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Quantification of the optical properties of two-layer turbid materials using a hyperspectral imaging-based spatially-resolved technique

机译：使用基于高光谱成像的空间分辨技术对两层浑浊材料的光学性质进行定量

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摘要

Recent research has shown that a hyperspectral imaging-based spatially-resolved technique is useful for determining the optical properties of homogenous fruits and food products. To better characterize fruit properties and quality attributes, it is desirable to consider fruit to be composed of two homogeneous layers of skin and flesh. This research was aimed at developing a nondestructive method to determine the absorption and scattering properties of two-layer turbid materials with the characteristics of fruit. An inverse algorithm along with the sensitivity coefficient analysis for a two-layer diffusion model was developed for the extraction of optical properties from the spatially-resolved diffuse reflectance data acquired using a hyperspectral imaging system. The diffusion model and the inverse algorithm were validated with Monte Carlo simulations and experimental measurements from solid model samples of known optical properties. The average errors of determining two and four optical parameters were 6.8percent and 15.3percent, respectively, for Monte Carlo reflectance data. The optical properties of the first or top layer of the model samples were determined with errors of less than 23.0percent for the absorption coefficient and 18.4percent for the reduced scattering coefficient. The inverse algorithm did not give acceptable estimations for the second or lower layer of the model samples. While the hyperspectral imaging-based spatially-resolved technique has the potential to measure the optical properties of two-layer turbid materials like fruits and food products, further improvements are needed in determining the optical properties of the second layer.
机译：最近的研究表明，基于高光谱成像的空间分辨技术可用于确定均质水果和食品的光学特性。为了更好地表征水果特性和品质属性，理想的是考虑将水果由两层均匀的皮肤和果肉层组成。这项研究旨在开发一种非破坏性的方法来确定具有水果特性的两层混浊材料的吸收和散射特性。开发了一种用于两层扩散模型的逆算法以及灵敏度系数分析，用于从使用高光谱成像系统获取的空间分辨的漫反射数据中提取光学特性。扩散模型和逆算法通过蒙特卡洛模拟和已知光学性质的固体模型样品的实验测量进行了验证。对于蒙特卡洛反射率数据，确定两个和四个光学参数的平均误差分别为6.8％和15.3％。确定了模型样品第一层或顶层的光学特性，其吸收系数的误差小于23.0％，降低的散射系数的误差小于18.4％。逆算法没有为模型样本的第二层或更低层给出可接受的估计。尽管基于高光谱成像的空间分辨技术具有测量水果和食品等两层混浊材料的光学特性的潜力，但在确定第二层的光学特性方面仍需要进一步的改进。

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