小波分析在汽车车灯光源色测量中CCD光谱的消噪平滑处理

CCD Spectrum Processing of Automobile Lamp Testing with Wavelet Analysis

本文依据小波变换原理 ,提出利用小波变换技术对汽车车灯光源色测量中实时采集的光源光谱信号进行多分辨分解 ,有效地消除噪声 ,提高了光谱的信噪比。由CCD接收的标准A光源谱进行了多层分解 ,讨论了不同小波基和分解阶次对信号分析结果的影响。选取最佳小波基 ,为光谱信号消噪平滑处理提供了较有效的数据处理方法。通过对CCD接收的光谱信号进行了消噪和平滑处理 ,解决了实时采集光谱信号在分析和数据处理上的困难 ,该研究充分体现了小波变换在数据处理方面的优势 ,在依赖于光谱信号的颜色测量领域中起重要的作用。

According to the wavelet multi-resolution analysis, the optical spectrum signal received by CCD was processed and analyzed by using the wavelet transformation technique. The noise in the optical spectrum signal can be removed by using the wavelet multi-resolution analysis technique. The curve of spectral signal can be smoothed. The ratio of signal to noise was enhanced. The spectrum of A-source by CCD was smoothed with wavelet multi-resolution analysis. The processing results with different wavelets in different orders were discussed. An effective data processing method was used for spectrum analysis. The difficulty in the analysis and processing of real-time signal can be solved, which is significant in the color testing field.