Color Dog: Guiding the Global Illumination Estimation to Better Accuracy (CROSBI ID 622544)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Banić, Nikola ; Lončarić, Sven
engleski
Color Dog: Guiding the Global Illumination Estimation to Better Accuracy
An important part of image enhancement is color constancy, which aims to make image colors invariant to illumination. In this paper the Color Dog (CD), a new learning-based global color constancy method is proposed. Instead of providing one, it corrects the other methods' illumination estimations by reducing their scattering in the chromaticity space by using a its previously learning partition. The proposed method outperforms all other methods on most high-quality benchmark datasets. The results are presented and discussed.
clustering ; color constancy ; illumination estimation ; image enhancement ; white balancing
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Podaci o prilogu
129-135.
2015.
objavljeno
Podaci o matičnoj publikaciji
VISAPP 2015: Proceedings of the 10th International Conference on Computer Vision Theory and Applications - (Volume 1)
Braz, José ; Battiato, Sebastiano ; Imai, Francisco
Scitepress
978-989-758-089-5
Podaci o skupu
10th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
poster
11.03.2015-14.03.2015
Berlin, Njemačka