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Extracting chlorophyll spectral characteristics by wavelet transformation

机译:小波变换提取叶绿素光谱特征

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It was successful to de-noise the spectrum signal within visual wave band (350 ∼ 550nm) by wavelet transformation and extract some characteristic wavepeaks such as chlorophyll''s 380nm, 414nm, 437nm and the folic acid 366nm. In the range from 550nm to 2500nm, after de-noising, the biggest error was smaller than 1.47%, while at the peaks of waves the biggest error was smaller than 0.11%. The results showed that the wavelet de-noising used in this work slightly or not affect the other non-noise band. The method is very effective in preprocessing spectral data. More consideration of the chlorophyll spectrum characters is helpful to provide a basis for developing chlorophyll meter which has a Strong anti-interference, high reliability and universality.
机译:通过小波变换对可见光波段(350〜550nm)内的光谱信号进行了去噪并提取了一些特征性的波峰,如叶绿素的380nm,414nm,437nm和叶酸366nm,这是成功的。在550nm至2500nm范围内,经过消噪后,最大误差小于1.47%,而在波峰处,最大误差小于0.11%。结果表明,该工作中使用的小波消噪对其他非噪声频段影响很小或没有影响。该方法在预处理光谱数据方面非常有效。对叶绿素光谱特性的更多考虑有助于为开发抗干扰性强,可靠性高,通用性强的叶绿素计提供基础。

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