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Color correction matrix for sparse RGB-W image sensor without IR cutoff filter
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Paper Abstract

Unlike photographic image sensors with infrared cutoff filter, low light image sensors gather light over visible and near infrared (VIS-NIR) spectrum to improve sensitivity. However, removing infrared cutoff filter makes the color rendering challenging. In addition, no color chart, with calibrated infrared content, is available to compute color correction matrix (CCM) of such sensors. In this paper we propose a method to build a synthetic color chart (SCC) to overcome this limitation. The choice of chart patches is based on a smart selection of spectra from open access and our own VIS-NIR hyperspectral images databases. For that purpose we introduce a fourth cir dimension to CIE-L*a*b* space to quantify the infrared content of each spectrum. Then we uniformly sample this L*a*b*cir space, leading to 1498 spectra constituting our synthetic color chart. This new chart is used to derive a 3x4 color correction matrix associated to the commercial RGB-White sensor (Teledyne-E2V EV76C664) using a classical linear least square minimization.. We show an improvement of signal to noise ratio (SNR) and color accuracy at low light level compared to standard CCM derived using Macbeth color chart.

Paper Details

Date Published: 24 May 2018
PDF: 10 pages
Proc. SPIE 10677, Unconventional Optical Imaging, 1067704 (24 May 2018); doi: 10.1117/12.2306123
Show Author Affiliations
J. Vaillant, Univ. Grenoble Alpes, CEA, LETI (France)
A. Clouet, Univ. Grenoble Alpes, CEA, LETI (France)
!!Lab. de Psychologie et NeuroCognition, Univ. Grenoble Alpes (France)
D. Alleysson, !!Lab. de Psychologie et NeuroCognition, Univ. Grenoble Alpes (France)


Published in SPIE Proceedings Vol. 10677:
Unconventional Optical Imaging
Corinne Fournier; Marc P. Georges; Gabriel Popescu, Editor(s)

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