基于奇異性檢測的信號去噪新方法
Denoising by Singularity Detection
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摘要: 該文引進了一種基于奇異性檢測的信號去噪方法,并對其在二維降噪中所需進行的復(fù)雜的線性內(nèi)插作了進一步簡化,使得整個二維降噪得以大大簡化而達到快速運算和節(jié)省存儲量的目的。文中詳細描述了該算法的理論基礎(chǔ)并給出其一維計算機仿真,同時也給出了進一步簡化后的二維降噪仿真。這種去噪方法不需要信號或噪聲的先驗信息。仿真結(jié)果表明,相比其它小波去噪方法,該方法的主要優(yōu)勢在于:它在某一時刻的脈沖噪聲的辨識和去除能力相當強,而且在去噪的同時能很好地保持信號邊緣。
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關(guān)鍵詞:
- 噪聲; 李氏指數(shù); 奇異性; 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. -
謝杰成,張大力,徐文立.小波圖象去噪綜述.中國圖象圖形學(xué)報,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]彭玉華.小波變換與工程應(yīng)用.北京:科學(xué)出版社,1999:38-62.[6]徐長發(fā),李國寬.實用小波方法.武漢:華中科技大學(xué)出版社,2001:210-225,235-246. -
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