Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81710
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Title: Lighting deviation correction for integrating-sphere multispectral imaging systems
Authors: Zou, Z
Shen, HL
Zhu, YF
Xin, JH 
Issue Date: 2019
Source: Sensors, 20 Aug. 2019, v. 19, no. 16, 3501, p. 1-13
Abstract: In an integrating sphere multispectral imaging system, measurement inconsistency can arise when acquiring the spectral reflectances of samples. This is because the lighting condition can be changed by the measured samples, due to the multiple light reflections inside the integrating sphere. Besides, owing to non-uniform light transmission of the lens and narrow-band filters, the measured reflectance is spatially dependent. To deal with these problems, we propose a correction method that consists of two stages. The first stage employs a white board to correct non-uniformity and a small white patch to correct lighting deviation, both under the assumption of ideal Lambertian reflection. The second stage uses a polynomial regression model to further remove the lighting inconsistency when measuring non-Lambertian samples. The method is evaluated on image data acquired in a real multispectral imaging system. Experimental results illustrate that our method eliminates the measurement inconsistency considerably. This consequently improves the spectral and colorimetric accuracy in color measurement, which is crucial to practical applications.
Keywords: Multispectral imaging
Integrating sphere
Lighting deviation
Spectral reflectance
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Sensors 
EISSN: 1424-8220
DOI: 10.3390/s19163501
Rights: © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
The following publication Zou, Z.; Shen, H.-L.; Li, S.; Zhu, Y.; Xin, J.H. Lighting Deviation Correction for Integrating-Sphere Multispectral Imaging Systems. Sensors 2019, 19, 3501, 1-13 is available at https://dx.doi.org/10.3390/s19163501
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