@InProceedings{MiguelOliveira2012,
author="Miguel Oliveira
and Angel Sappa
and V. Santos",
title="Color Correction using 3D Gaussian  Mixture Models",
booktitle="9th International Conference on Image Analysis and Recognition",
year="2012",
publisher="Springer Berlin Heidelberg",
volume="7324",
number="I",
pages="97--106",
abstract="The current paper proposes a novel color correction approach based on a probabilistic segmentation framework by using 3D Gaussian Mixture Models. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. The proposed approach is evaluated using both a recently published metric and two large data sets composed of seventy images. The evaluation is performed by comparing our algorithm with eight well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches.",
optnote="ADAS",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2015), last updated on Fri, 23 Jun 2017 11:09:28 +0200",
isbn="10.1007/978-3-642-31295-3\_12",
issn="0302-9743",
doi="10.1007/978-3-642-31295-3_12",
file=":http://refbase.cvc.uab.es/files/OSS2012a.pdf:PDF"
}