This study aims to investigate the combination of speckle pattern analysis, polarization parameters and chemometric tools to predict the optical absorption and scattering properties of materials. For this purpose, an optical setup based on light polarization and speckle measurements was developed and turbid samples were measured at 405 nm and 660 nm. First, backscattered polarized speckle acquisition was performed on a set of 41 samples with various scattering (µ s) and absorbing (µ a) coefficients. Then, several parameters were computed from the polarized speckle images and prediction models were built using stepwise-Multiple Linear Regression. For scattering media, µ s was predicted with R² > 0.9 using two parameters. In the case of scattering and absorbing media, prediction results using two parameters were R² = 0.62 for µ s and R² = 0.8 for µ a. The overall results obtained in this research showed that the combination of speckle pattern analysis, polarization parameters and chemometric tools to predict the optical bulk properties of materials show interesting promises.
In the dataset presented in this article, sixty sugarcane samples were analyzed by eight visible / near infrared spectrometers including seven micro-spectrometers. There is one file per spectrometer with sample name, wavelength, absorbance data [calculated as log
10
(1/Reflectance)], and another file for reference data, in order to assess the potential of the micro-spectrometers to predict chemical properties of sugarcane samples and to compare their performance with a LabSpec spectrometer. The Partial Least Square Regression (PLS-R) algorithm was used to build calibration models. This open access dataset could also be used to test new chemometric methods, for training, etc.
We analyze the multilayer structure of sunflower leaves from Terahertz data measured in the time-domain at a ps scale. Thin film reverse engineering techniques are applied to the Fourier amplitude of the reflected and transmitted signals in the frequency range f < 1.5 Terahertz (THz). Validation is first performed with success on etalon samples. The optimal structure of the leaf is found to be a 8-layer stack, in good agreement with microscopy investigations. Results may open the door to a complementary classification of leaves.
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