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Study on Pretreatment Algorithm of Near Infrared Spectroscopy

机译:近红外光谱预处理算法研究

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摘要

Pretreatment of near-infrared spectral data is the basis of feature extraction, quantitative and qualitative analysis and establishment of models, it plays a significant role in obtaining the data and get reliable results. The purpose of the paper is compared the advantages and disadvantages of the S-G, derivative and multiple algorithm methods of spectral preprocessing through the example of apple leaves. S-G algorithm can smooth the data relatively better, but we must according to the specific circumstances of the case while chose the width of the window and the order of polynomial; Kernel smoothing is better than S-G in two-ends data processing, but its processing speed is slower than S-G. Derivative algorithm can get more stable reflectance, but it is sensitive to noise, so it need to be used with the smoothing algorithm. Multiple scatter correction can be used effectively to eliminate the translation and offset of baseline. All of above algorithms have been applied in the system of near infrared spectroscopy processing system of leaves and satisfactory result was obtained.
机译:近红外光谱数据的预处理是特征提取,定量和定性分析以及建立模型的基础,在获取数据和获得可靠结果方面起着重要作用。本文以苹果叶片为例,比较了S-G,光谱预处理的导数和多种算法方法的优缺点。 S-G算法可以较好地平滑数据,但是必须根据情况的具体情况选择窗口的宽度和多项式的阶数;内核平滑在两端数据处理中比S-G更好,但其处理速度比S-G慢。导数算法可以获得更稳定的反射率,但对噪声敏感,因此需要与平滑算法一起使用。多次散射校正可以有效地消除基线的平移和偏移。以上所有算法已应用于叶片近红外光谱处理系统中,取得了满意的效果。

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