norm_max

利用小波变换，通过设置阈值对图像进行去噪。 首先对图像用小波进行2层分解，然后通过设置硬阈值和软阈值的方法，对图像高频部分去噪。(The wavelet transform is used to denoise the image by setting threshold. Firstly, the image is decomposed into 2 layers by wavelet, and then the high frequency part of the image is denoised by setting the hard threshold and the soft threshold.)

计算小波时间熵的源程序，内容详尽，调试正确，非常有用。计算小波时间熵的源程序，内容详尽，调试正确，非常有用。(Calculate the entropy of the source wavelet time, detailed, debugging is correct, very useful. Calculate the entropy of the source wavelet time, detailed, debugging is correct, very useful.)

使用傅里叶变换和小波变换提取心电信号中的呼吸信号(Using the Fourier transform and the wavelet transform to extract the breathing signal ECG)

中值滤波源程序，非常好用。程序有说明很容易看懂！(median filtering source, very handy. Note procedure is easy to read!)

对雾天图像利用小波变换分解，实现图像去雾增强，分解的层数越多，处理后的效果越明显。(On the fog image using wavelet transform decomposition, to achieve the image to fog enhancement, decomposition of the number of layers, the more obvious the effect of the treatment.)

Block-based random image sampling is coupled with a projectiondriven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously with a smooth reconstructed image. Both contourlets as well as complex-valued dual-tree wavelets are considered for their highly directional representation, while bivariate shrinkage is adapted to their multiscale decomposition structure to provide the requisite sparsity constraint. Smoothing is achieved via a Wiener filter incorporated into iterative projected Landweber compressed-sensing recovery, yielding fast reconstruction. The proposed approach yields images with quality that matches or exceeds that produced by a popular, yet computationally expensive, technique which minimizes total variation. Additionally, reconstruction quality is substantially superior to that from several prominent pursuits-based algorithms that do not include any smoothing

用matlab编写的提升小波算法，应用于图像处理，很好用(Matlab prepared using lifting wavelet algorithm used in image processing, very good use)

小波分析用于图像融合和去噪；APES,MUSIC,LMS算法仿真实例；(Wavelet analysis is used to image fusion and noise；APES,MUSIC,LMS )

对含噪声信号进行小波变换；对变换得到的小波系数进行某种处理，以去除其中包含的噪声；对处理后的小波系数进行小波逆变换，得到去噪后的信号(Containing noise signal wavelet transform the wavelet transform coefficients to a treatment to remove the noise contained therein the treated wavelet inverse wavelet transform coefficients to obtain a denoised signal)

小波包分解包括重构信号问题程序，这是一个matlab程序，经过测试可用，数据采用自己的数据。(Including the reconstructed signal wavelet packet decomposition problem program, which is a matlab program, tested available data using their own data.)