Mean Shift Based Adaptive Filtering and Its Applications to Spectra Signal Processing
Liu Rong①; Duan Fu-qing②; Liu San-yang①;Wu Fu-chao②
①Department of Mathematics, Xidian University, Xi’an 710071, China; ②National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China
Abstract:An adaptive bilateral filtering method based on mean shift algorithm is presented. The filter is governed by the kernel width in spatial domain, which controls the spatial extent of nearby data for filtering. Its kernel width in range domain is chosen adaptively by the local characteristic of the signal. It can remove impulsive noise and improve smoothing of non-impulsive noise with edges preserved. Comparisons with Gaussian filter and median filter were made. Applications to spectra signal processing show this method can suppress noises in spectra effectively and reduce the amount of smoothing near spectral lines.
刘 蓉; 段福庆; 刘三阳; 吴福朝. 基于均值漂移的自适应滤波及其在光谱信号处理中的应用[J]. 电子与信息学报, 2006, 28(2): 312-316 .
Liu Rong①; Duan Fu-qing②; Liu San-yang①;Wu Fu-chao②. Mean Shift Based Adaptive Filtering and Its Applications to Spectra Signal Processing. , 2006, 28(2): 312-316 .