Color correction using 3d gaussian mixture models

Authors:
Miguel Oliveira;Angel D. Sappa;Vítor Santos
Affiliations:
Department of Mechanical Engineering, University of Aveiro, Santiago, Aveiro, Portugal;Computer Vision Center, Edifici O, Campus UAB, Bellaterra, Barcelona, Spain;Department of Mechanical Engineering, University of Aveiro, Santiago, Aveiro, Portugal
Venue:
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part I
Year:
2012

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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.