suanfa

curvelet lab,其中包括curvelets的matlab工具箱以及C语言开发(curvelet lab, including the matlab toolbox curvelets as well as the C language development)

小波信号分解与重构的Matlab程序，程序里边涉及卷积的直接调用的Matlab的conv()函数。(Wavelet signal decomposition and reconstruction in Matlab,Program inside invoked directly related to the convolution of Matlab conv () function.)

《小波分析理论与MATALB R2007 实现》第10章源码(wavelet analysis using matlab)

几种小波阈值函数去噪的程序及其运行结果比较(Several wavelet threshold denoising function to run the program and its results more)

双树复数小波变换的滤波程序,在所有小波变换的程序中，该程序采用双变量模型能很好完成去噪功能(dual-tree complex wavlet transform is a good inshift wavelet transform)

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

希尔伯特变换和小波包结合的齿轮箱故障诊断方法，里面有具体的介绍小波包的分层方法，非常详细，可以下下来看看(Hilbert transform and wavelet packet of gearbox fault diagnosis method, there is detailed introduction inside the layered method of wavelet packet is very detailed, can down and have a look )

小波分析程序，包括墨西哥小波morlet小波(Wavelet analysis program)

图像小波变换，小波变换（wavelet transform，WT）是一种新的变换分析方法，它继承和发展了短时傅立叶变换局部化的思想，同时又克服了窗口大小不随频率变化等缺点，能够提供一个随频率改变的“时间-频率”窗口，是进行信号时频分析和处理的理想工具。它的主要特点是通过变换能够充分突出问题某些方面的特征，能对时间（空间）频率的局部化分析，通过伸缩平移运算对信号（函数)逐步进行多尺度细化，最终达到高频处时间细分，低频处频率细分，能自动适应时频信号分析的要求，从而可聚焦到信号的任意细节，解决了Fourier变换的困难问题，成为继Fourier变换以来在科学方法上的重大突破。(Image Wavelet Transform)

可见光与红外图像融合技术的研究 其中多种算法在内(Infrared and visible image fusion research)