非下采样小波变换红外光谱数据去噪  

Denoising method for infrared spectral data based on non-subsampled wavelet transform

作　　者：宗靖国[1] 秦翰林[1] 何国经[1] 袁胜春[1] 刘德连[1] 赵小明[1] 

机构地区：[1]西安电子科技大学技术物理学院,西安710071

出　　处：《强激光与粒子束》2013年第5期1105-1109,共5页High Power Laser and Particle Beams

基　　金：中央高校基本科研业务费专项资金项目(K50511050003;K50510050003;72005623)

摘　　要：为了降低噪声对实测红外光谱信号的影响,引入了一种非下采样小波变换的红外光谱数据去噪方法。采用非下采样小波变换对原始光谱信号进行多尺度分解,提取信号的多尺度细节特征;根据光谱信号和噪声在不同尺度上的差异,通过应用变分偏微分方程方法调整分解后的各子带系数;重构各子带就可以将原始光谱信号中真实信号和噪声分离,从而达到剔除噪声的目的。通过两组实验对比传统小波和该方法针对红外光谱数据的消噪效果,实验结果表明:非下采样小波变换在红外光谱数据去噪方面具有明显的优势,不仅能够有效地去除噪声,很好地保持信号的形状,并且均方误差较小;在实际的红外光谱数据处理中能够获得较好的去噪效果。To reduce the impact of noise on infrared spectral signal measurement, a denoising method based on non-subsampled wavelet transform（NSWT） is proposed. In this method, original spectrum signal is decomposed in multi-scale with NSWT. According to the difference between signal and noise in the scales, sub-band coefficients from the decomposition are adjusted by resolving correlated variational partial differential equations. Signal and noise can then be separated in re-composing the subbands. Experiments were conducted for denoising performance comparison between traditional wavelet method and our method. The experiment results show that our method is much better in denoising and signal shape＇s keeping. The mean square error of our method is also less than that of the traditional method.

关 键 词：红外光谱数据 光谱去噪 非下采样小波变换 变分偏微分方程 

分 类 号：TN219[电子电信—物理电子学]