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《Computer Measurement & Control》 2008-09
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Study and Application of Wavelet Threshold Based on Kohonen Neural Network in Remote Sensing Image De-noising

Zhang Xun,Wu Wenbo (School of Geomatics,Liaoning Technical University,Fuxin 123000,China)  
In the de-noising of traditional non-linear wavelet threshold,we often select threshold by variance of noise,but that is difficultly obtained in practice,the disadvantage of theory cause that all kinds of the method based-on estimate of variance can't satisfy practical demand.Aim at threshold's choice,the paper propose new de-noising method of non-linear wavelet threshold based on Kohonen neural network in remote sensing image,which combines character mapping of threshold self-organize and neural network,chooses the best threshold according to the images,and reaches the best effect of de-noising.
【Fund】: 教育部博士点基金资助项目(20050147002);; 辽宁省自然科学基金资助项目(20042175)
【CateGory Index】: TP751
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【Secondary Citations】
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