| ||Improving Color Constancy by Photometric Edge Weighting|
In IEEE Transactions on Pattern Analysis and Machine Intelligence 2012.
[bibtex] [pdf] [url]
Edge-based color constancy methods make use of image derivatives to estimate the illuminant. However, different
edge types exist in real-world images such as material, shadow and highlight edges. These different edge types may have a
distinctive influence on the performance of the illuminant estimation.
Therefore, in this paper, an extensive analysis is provided of different edge types on the performance of edge-based color
constancy methods. First, an edge-based taxonomy is presented classifying edge types based on their photometric properties
(e.g. material, shadow-geometry and highlights). Then, a performance evaluation of edge-based color constancy is provided
using these different edge types. From this performance evaluation it is derived that specular and shadow edge types are more
valuable than material edges for the estimation of the illuminant. To this end, the (iterative) weighted Grey-Edge algorithm is
proposed in which these edge types are more emphasized for the estimation of the illuminant.
Images that are recorded under controlled circumstances demonstrate that the proposed iterative weighted Grey-Edge algorithm
based on highlights reduces the median angular error with approximately 25%. In an uncontrolled environment, improvements in
angular error up to 11% are obtained with respect to regular edge-based color constancy.
author = "Gijsenij, A. and Gevers, T. and van de Weijer, J.",
title = "Improving Color Constancy by Photometric Edge Weighting",
journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
number = "5",
volume = "34",
pages = "918--929",
year = "2012",
url = "https://ivi.fnwi.uva.nl/isis/publications/2012/GijsenijTPAMI2012",
pdf = "https://ivi.fnwi.uva.nl/isis/publications/2012/GijsenijTPAMI2012/GijsenijTPAMI2012.pdf",
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