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Effective Wavelengths Selection of Hyperspectral Images of Plastic Films in Cotton

机译:棉花塑料薄膜高光谱图像的有效波长选择

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This research was conducted to investigate the application of detecting plastic films in cotton using visible and near-infrared hyperspectral imaging. A line-scan hyperspectral imaging system (326–1100 nm) was used to detect plastic films mixed with cotton which was an important quality issue. Hyperspectral reflectance images were acquired and difference spectra of cotton and plastic films were extracted and analyzed to determine the dominant wavelengths. Also, as one of the most commonly used methods for dimensionality reduction, principal component analysis (PCA) was chosen to process the hyperspectral images. Afterwards, effective wavelengths were selected by analyzing the first three principal components (PCs) and six single-band images at 473.24 nm, 497.29 nm, 530.6 nm, 670.81 nm, 674.71 nm, and 955.68 nm were extracted respectively. Finally, the selected wavelengths were validated to prove the effectiveness. The results indicated that the selected wavelengths could be able to detect plastic films in cotton instead of the whole wavelengths.
机译:这项研究是进行调查的使用可见光和近红外光谱成像检测棉塑料薄膜中的应用。线扫描超光谱成像系统(326-1100纳米)用于检测塑料薄膜与棉,其是一个重要的质量问题混合。高光谱反射图像获得并提取和分析,以确定主波长棉花和塑料膜的差示光谱。另外,作为用于降维的最常用的方法之一,被选为主成分分析(PCA)来处理高光谱图像。然后,通过分析所述第一三个主成分(PC)和6个单带图像在473.24纳米,497.29纳米,530.6纳米,670.81纳米,674.71纳米选择有效的波长,和955.68处分别萃取。最后,所选择的波长进行了验证,证明有效性。结果表明,所选择的波长可以是能够检测棉塑料薄膜而不是整个波长。

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