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A Perception-based Color Correction Method for Multi-view Images

  • Shao, Feng (Faculty of Information Science and Engineering, Ningbo University) ;
  • Jiang, Gangyi (Faculty of Information Science and Engineering, Ningbo University) ;
  • Yu, Mei (Faculty of Information Science and Engineering, Ningbo University) ;
  • Peng, Zongju (Faculty of Information Science and Engineering, Ningbo University)
  • Received : 2010.11.14
  • Accepted : 2011.01.18
  • Published : 2011.02.28

Abstract

Three-dimensional (3D) video technologies are becoming increasingly popular, as it can provide users with high quality and immersive experiences. However, color inconsistency between the camera views is an urgent problem to be solved in multi-view imaging. In this paper, a perception-based color correction method for multi-view images is proposed. In the proposed method, human visual sensitivity (VS) and visual attention (VA) models are incorporated into the correction process. Firstly, the VS property is used to reduce the computational complexity by removing these visual insensitive regions. Secondly, the VA property is used to improve the perceptual quality of local VA regions by performing VA-dependent color correction. Experimental results show that compared with other color correction methods, the proposed method can greatly promote the perceptual quality of local VA regions greatly and reduce the computational complexity, and obtain higher coding performance.

Keywords

References

  1. Y. Morvan, D. Farin and P. H. N. de With, "System architecture for free-viewpoint video and 3D-TV," IEEE Transactions on Consumer Electronics, vol. 54, no. 2, pp. 925-932, 2008. https://doi.org/10.1109/TCE.2008.4560180
  2. A. Kubota, A. Smolic, M. Magnor, M. Tanimoto, T. Chen and C. Zhang, "Multiview imaging and 3DTV," IEEE Signal Processing Magazine, vol. 24, no. 6, pp. 10-21, 2007.
  3. P. Merkle, A. Smolic, K. Muller and T. Wiegand, "Efficient prediction structures for multiview video coding," IEEE Transactions on Circuits and Systems for Video Technology, vol. 17, no. 11, pp. 1461-1473, 2007. https://doi.org/10.1109/TCSVT.2007.903665
  4. K. Muller, A. Smolic, K. Dix, P. Merkle, P. Kauff and T. Wiegand, "View synthesis for advanced 3D video system," EURASIP Journal on Image and Video Processing, vol. 2008, Article ID 438148, 11 pages, 2008.
  5. S. H. Lee and J. H. Choi, "Design and implementation of color correction system for images captured by digital camera," IEEE Transactions on Consumer Electronics, vol. 54, no. 2, pp. 268-276, 2008. https://doi.org/10.1109/TCE.2008.4560085
  6. K. Yamamoto, M. Kitahara, H. Kimata, T. Yendo, T. Fujii, M. Tanimoto, S. Shimizu, K. Kamikura and Y. Yashima, "Multiview video coding using view interpolation and color correction," IEEE Transactions on Circuits and Systems for Video Technology, vol. 17, no. 11, pp. 1436-1449, 2007. https://doi.org/10.1109/TCSVT.2007.903802
  7. Y. Chen, J. Chen and C. Cai, "Luminance and chrominance correction for multi-view video using simplified color error model," in Proc. of Picture Coding Symposium, Beijing, China, April 2006.
  8. U. Fecker, M. Markowsky and A. Kaup, "Histogram-based pre-filtering for luminance and chrominance compensation of multi-view video," IEEE Transactions on Circuits and Systems for Video Technology, vol. 18, no. 9, pp. 1258-1267, 2008. https://doi.org/10.1109/TCSVT.2008.926997
  9. F. Shao, G. Jiang and M. Yu, "Multi-view video color correction using dynamic programming," Journal of System Engineering and Electronics, vol. 19, no. 6, pp. 1115-1120, 2008. https://doi.org/10.1016/S1004-4132(08)60206-6
  10. Z. Lu, W. lin, X. Yang, E. Ong and S. Yao, "Modelling visual attention's modulatory aftereffects on visual sensitivity and quality evaluation," IEEE Transactions on Image Processing, vol. 14, no. 11, pp. 1928-1942, 2005. https://doi.org/10.1109/TIP.2005.854478
  11. X. Yang, W. Lin, Z. Lu, E. Ong and S. Yao, "Motion-compensated residue preprocessing in video coding based on just-noticeable-distortion profile," IEEE Transactions on Circuits and Systems for Video Technology, vol. 15, no. 6, pp. 742-751, 2005. https://doi.org/10.1109/TCSVT.2005.848313
  12. K. Barnard, V. Cardei and B. Funt, "A comparison of computational color constancy algorithms - Part 1: methodology and experiments with synthesized data," IEEE Transactions on Image Processing, vol. 11, no. 9, pp. 972-983, 2002. https://doi.org/10.1109/TIP.2002.802531
  13. A. Rizzi and C. Gatta, "From retinex to automatic color equalization: issues in developing a new algorithm for unsupervised color equalization," Journal of Electronics Imaging, vol. 13, no. 1, pp. 75-84, 2004. https://doi.org/10.1117/1.1635366
  14. M. Bertalmio, V. Caselles, E. Provenzi and A. Rizzi, "Perceptual Color correction through variational techniques," IEEE Transactions on Image Processing, vol. 16, no. 4, pp. 1058-1072, 2007. https://doi.org/10.1109/TIP.2007.891777
  15. R. Palma-Amestoy, E. Provenzi, M. Bertalmio and V. Caselles, "A perceptually inspired variational framework for color enhancement," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 3, pp. 458-474, March 2009. https://doi.org/10.1109/TPAMI.2008.86
  16. F. W. M. Stentiford and A. Bamidele, "Attention-based colour correction," in Proc. of the SPIE, vol. 6057, pp. 158-167, 2006.
  17. ISO/IEC JTC1/SC29/WG11, "Available Technologies for FTV," Doc. M15088, Antalya, Turkey, January 2008.
  18. T. Lanrence and A. Brian, "Color constancy: A method for recovering surface spectral reflectance," Journal of Optical Society of America(A), vol. 3, no. 1, pp. 29-33, 1986. https://doi.org/10.1364/JOSAA.3.000029
  19. F. Shao, G. Jiang, M. Yu and Y. Ho, "Fast color correction for multi-view video by modeling spatio-temporal variation," Journal of Visual Communication and Image Representation, vol. 21, no. 5-6, pp. 392-403, 2010. https://doi.org/10.1016/j.jvcir.2010.03.001
  20. F. Shao, G. Jiang, M. Yu and Y. Ho, "Highlight-detection-based color correction method for multi-view images," ETRI Journal, vol. 31, no. 4, pp. 448-450, 2009. https://doi.org/10.4218/etrij.09.0209.0003
  21. Y. Zhang, G. Jiang, M. Yu, Y. Yang, Z. Peng and K. Chen, "Depth perceptual region-of-interest based multiview video coding," Journal of Visual Communication and Image Representation, vol. 21, no. 5-6, pp. 498-512, 2010. https://doi.org/10.1016/j.jvcir.2010.03.002
  22. J. Lubin, M. Brill and R. Crane, "Vision model-based assessment of distortion magnitudes in digital video," Available: http://www.mpeg.org/MPEG/JND.
  23. R. Achanta, S. Hemami, F. Estrada and S. Süsstrunk, "Frequency-tuned salient region detection," in Proc. of International Conference on Computer Vision and Pattern Recognition, Miami, U.S.A., 2009.
  24. J. Hur, S. Cho and Y. Lee, "Adaptive local illumination change compensation method for H.264/AVC-based multiview video coding," IEEE Transactions on Circuits and Systems for Video Technology, vol. 17, no. 11, pp. 1496-1505, 2007. https://doi.org/10.1109/TCSVT.2007.903774
  25. ISO/IEC JTC1/SC29/WG11, "KDDI multi-view video sequences for MPEG 3DAV use," Doc. M10533, Munich, Germany, 2004.
  26. ISO/IEC JTC1/SC29/WG11, "Joint multiview video model (JMVM) 7.0," JVT-Z207, Antalya, Turkey, Jan. 2008.