一种基于小波最佳分解层数的红外光谱基线校正算法
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An Infrared Spectral Baseline Correction Algorithm Based on Wavelet Optimal Decomposition Layer Number
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    摘要:

    红外光谱分析技术是一种用于食品健康检测、生物制药和环境监测等方面的高新技术。为了去除应用过程中的基线漂移现象,提出了一种基于小波最佳分解尺度的红外光谱基线校正算法。首先,对原始光谱信号多次进行每一层的小波分解,同时也进行每一层的小波重构。然后算得每一层的信噪比,并通过信噪比比对法获得除噪后的光谱信号。接着对该信号进行每一层的小波分解,得到每一层小波细节和小波逼近的频率。分别将两个频率做除法并求出比值。然后比较每层的比值大小,并选择最大的比值作为分解层数的最佳值。将最佳分解层数下的小波逼近系数置零后再进行小波重构,获得基线校正后的光谱信号。通过实验验证发现,该算法不仅可以为小波分解的最佳层数提供依据,而且能够在更好地保留有用信号的同时,除去高频噪声以及低频基线干扰。基线校正比较充分,效果良好。

    Abstract:

    Infrared spectroscopy technology is a new and high technology used in food health inspection, biological pharmacy and environmental monitoring. In order to eliminate baseline drift during application, an infrared spectral baseline correction algorithm based on wavelet optimal decomposition scale is proposed. First, the multi-layer wavelet decomposition and reconstruction are performed on the original spectral signal, and the signal-to-noise ratio of each layer is calculated. Then, the denoised spectral signal is obtained by SNR contrast. The multi-layer wavelet decomposition is performed on the denoised signal to obtain the frequencies of the wavelet detail and wavelet approximation. The two frequencies are divided and the ratio is calculated. Then, the ratios of all the layers are compared, and the maximum one is selected as the best number of decomposition layers. Finally, the spectral signal after baseline correction can be obtained by setting the wavelet approximation coefficient to zero at the optimal decomposition layer number and reconstructing the wavelet. After the experiment verification, it is found that this algorithm can not only provide the basis for the optimal number of layers for wavelet decomposition, but also can remove the high frequency noise and low frequency baseline interference while retaining the useful signals better. The baseline correction is quite sufficient and the effect is good.

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吕子敬,张鹏,张志辉,等.一种基于小波最佳分解层数的红外光谱基线校正算法[J].红外,2020,41(12):30-35.

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