De-noising by self-adaptive lifting Algorithm based on Modulus Mazimum Analysis
De-noising by the traditional wavdet transform, the result is affected by the choosing of wavelet base. Because the wavelet base is fixed in the traditional wavelet transform, either the smoothness or singularity of the signal cant be fitted quite well. To overcome the limitation, a new selfadaptive lifting scheme based on modulus maximum analysis is presented. Modulus maximum sequence of the large scale wavelet coefficients can Ioeate the point of the signal with big singularity precisely. According to the position of the point with big singularity, proper neighborhood is fixed, and prediction operator can be chosen self-adaptively. In this way, the prediction operator is fitted to the local feature of the signal The simulation and engineering application showed that the proposed method could overcome the denoising disadvantage of traditional wavelet transform. It not only can filter noise from original signal effectively but also can hold local characteristics of original signal in the denoised signals.
lifging scheme self-adapetive denoising
Wang wei Zhang Yingtang Ren Guoquan
Department of Self-propelled Gun Ordnance Engineering College Shijiazhuang,China
国际会议
长沙
英文
449-452
2009-04-11（万方平台首次上网日期，不代表论文的发表时间）