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.
Highlights
Integrating spheres are widely used in radiometric and photometric measurements, among which reflectance measurement is a typical application [1]
Considering the illuminant fluctuation and non-Lambertian samples, in this paper, we propose a two-stage lighting deviation correction for integrating sphere multispectral imaging systems
We have proposed a lighting correction method to eliminate the measurement inconsistency caused by spatial non-uniformity and lighting deviation in integrating sphere multispectral imaging systems
Summary
Integrating spheres are widely used in radiometric and photometric measurements, among which reflectance measurement is a typical application [1]. Absolute or relative reflectance measurements can be conducted by using integrating spheres. One is the comparison method, in which the standard and sample are placed in the sphere simultaneously. By reconstructing the 31-channel spectral reflectance from corresponding camera responses at different bands, we further quantified the improvement in spectral color measurement with our method. For a patch placed on different background samples, the consistency of color measurement can be evaluated using both spectral and colorimetric errors. The colorimetric errors were computed using the CIEDE2000 color difference formula [33] under CIE standard illuminants D65, A, and F2, respectively. The average color difference error under D65 of the original spectral reflectances was 5.1649 units before lighting deviation correction. It was reduced to 3.0092 and 0.3679 units after applying the corrections in Stage I and Stage II
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