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Some recent publications on Color Constancy (requested)

  • Articles appearing in Google Scholar (since 2017)
  • Shao-Bing Gao, Ming Zhang, Chao-Yi Li, and Yong-Jie Li, “Improving color constancy by discounting the variation of camera spectral sensitivity”, Journal of the Optical Society of America A: 34(8) (2017), pp. 1448-1462.
  • N. Banic and S. Loncaric, “Color Cat: Remembering Colors for Illumination Estimation”, Signal Processing Letters: 22(6) (2015), pp 651-655.
  • Nikola Banic and Sven Loncaric, “Improving the White patch method by subsampling”, in IEEE International Conference on Image Processing (ICIP), 2014. The project website, including source-code, can be found here.
  • Nikola Banic and Sven Loncaric, “Color Rabbit: Guiding the Distance of Local Maximums in Illumination Estimation”, in IEEE International Conference on Digital Signal Processing (DSP), 2014. The project website, including source-code, can be found here.
  • Nikola Banic and Sven Loncaric, “Using the Random Sprays Retinex algorithm for global illumination estimation”, Proceedings of the Croatian Computer Vision Workshop, 2013. The project website, including source-code, can be found here.
  • M. Rezagholizadeh and J.J. Clark, “Edge-Based and Efficient Chromaticity Spatio-spectral Models for Color Constancy”, in International Conference on Computer and Robot Vision (CRV), 2013.
  • Wan Mohd Yaakob Wan Bejuri, Mohd Murtadha Mohamad, Maimunah Sapri and Mohd Adly Rosly, “Ubiquitous WLAN/Camera Positioning using Inverse Intensity Chromaticity Space-based Feature Detection and Matching: A Preliminary Result”, International Conference on Man-Machine Systems (ICOMMS 2012), 2012.
  • Wan Mohd Yaakob Wan Bejuri, Mohd Murtadha Mohamad, Maimunah Sapri and Mohd Adly Rosly, “Investigation of Color Constancy for Ubiquitous Wireless LAN/Camera Positioning: An Initial Outcome”, International Journal of Advancements in Computing Technology, vol. 4, no. 7, pp. 269-280, 2012.
  • S. Bianco and R. Schettini, “Color Constancy Using Faces”, in IEEE Conference on Computer Vision and Pattern Recognition, 2012.
  • A. Chakrabarti, K. Hirakawa and T. Zickler, “Color Constancy with Spatio-spectral Statistics”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Accepted, 2011 (Preprint).
  • S. Bianco, G. Ciocca, C. Cusano, and R. Schettini, “Automatic color constancy algorithm selection and combination”, Pattern Recognition, vol. 43, no. 3, pp. 695–705, 2010.
  • B. Funt and L. Shi, “The rehabilitation of maxrgb”, in IS\&T/SID’s Color Imaging Conference, 2010.
  • B. Funt and L. Shi, “The effect of exposure on maxrgb color constancy”, in Proc. SPIE, vol. 7527 Human Vision and Electronic Imaging XV, 2010.
  • A. Gijsenij, T. Gevers, and J. van de Weijer, “Generalized gamut mapping using image derivative structures for color constancy”, International Journal of Computer Vision, vol. 86, no. 1–2, pp. 127–139, 2010.
  • B. Li, D. Xu, W. Xiong, and S. Feng, “Color constancy using achromatic surface”, Color Research and Application, vol. 35, no. 4, pp. 304-312, 2010.
  • M. Mosny and B. Funt, “Cubical gamut mapping colour constancy”, in IS\&T’s European Conference on Color in Graphics, Imaging and Vision, 2010.
  • M. Wu, J. Sun, J. Zhou, and G. Xue, “Color constancy based on texture pyramid matching and regularized local regression”, Journal of the Optical Society of America A, vol. 27, no. 10, pp. 2097–2105, 2010.