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We study the relationship between reflectance and the degree of linear polarization of radiation that bounces off the surface of an unvarnished oil painting. We design a VNIR-SWIR (400 nm to 2500 nm) polarimetric reflectance imaging spectroscopy setup that deploys unpolarized light and allows us to estimate the Stokes vector at the pixel level. We observe a strong negative correlation between the S0 component of the Stokes vector (which can be used to represent the reflectance) and the degree of linear polarization in the visible interval (average -0.81), while the correlation is weaker and varying in the infrared range (average -0.50 in the NIR range between 780 and 1500 nm, and average -0.87 in the SWIR range between 1500 and 2500 nm). By tackling the problem with multi-resolution image analysis, we observe a dependence of the correlation on the local complexity of the surface. Indeed, we observe a general trend that strengthens the negative correlation for the effect of artificial flattening provoked by low image resolutions. [ABSTRACT FROM AUTHOR]

Spectral and polarization imaging (SPI) is an emerging sensing method that permits the analysis of both spectral and polarization information of a scene. The existing acquisition systems are limited by several factors, such as the space requirement, the inability to capture quickly the information, and the high cost. We propose an SPI acquisition system with a high spatial resolution that combines six spectral channels and four polarization channels. The optical setup employs two color-polarization filter array cameras and a pair of bandpass filters. We define the processing pipeline, consisting of preprocessing, geometric calibration, spectral calibration, and data transformation. We show that, around specular highlights, the spectral reconstruction can be improved by filtering the polarized intensity. We provide a database of 28 spectropolarimetric scenes with different materials for future simulation and analysis by the research community. [ABSTRACT FROM AUTHOR]