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Extracting chlorophyll spectral characteristics by wavelet transformation

机译:用小波变换提取叶绿素光谱特性

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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:通过小波变换将光谱信号(350〜550nm)内的频谱信号进行噪声,并提取一些特征波峰,例如叶绿素的380nm,414nm,437nm和叶酸366nm。在550nm至2500nm的范围内,在取消通知后,最大的误差小于1.47%,而在波的峰值上最大的误差小于0.11%。结果表明,在这项工作中使用的小波脱光略微影响其他非噪声带。该方法在预处理光谱数据中非常有效。更多对叶绿素谱特征的考虑有助于为开发具有强烈抗干扰,高可靠性和普遍性的叶绿素仪表提供依据。

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