Shida Beigpour, Christian Riess, Joost van de Weijer and Elli Angelopoulou recently published a paper, “Multi-Illuminant Estimation with Conditional Random Fields” in IEEE Transactions on Image Processing (TIP), 23(1), 2014, pages 83-95, in which they introduced a novel two-illuminant color constancy benchmark data set with ground truth. The images are available here and the original high resolution raw data from the camera (.X3F format) are available upon request. More information about the data set can be found at the project website.

We updated the page with Yet Another Color Constancy database (Updated)! This set of images is released by the Eidomatics Laboratory of the Department of Computer Science of the Università degli Studi di Milano (Italy), and contains both low dynamic range (LDR) and high dynamic range (HDR) images. More information on this data set can be found here.

We updated the page with new results! Nikola Banić and Sven Lončarić shared the results of their method described in their 2015 paper published in Signal Processing Letters. “Color Cat: Remembering Colors for Illumination Estimation” is incorporated in our section results-per-method and results-per-dataset.

We updated the site with a new data set! The images used in the 2012 TIP-paper “Color Constancy for Multiple Light Sources” by Gijsenij, Lu and Gevers are (finally) made available to the public. Please only use with the proper citations! The data set can be found here, and is provided as is.

We updated the page with new results! Hamid Reza Vaezi Joze and Mark Drew shared the results of their method described in their 2012 BMVC and 2013 TPAMI-follow-up papers. “Exemplar-Based Colour Constancy and Multiple Illumination” is incorporated in our sections results-per-method and results-per-dataset.

We updated the page with new source-code! Mehdi Rezagholizadeh and James J. Clark were kind enough to make their source-code available to the community through this website. The publication related to the software was presented at the the International Conference on Computer and Robot Vision (CRV) in 2013, and is titled “Edge-Based and Efficient Chromaticity Spatio-spectral Models for Color Constancy”. The source-code can be found here.

We updated the page with new results and source-code! Joost van de Weijer put some effort into making the source-code of our TPAMI-paper titled Improving Color Constancy by Photometric Edge Weighting suited for publication on-line. The source-code of the Weighted Grey-Edge can be found here. Moreover, the results as reported in the paper are also made available in our sections results-per-method and results-per-dataset.

We updated the page with new results! Simone Bianco et al. were so kind to share their results of their 2010 Pattern Recognition paper titled “Automatic color constancy algorithm selection and combination”. These results are incorporated in our sections results-per-method and results-per-dataset. They also recomputed the ground truth of the reprocessed version of the Color-checker data set and made these available together with their results on this data set.

We updated the page with new results! Ayan Chakrabarti et al. recently had a paper accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence (click here for the corresponding research-page and preprint) and were so kind to share their results. These results are incorporated in our sections results-per-method and results-per-dataset. A full overview of their findings can be found here.

Publications affiliated with this website

• R. Zakizadeh, M. Brown and G. Finlayson, “A Hybrid Strategy for Illuminant Estimation Targeting Hard Images”, International Conference on Computer Vision Workshop 2015, page 49-56, 2015.
• A. Gijsenij, Th. Gevers and J. van de Weijer, “Computational Color Constancy: Survey and Experiments”, IEEE Transactions on Image Processing, Volume 20 (9), page 2475-2489, 2011.
• A. Gijsenij and Th. Gevers, “Color Constancy using Natural Image Statistics and Scene Semantics”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 33 (4), page 687-698, 2011.
• A. Gijsenij, Th. Gevers and J. van de Weijer, “Improving Color Constancy by Photometric Edge Weighting”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Accepted, 2011.
• A. Gijsenij, R. Lui and Th. Gevers, “Color Constancy for Multiple Light Sources”, IEEE Transactions on Image Processing, Accepted, 2011.

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.