基于奇异性检测的信号去噪新方法
Denoising by Singularity Detection
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摘要: 该文引进了一种基于奇异性检测的信号去噪方法,并对其在二维降噪中所需进行的复杂的线性内插作了进一步简化,使得整个二维降噪得以大大简化而达到快速运算和节省存储量的目的。文中详细描述了该算法的理论基础并给出其一维计算机仿真,同时也给出了进一步简化后的二维降噪仿真。这种去噪方法不需要信号或噪声的先验信息。仿真结果表明,相比其它小波去噪方法,该方法的主要优势在于:它在某一时刻的脉冲噪声的辨识和去除能力相当强,而且在去噪的同时能很好地保持信号边缘。
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关键词:
- 噪声; 李氏指数; 奇异性; 小波
Abstract: A signal denoising algorithm based on singularity detection is introduced in this paper, It simplified the complicated linear interpolation operation needed in the 2-D image denoising so that the 2-D denoising is greatly simplified and it can also get the fast denoising and save lots of memory. A complete description of this method and its 1-D denoising simulation are presented. A simplified 2-D denoising simulation is presented, too. This method does not need the prior information of signal or noise. Simulation results indicate that compared to other wavelet based denoising algorithms, the main advantage of this method is: it can better detect and reduce the pulse noise and it can reduce the noise while keeping the signal edges better. -
谢杰成,张大力,徐文立.小波图象去噪综述.中国图象图形学报,2002,7(3):209-217.[2]Donoho D L, Johnstone I M. Ideal spatial adaptation by wavelet shrinkage[J].Biometrika.1994, 81(3):425-[3]Mallat S, Hwang W L. Singularity detection and processing with wavelets, IEEE Trans[J].on Information Theory.1992, 38(3):617-[4]Hsung Tai-Chiu, Lun Daniel Pak-Kong, Siu Wan-Chi. Denoising by singularity detection[J].IEEE Trans. on Signal Processing.1999,47(11):3139-[5]彭玉华.小波变换与工程应用.北京:科学出版社,1999:38-62.[6]徐长发,李国宽.实用小波方法.武汉:华中科技大学出版社,2001:210-225,235-246. -
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