TY - GEN
T1 - Colour by correlation in a three-dimensional colour space
AU - Barnard, Kobus
AU - Martin, Lindsay
AU - Funt, Brian
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2000.
PY - 2000
Y1 - 2000
N2 - We improve the promising Colour by Correlation method for computational colour constancy by modifying it to work in a three dimensional colour space. The previous version of the algorithm uses only the chromaticity of the input, and thus cannot make use of the information inherent in the pixel brightness which previous work suggests is useful. We develop the algorithm for the Mondrian world (matte surfaces), the Mondrian world with fluorescent surfaces, and the Mondrian world with specularities. We test the new algorithm on synthetic data, and on a data set of 321 carefully calibrated images. We find that on the synthetic data, the new algorithm significantly out-performs all other colour constancy algorithms. In the case of image data, the results are also promising. The new algorithm does significantly better than its chromaticity counter-part, and its performance approaches that of the best algorithms. Since the research into the method is still young, we are hopeful that the performance gap between the real and synthetic case can be narrowed.
AB - We improve the promising Colour by Correlation method for computational colour constancy by modifying it to work in a three dimensional colour space. The previous version of the algorithm uses only the chromaticity of the input, and thus cannot make use of the information inherent in the pixel brightness which previous work suggests is useful. We develop the algorithm for the Mondrian world (matte surfaces), the Mondrian world with fluorescent surfaces, and the Mondrian world with specularities. We test the new algorithm on synthetic data, and on a data set of 321 carefully calibrated images. We find that on the synthetic data, the new algorithm significantly out-performs all other colour constancy algorithms. In the case of image data, the results are also promising. The new algorithm does significantly better than its chromaticity counter-part, and its performance approaches that of the best algorithms. Since the research into the method is still young, we are hopeful that the performance gap between the real and synthetic case can be narrowed.
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U2 - 10.1007/3-540-45054-8_25
DO - 10.1007/3-540-45054-8_25
M3 - Conference contribution
AN - SCOPUS:84944226346
SN - 3540676856
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 375
EP - 389
BT - Computer Vision - ECCV 2000 - 6th European Conference on Computer Vision, Proceedings
A2 - Vernon, David
PB - Springer-Verlag
T2 - 6th European Conference on Computer Vision, ECCV 2000
Y2 - 26 June 2000 through 1 July 2000
ER -