PT Journal
AU Shida Beigpour
   Christian Riess
   Joost Van de Weijer
   Elli Angelopoulou
TI Multi-Illuminant Estimation with Conditional Random Fields
SO IEEE Transactions on Image Processing
JI TIP
PY 2014
BP 83
EP 95
VL 23
IS 1
DI 10.1109/TIP.2013.2286327
DE color constancy; CRF; multi-illuminant
AB Most existing color constancy algorithms assume uniform illumination. However, in real-world scenes, this is not often the case. Thus, we propose a novel framework for estimating the colors of multiple illuminants and their spatial distribution in the scene. We formulate this problem as an energy minimization task within a conditional random field over a set of local illuminant estimates. In order to quantitatively evaluate the proposed method, we created a novel data set of two-dominant-illuminant images comprised of laboratory, indoor, and outdoor scenes. Unlike prior work, our database includes accurate pixel-wise ground truth illuminant information. The performance of our method is evaluated on multiple data sets. Experimental results show that our framework clearly outperforms single illuminant estimators as well as a recently proposed multi-illuminant estimation approach.
ER