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原始信号的噪声处理是微型光谱仪器数据处理的重要组成部分,为了提高在弱光照射下便携式微型光谱仪的工作性能,在分析了线阵CCD探测器的各种噪声来源基础上,指出依靠硬件电路去除噪声在微型仪器设备应用的局限性。虽然判断一段离散数据曲线上噪声大小可以采用解析几何或者傅里叶变换得到特征频谱来判断,但是运算复杂,不利于在单片机应用中编程。通过对Freeman方向链码的分析,提出利用Freeman方向链码判断一段曲线上的噪声程度,量化后作为平滑窗口尺寸选择的依据。在处理线阵CCD输出信号中将该方法与固定窗口曲线平滑或者FFT数字滤波器进行了比较,证明了其可行性。Freeman链码的应用简化了在单片机编程中使用数字滤波器的大模块的编程,降低了编程难度,同时使信号噪声的处理仅仅在数学运算阶段中,不引入其他的电路噪声,从而达到比前期增加电子元件处理的方法能更好地抑制噪声的目的。
The noise of the original signal is an important part of the micro-spectrometer data processing. In order to improve the working performance of the portable micro-spectrometer under low light irradiation, based on the analysis of various noise sources of the linear CCD detector, it is pointed out that relying on the hardware circuit Limitations of noise removal in micro-instrumentation applications. Although the size of the noise on a discrete data curve can be judged by using analytic geometry or Fourier transform to obtain the characteristic spectrum, the operation is complicated and not conducive to programming in a singlechip application. Through the analysis of Freeman direction chain code, it is proposed to use Freeman direction chain code to judge the degree of noise on a curve, which is used as the basis for the selection of smooth window size after quantization. This method is proved to be feasible when dealing with linear CCD output signal with the smoothing of fixed window curve or FFT digital filter. The application of Freeman chain code simplifies the programming of large modules using digital filters in microcontroller programming, reducing the programming difficulty while making the signal noise processing only in the mathematical operation phase, without introducing other circuit noise, The method of increasing the electronic component processing can better suppress the noise.