Laboratory of Computer
Graphics - LCG. Graduate Program in Systems Engineering and Computing (PESC). Alberto Luiz Coimbra In-
stitute for Graduate Studies and Research in Engineering - COPPE. Federal University of Rio de Janeiro (UFRJ -
http://www.ufrj.br), Brazil - Rio de Janeiro/RJ, Phone: (21) 8204-7102.
1
Bibliography: Intelligent Transfer of Thematic Harmonic Color Palettes
Michel Alves dos Santos
January, 2014
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1

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Intelligent Transfer of Thematic Harmonic Color Palettes

  • 1. Intelligent Transfer of Thematic Harmonic Color Palettes Michel Alves dos Santos ∗ January, 2014 Abstract This theme has as main objective to introduce a method of "smart" transfer of harmonic color palettes based on a particular theme or color expression model. The "smart" part would be shaped by the retention ca- pability information of the original input image, ie, the number of percep- tible colors must not be changed beyond be combined with other existing color model. The "thematic" part would be for the account of a research core of palettes that would read a certain base of images and would ex- tract the n best ranked palettes in the base. Keywords: color transfer, color space, progressive transfer, visual per- ception, scene content analysis, pattern clustering, cluster recognition, color similarity, colormap clustering, intelligent system design, natural color transfer methods, objective evaluation parameter, colour grading, transforms, recoloring, local color information, histogram analysis, cor- relation, image colour analysis, image processing, mathematical models, color harmony, harmonic template, harmonic analysis, signal processing, visual artifact, segmentation, human visual system. ∗Michel Alves dos Santos - Alves, M. - malves@cos.ufrj.br - http://www.michelalves.com. MSc. Candidate in Computer Graphics, Image Processing and Computer Vision. http://www.lcg.ufrj.br - Laboratory of Computer Graphics - LCG. Graduate Program in Systems Engineering and Computing (PESC). Alberto Luiz Coimbra In- stitute for Graduate Studies and Research in Engineering - COPPE. Federal University of Rio de Janeiro (UFRJ - http://www.ufrj.br), Brazil - Rio de Janeiro/RJ, Phone: (21) 8204-7102. 1
  • 2. Bibliography: Intelligent Transfer of Thematic Harmonic Color Palettes Michel Alves dos Santos January, 2014 References Chang, Y., Saito, S. & Nakajima, M. (2002), Color transfor- mation based on the basic color categories of a painting, in ‘ACM SIGGRAPH 2002 Conference Abstracts and Ap- plications’, ACM, New York, NY, USA, pp. 157–157. Chang, Y., Saito, S., Uchikawa, K. & Nakajima, M. (2005), ‘Example-based color stylization of images’, ACM Trans. Appl. Percept. 2(3), 322–345. Chang, Y., Uchikawa, K. & Saito, S. (2004), Example-based color stylization based on categorical perception, in ‘Pro- ceedings of the 1st Symposium on Applied Perception in Graphics and Visualization’, ACM, New York, NY, USA, pp. 91–98. Cohen-Or, D., Sorkine, O., Gal, R., Leyvand, T. & Xu, Y.-Q. (2006), Color harmonization, in ‘ACM SIGGRAPH 2006 Papers’, SIGGRAPH ’06, ACM, New York, NY, USA, pp. 624–630. URL http://doi.acm.org/10.1145/ 1179352.1141933. Gonzales, R. C. & Wintz, P. (1987), Digital Image Processing (2Nd Ed.), Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA. Gooch, A. A., Olsen, S. C., Tumblin, J. & Gooch, B. (2005), Color2gray: Salience preserving color removal, in ‘ACM SIGGRAPH 2005 Papers’, SIGGRAPH ’05, ACM, New York, NY, USA, pp. 634–639. Greenfield, G. R. & House, D. H. (2003), Image recoloring induced by palette color associations., in ‘WSCG’. Greenfield, G. R. & House, D. H. (2005), A palette driven approach to image color transfer, in ‘Proceedings of the First Eurographics Conference on Computational Aesthe- tics in Graphics, Visualization and Imaging’, Computa- tional Aesthetics’05, Eurographics Association, Aire-la- Ville, Switzerland, Switzerland, pp. 91–99. Huang, H., Zang, Y. & Li, C.-F. (2010), ‘Example-based pain- ting guided by color features’, The Visual Computer 26(6- 8), 933–942. Levin, A., Lischinski, D. & Weiss, Y. (2004), ‘Colorization using optimization’, ACM Trans. Graph. 23(3), 689–694. Li, C. (2010), ‘Example-based painting guided by color fea- tures’, The Visual Computer. Nguyen, C. H., Ritschel, T., Myszkowski, K., Eisemann, E. & Seidel, H.-P. (2012), ‘3d material style transfer’, Computer Graphics Forum (Proc. EUROGRAPHICS 2012). Pérez, P., Gangnet, M. & Blake, A. (2003), ‘Poisson image editing’, ACM Trans. Graph. 22(3), 313–318. URL http: //doi.acm.org/10.1145/882262.882269. Pouli, T. & Reinhard, E. (2011), ‘Progressive color trans- fer for images of arbitrary dynamic range’, Computers & Graphics 35(1), 67–80. Reinhard, E. & Pouli, T. (2011), Colour spaces for colour transfer, in ‘Proceedings of the Third International Confe- rence on Computational Color Imaging’, Springer-Verlag, Berlin, Heidelberg, pp. 1–15. Reinhard, E., Ashikhmin, M., Gooch, B. & Shirley, P. (2001), ‘Color transfer between images’, IEEE Comput. Graph. Appl. 21(5), 34–41. Shinagawa, Y. & Kunii, T. L. (1998), ‘Unconstrained au- tomatic image matching using multiresolutional critical- point filters’, IEEE Trans. Pattern Anal. Mach. Intell. 20(9), 994–1010. URL http://dx.doi.org/10.1109/34. 713364. Suganuma, K., Sugita, J. & Takahashi, T. (2008), Coloriza- tion using harmonic templates, in ‘ACM SIGGRAPH 2008 posters’, SIGGRAPH ’08, New York, USA, pp. 62:1–62:1. Wang, B., Yu, Y. & Xu, Y.-Q. (2011), Example-based image color and tone style enhancement, in ‘ACM SIGGRAPH 2011 Papers’, SIGGRAPH ’11, ACM, New York, NY, USA, pp. 64:1–64:12. URL http://doi.acm.org/10.1145/ 1964921.1964959. Wang, B., Yu, Y., Wong, T.-T., Chen, C. & Xu, Y.-Q. (2010), ‘Data-driven image color theme enhancement’, ACM Transactions on Graphics (SIGGRAPH Asia 2010 issue) 29(6), 146:1–146:10. Wang, C.-M. & Huang, Y.-H. (2004), ‘A novel color trans- fer algorithm for image sequences.’, J. Inf. Sci. Eng. 20(6), 1039–1056. URL http://dblp.uni-trier.de/db/ journals/jise/jise20.html#WangH04. Welsh, T., Ashikhmin, M. & Mueller, K. (2002), ‘Transferring color to greyscale images’, ACM Trans. Graph. 21(3), 277– 280. Xiao, X. & Ma, L. (2006), Color transfer in correlated co- lor space, in ‘Proceedings of the 2006 ACM International Conference on Virtual Reality Continuum and Its Appli- cations’, ACM, New York, NY, USA, pp. 305–309. Yang, C. K. & Peng, L.-K. (2008), ‘Automatic mood trans- ferring between color images’, IEEE Comput. Graph. Appl. 28(2), 52–61. 1