Using the Monge-Kantorovitch Transform in Chromagenic Color Constancy for Pathophysiology

Hemrit, Ghalia, Matsushita, Futa, Uchida, Mihiro, Vasqez-Corral, Javier, Gong, Han, Tsumura, Norimichi and Finlayson, Graham (2019) Using the Monge-Kantorovitch Transform in Chromagenic Color Constancy for Pathophysiology. In: Computational Color Imaging. Lecture Notes in Computer Science . Springer, pp. 121-133. ISBN 978-3-030-13939-1

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Abstract

The Chromagenic color constancy algorithm estimates the light color given two images of the same scene, one filtered and one unfiltered. The key insight underpinning the chromagenic method is that the filtered and unfiltered images are linearly related and that this linear relationship correlates strongly with the illuminant color. In the original method the best linear relationship was found based on the assumption that the filtered and unfiltered images were registered. Generally, this is not the case and implies an expensive image registration step. This paper makes three contributions. First, we use the Monge-Kantorovich (MK) method to find the best linear transform without the need for image registration. Second, we apply this method on chromagenic pairs of facial images (used for Kampo pathophysiology diagnosis). Lastly, we show that the MK method supports better color correction compared with solving for a 3 × 3 correction matrix using the least squares linear regression method when the images are not registered.

Item Type: Book Section
Faculty \ School: Faculty of Science > School of Chemistry
Faculty of Science > School of Computing Sciences
Depositing User: LivePure Connector
Date Deposited: 27 Mar 2019 11:30
Last Modified: 30 Jul 2020 00:00
URI: https://ueaeprints.uea.ac.uk/id/eprint/70355
DOI: 10.1007/978-3-030-13940-7_10

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