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小波软阈值的去噪处理方法,里面有程序运行的Demo.-soft thresholding wavelet denoising way, there are procedures in the Demo.
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小波软阈值去噪soft harr.rar 将文件所在目录设为工作目录,然后打开wavlet.fig,在noise提示框下输入噪声强度,在0-0.1之间(不能为零)。然后点process按钮,就会显示实验结果,包括原图像,加噪图像,去噪图像的对比以及当前的psnr值。 wavlet.m是程序文件。-wavelet soft thresholding soft harr.rar file directory as the working directory. wavlet.fig then open
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小波软阈值去噪soft harr.rar 小波软阈值去噪soft harr.rar 将文件所在目录设为工作目录,然后打开wavlet.fig,在noise提示框下输入噪声强度,在0-0.1之间(不能为零)。然后点process按钮,就会显示实验结果,包括原图像,加噪图像,去噪图像的对比以及当前的psnr值。 wavlet.m是程序文件。-wavelet soft thresholding wavelet soft harr.rar soft thresholding soft harr.r ar
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速度非常块,效果接近blsgsm。堪称去噪的又一突破。
OWT SURE-LET SOFTWARE FOR MATLAB
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Florian Luisier, Thierry Blu and Michael Unser
Biomedical Imaging group
Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland.
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小波变换去噪,软阈值和硬阈值,以及自己的设计的阈值函数来去噪,毕业设计全套。很全面的资料,绝对最全面的资料,我保证,Wavelet denoising, soft thresholding and hard thresholding, as well as design their own threshold denoising function, the design of a full set of graduation. Comprehensive information is absol
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包括的多个示例源代码有:一维线性非线性近似、二维线性非线性近似、使用线性滤波过滤噪声、使用小波门限消除噪声、使用小波变换压缩一维信号、二维小波图像压缩等等。-Including the source code of a number of examples are: a linear one-dimensional non-linear approximation, nonlinear two-dimensional linear approximation, the use of linear
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小波阈值去噪,实现那的生死小波的去早实现和问卷字啊额的-wavelet soft-thresholding
this is a good ids ea se
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Wavelet Thresholding Techniques for
Power Spectrum Estimation
Pierre Moulin
Bell Communications Research
445 South Street
Morristown, NJ 07960
email: moulin@bellcore.com
tel (201) 829-5021
fax (201) 829-4391
August 1993
to appear
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IMAGE DENOISING USING BAYES THRESHOLDING OF WAVELET COEFFICIENTS
基于贝叶斯(BAYES)阈值的小波(WAVELET)图像去噪算法源代码-IMAGE DENOISING USING BAYES THRESHOLDING OF WAVELET COEFFICIENTS Bayesian (BAYES) threshold wavelet (WAVELET) image denoising algorithm source cod
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小波方法和偏微分方程方法是图像去噪中的主要方法。该文提出基于离散小波变换对图像进行阈值去噪,得出了小波阈值的偏微
分方程表示形式,在此基础上研究偏微分方程的解法,采用分数步的小波阈值方法对图像去噪,得到了较好的去噪效果,同时可以保护边
缘。数值试验结果表明,该方法具有比小波方法更好的去噪效果,能获得较高的信噪比-Wavelet method and partial differential equations is the main method of image denoising.
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Denoising demonstration based on the SURE-LET principle applied to interscale orthonormal wavelet thresholding. To run this scr ipt, just type denoising_demo in your Matlab Command Window
-Denoising demonstration based on the SURE-LET principle app
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此文件夹主要是在学习自适应语音小波阈值去噪中所查找的文献,其中论文包括自适应算法的介绍、语音小波自适应去噪、其他数字信号自适应小波阈值去噪。-This folder is the main voice in the learning adaptive wavelet threshold denoising in the search of the literature, which includes adaptive algorithm thesis presentation, voice, w
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将小波相邻系数相关性的降噪思想引入到冗余第2代小波中,提出了基于邻域相关性的冗余第2代小波降噪方法,该方法克服了传统阈值降噪没有考虑小波系数之间相关性的不足。-Aiming at fault feature extraction in the background of strong noise, a wavelet denoising idea by incorporating neighboring coefficients is introduced into redundant seco
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利用小波分析方法,阈值去噪的算法及MATLAB实现的程序-Wavelet analysis method, thresholding algorithm in MATLAB program
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对图像进行二维离散小波变换, 变换级数大于等于3级,然后进行阈值化处理(阈值约为10左右),再统计系数中0的个数(百分比表示)并进行重构, 最后计算重构图像的峰值信噪比(PSNR). -Two-dimensional discrete wavelet transform image transformed series is greater than or equal to 3, and then processing thresholding (threshold of about 10 or
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二维离散小波变换(Mallat快速算法)对图像进行二维离散小波变换, 变换级数大于等于3级,然后进行阈值化处理(阈值约为10左右),再统计系数中0的个数(百分比表示)并进行重构, 最后计算重构图像的峰值信噪比(PSNR).
数据:灰度图像lena.bmp或其它图像, 滤波器系数可以调用matlab中的wfilters函数获得, wfilters函数的使用请在matlab中help wfilters.-Two-dimensional discrete wavelet transform (Ma
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bayes shrink is a thresholding method in wavelet based denoising of images
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对设备进行故障诊断的主要方法就是测量故障
设备的振动或噪声, 并对其进行分析, 从而找出故障原因。然而振动或噪声信号中除了对分析故障有用的信息外, 还有大量的噪声成分。只有有效地滤除噪声, 才能获得有用的信息, 从而得到可靠的分析结论。传统的滤噪方法是将被噪声污染的信号通过一个滤波器, 滤掉噪声频率成分。但对于短时瞬态信号、非平稳信号、含宽带噪声的信号, 采用传统处理方法有着明显的局限性。小波变换为信号去噪提供了一种有效的方法, 小波阈值去噪具有传统方法不可比拟的优越性。但是小波分解的频域重
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Gaussian的小波去噪工具箱,基于matlab-Gaussian Wavelet Denoising Matlab Toolbox
Various wavelet shrinkage and wavelet thresholding estimators, appeared in the nonparametric regression literature, are implemented in MATLAB§. These estimators arise from a wide
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小波域阈值去噪
将信号映射到小波域,根据噪声和噪声的小波系数在不同尺度上具有不同的性质和机理,对含噪信号的小波系数进行处理。
-Thresholding in wavelet domain to the wavelet domain signal mapped, in accordance with noise and noise wavelet coefficients have different properties and mechanisms at different scal
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