Finding a Colour Filter to Make a Camera Colorimetric by Optimisation. Finlayson, G. & Zhu, Y. In Tominaga, S., Schettini, R., Tremeau, A., & Horiuchi, T., editors, Computational Color Imaging, of Lectures Notes in Computer Science, pages 53–62. Springer, February, 2019. ![Finding a Colour Filter to Make a Camera Colorimetric by Optimisation [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex The Luther condition states that a camera is colorimetric if its spectral sensitivities are a linear transform from the XYZ colour matching functions. Recently, a method has been proposed for finding the optimal coloured filter that when placed in front of a camera, results in effective sensitivities that satisfy the Luther condition. The advantage of this method is that it finds the best filter for all possible physical capture conditions. The disadvantage is that the statistical information of typical scenes are not taken into account. In this paper we set forth a method for finding the optimal filter given a set of typical surfaces and lights. The problem is formulated as a bilinear least-squares estimation problem (linear both in the filter and the colour correction). This is solved using Alternating Least-Squares (ALS) technique. For a range of cameras we show that it is possible to find an optimal colour correction filter with respect to which the cameras are almost colorimetric.
@incollection{uea70353,
month = {February},
author = {Graham Finlayson and Yuteng Zhu},
series = {Lectures Notes in Computer Science},
booktitle = {Computational Color Imaging},
editor = {Shoji Tominaga and Raimondo Schettini and Alain Tremeau and Takahiko Horiuchi},
title = {Finding a Colour Filter to Make a Camera Colorimetric by Optimisation},
publisher = {Springer},
year = {2019},
doi = {10.1007/978-3-030-13940-7\_5},
pages = {53--62},
url = {https://ueaeprints.uea.ac.uk/id/eprint/70353/},
abstract = {The Luther condition states that a camera is colorimetric if its spectral sensitivities are a linear transform from the XYZ colour matching functions. Recently, a method has been proposed for finding the optimal coloured filter that when placed in front of a camera, results in effective sensitivities that satisfy the Luther condition. The advantage of this method is that it finds the best filter for all possible physical capture conditions. The disadvantage is that the statistical information of typical scenes are not taken into account. In this paper we set forth a method for finding the optimal filter given a set of typical surfaces and lights. The problem is formulated as a bilinear least-squares estimation problem (linear both in the filter and the colour correction). This is solved using Alternating Least-Squares (ALS) technique. For a range of cameras we show that it is possible to find an optimal colour correction filter with respect to which the cameras are almost colorimetric.}
}
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