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ToolsHemrit, 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
Full text not available from this repository. (Request a copy)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 |
| UEA Research Groups: | Faculty of Science > Research Groups > Interactive Graphics and Audio Faculty of Science > Research Groups > Colour and Imaging Lab |
| Depositing User: | LivePure Connector |
| Date Deposited: | 27 Mar 2019 11:30 |
| Last Modified: | 20 Apr 2023 06:37 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/70355 |
| DOI: | 10.1007/978-3-030-13940-7_10 |
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