Abstract
Recently, an iterative optimization method was proposed that determines the spectral transmittance of a color filter which, when placed in front of a camera, makes the camera more colorimetric [1]. However, the performance of this method depends strongly on the filter (guess) that initializes the optimization. In this paper, we develop a simple extension to the optimization where we systematically sample the set of possible initial filters and for each initialization solve for the best refinement. Experiments demonstrate that improving the initialization step can result in the effective ‘camera+filter’ imaging system being much more colorimetric. Moreover, the filters we design are smoother than previously reported (which makes them easier to manufacture).
Original language | English |
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Pages | 163-1-163-6 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 30 Oct 2020 |
Event | Electronic Imaging 2020 - Burlingame, California, United States Duration: 26 Jan 2020 → 30 Jan 2020 https://www.imaging.org/site/IST/Conferences/EI/EI2020/IST/Conferences/EI/Symposium_Overview.aspx?hkey=c462d1b7-6d23-420c-ba06-e89cfa07e24f |
Conference
Conference | Electronic Imaging 2020 |
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Abbreviated title | EI2020 |
Country/Territory | United States |
City | California |
Period | 26/01/20 → 30/01/20 |
Internet address |
Keywords
- filter design
- optimisation
- colorimetric
- sampling method
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