cs-2d

离散小波分解，把图像分为高频细节与低频概貌。(Discrete wavelet decomposition, the image is divided into high and low frequency detail overview)

本文实现基于贝叶斯(BAYES)阈值的小波(WAVELET)图像去噪算法，相比较其它的小波去噪算法而言，效果非常好(This realization based on Bayesian (BAYES) Threshold the wavelet (WAVELET) image denoising algorithm, compared with other wavelet denoising algorithm, the effect was very good)

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

形态成分析（MCA）用于图像分割与去噪的实验代码(Form into analysis (MCA) for image segmentation and denoising experimental code)

使用小波包变换分析信号的MATLAB程序, 使用小波包变换分析两个信号的特征向量和各频率成分的功率谱，很完整的一个应用程序 (Signal using wavelet packet analysis of MATLAB program, using wavelet packet analysis of two signal eigenvectors and the power spectrum of each frequency component, an application is complete)

一维小波单支重构函数，一维小波系数直接重构函数(Single one-dimensional reconstruction of wavelet functions, the direct reconstruction of one-dimensional wavelet function)

基于小波域的图像压缩分组编码及其差错隐藏.(Image compression based on wavelet packet coding and error to hide.)

说明：  基于dct系数的数字水印算法实现，在matlab环境中实现(coefficient based on digital watermarking algorithm in Matlab environment to achieve)

说明：  实现对离散信号的连续小波变换进行时频域分析，判断信号的稳定性(The continuous wavelet transform of the signal is analyzed in time and frequency domain)

小波变换的程序包括小波变化 小波分解小波包分解程序(Wavelet transform procedures include wavelet transform wavelet decomposition wavelet packet decomposition program)