WMAX

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

说明：  利用ENVI/IDL，对两张影像进行直方图规范化，均衡化。(The histogram of the two images is normalized and balanced.)

1、求冲激函数、阶跃函数及三角函数的小波变换 2、模极大值曲线 3、求它们的李氏指数(one, seeking impulse function, step function and trigonometry two wavelet transform, modulus maxima curve 3, Lee seeking their index)

基于Matlab的JPEG2000图像压缩实现，离散小波变换DWT，程序中图片的位置修改下可以自己运行程序看到效果(Matlab-based implementation of the JPEG2000 image compression, discrete wavelet transform DWT, where the image changes the program may be run its own program to see results)

说明：  采用5/3小波提升算法编写的一维和二维信号小波分解与重构程序。给出了图象分解的演示示例。(using 5/3 wavelet algorithm to enhance the one-and two-dimensional wavelet decomposition and reconstruction process. Given the decomposition of images demonstration examples.)

基于小波变换的信号奇异性检测，小波模极大值的计算(The signal singularity detection based on wavelet transform )

二代小波的labview实现，详细介绍在labview中如何实现二代小波(Labview implementation of second generation wavelet)

自己编写离散小波变换与离散小波反变换程序对一幅图像做2级小波分解（离散小波变换）与合成（离散小波反变换）(Write your own discrete wavelet transform and discrete wavelet inverse transform procedure on an image to do two wavelet transform (DWT) and synthesis (discrete wavelet inverse transform))

说明：  可以将目标矩阵进行线性褶积运算，用于数字信号处理(The target matrix can be linearly convoluted for digital signal processing)

用MATLAB对一语音信号进行小波分解，然后对其各层系数进行处理以达到小波抑制的目的，重构处理后的信号，画出波形分析；用MATLAB实现对一语音信号用不同小波进行分解，提取各层的高低频系数，画出各系数波形，并重构；用MATLAB对一图象分别用不同小波分解，观察高低频部分进行重构，比较重构误差，再进行阈值消噪，比较消噪前后图象；用MATLAB对一语音信号进行小波分解，分别用强阈值，软阈值，默认阈植进行消噪处理。(Wavelet decomposition and reconstruction)