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《Journal of Zhejiang University(Engineering Science)》 2004-10
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New digital signal denoising algorithm based on Mumford-Shah functional

CHEN Xu-feng~(1,2), GUAN Zhi-cheng~1(1.Institute of Computer Graphic and Image Processing, Zhejiang University, Hangzhou 310027, China;2.School of Science, Hangzhou Dianzi University, Hangzhou 310018 , China)  
The problem of denoising technique in digital signal processing was analyzed by using the characteristics of the Mumford-Shah functional model. Two-dimensional Mumford-Shah function was simplified and reduced to one-dimensional case. A new signal denoising model was presented which based on the one-dimensional version and the variational theory. Two numerical algorithms for the new model were described: region merging algorithm and points-set growing algorithm. The latter algorithm has global optimization by applying the step-by-step analytical method of statistics. Numerical results show that the algorithms can restore noised signal effectively, and detect the jumping points simultaneously. Compared to the Pollak-Willsky algorithm, the presented algorithms can preserve the original signal structures more precisely.
【CateGory Index】: TP391.41
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【Secondary References】
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1 Zhang Xun,Wu Wenbo (School of Geomatics,Liaoning Technical University,Fuxin 123000,China);Study and Application of Wavelet Threshold Based on Kohonen Neural Network in Remote Sensing Image De-noising[J];Computer Measurement & Control;2008-09
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