Projects per year
Abstract
Color correction involves mapping device RGBs to display counterparts or to corresponding XYZs. A popular methodology is to take an image of a color chart and then solve for the best 3 × 3 matrix that maps the RGBs to the corresponding known XYZs. However, this approach fails at times when the intensity of the light varies across the chart. This variation needs to be removed before estimating the correction matrix. This is typically achieved by acquiring an image of a uniform gray chart in the same location, and then dividing the color checker image by the gray-chart image. Of course, taking images of two charts doubles the complexity of color correction. In this article, we present an alternative color correction algorithm that simultaneously estimates the intensity variation and the 3 × 3 transformation matrix from a single image of a color chart. We show that the color correction problem, that is, finding the 3 × 3 correction matrix, can be solved using a simple alternating least-squares procedure. Experiments validate our approach. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 232–242, 2015
Original language | English |
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Pages (from-to) | 232–242 |
Number of pages | 11 |
Journal | Color Research & Application |
Volume | 40 |
Issue number | 3 |
Early online date | 24 May 2014 |
DOIs | |
Publication status | Published - Jun 2015 |
Keywords
- color correction
- nonuniform intensity
- alternating least squares
- characterization
- shading field
Profiles
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Graham Finlayson
- School of Computing Sciences - Professor of Computing Science
- Colour and Imaging Lab - Member
Person: Research Group Member, Academic, Teaching & Research
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Michal Mackiewicz
- School of Computing Sciences - Professor of Computer Vision
- Colour and Imaging Lab - Member
Person: Research Group Member, Academic, Teaching & Research
Projects
- 1 Finished
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Rank based spectral estimation
Finlayson, G., Gibbs, D., Stodeman, A., Vazquez Corral, J. & Trollope, P.
Engineering and Physical Sciences Research Council
1/09/12 → 30/11/16
Project: Research