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wavelet_denosiy

于 2019-12-18 发布
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说明:  Donoho提出的小波阀值去噪的基本思想是将信号通过小波变换(采用Mallat算法)后,信号产生的小波系数含有信号的重要信息,将信号经小波分解后小波系数较大,噪声的小波系数较小,并且噪声的小波系数要小于信号的小波系数,通过选取一个合适的阀值,大于阀值的小波系数被认为是有信号产生的,应予以保留,小于阀值的则认为是噪声产生的,置为零从而达到去噪的目的。尺度不变特征变换(Scale-invariant feature transform,SIFT),是用于图像处理领域的一种描述。这种描述具有尺度不变性,可在图像中检测出关键点。(The basic idea of wavelet threshold de-noising proposed by Donoho is that the wavelet coefficients generated by the signal after passing through the wavelet transform (Mallat algorithm) contain the important information of the signal. After the wavelet decomposition, the wavelet coefficients of the signal are larger, the wavelet coefficients of the noise are smaller, and the wavelet coefficients of the noise are smaller than the wavelet coefficients of the signal. By selecting a suitable threshold, the wavelet coefficients of the noise are larger than the valve The wavelet coefficients of values are considered to be generated by signals, which should be preserved. The ones less than the threshold are considered to be generated by noise, which is set to zero to achieve the purpose of denoising.)

文件列表:

lena.jpg, 47132 , 2018-11-08
wavelet_denosiy.m, 953 , 2019-12-18

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