小波阈值去噪的一种改进方案

信号在采集、转换和传输过程中经常会受到设备、环境等因素的影响,致使现实信号成为含噪信号,对得到的信号进行去噪是信号处理中的一个很重要的环节。在近二十年中小波去噪方法应用比较广泛并取得了较好的效果,越来越多的学者用小波阈值进行信号去噪。首先讨论了小波阈值去噪中估计小波系数的软阈值和硬阈值方法,然后本着提高去噪质量的目的,提出了一种改进方案。该方法在阈值函数中加入因子,可以自适应地减小阈值函数中的恒定偏差。与传统阈值去噪方法相比,有以下两点优势:①去噪效果比传统阈值去噪方法好。②具有一定的自适应性。此外,还用Matlab仿真实验证实了该改进方案的有效性和优越性。

A Modified Method of Wavelet-thresholding Denoising

The signal usually will be under the influence of equipments and environment...etc.during the process of collection,conversion,and transmition.So,the realistic signals become noising signals.It is a very important link to denoise in the signal processing.Over the past decade,wavelet denoising have applied in many different areas.Most researchers use the threshold denoising methods.This paper first presents soft-thresholding and hard-thresholding denoising methods in wavelet thresholding denoising,then,it presents a new thresholding function based on them,as their modified project,in order to improve the denoising effect.We add a factor to this modified project,so it can self-adaptively reduce the fixed deviation in soft-thresholding function.Compared with classical thresholding denoising methods,the new method has two advantages:(i) It has better denoising effects than classical thresholding denoising methods.(ii) It has self-adaptation in some extent.Moreover,it can be applied to the effective and superior wavelet thresholding denoising,which is verified through a good many of Matlab simulations.