The Discrete Wavelet Transform

本文提出了一种构造自适应小波的新方法。其主要思想是通过设计合适的小波滤波器组来提取信号的不同模式。这种构造导致了一种新的小波变换，称为经验小波变换（EWT）。实验结果表明，与经典的经验模式分解(EMD)方法相比，该方法是可行的。

包含【添加噪声】+【软、硬阈值去噪】+【强制去噪、默认阈值去噪、给定阈值去噪】+【对含噪正弦波去噪】+【含噪矩形波去噪】共5个m文件

小波方法测量地震行时变化的代码 这个python程序基于Mao和Mordret的工作，您可以在这里找到： : 原始代码在MATLAB中，这是等效的Python 联系人：Higueret Quentin（ ）和AurélienMordret（ ） 该软件包包含用于使用小波互谱分析在时频域中测量地震传播时间偏移的代码和测试数据。 要求 启动程序时，所有文件都必须位于同一文件夹中 需要Python 3和中的PyCWT软件包来运行代码 您可以使用pip安装此软件包： $ pip install pycwt 包装内容 xwt.py 通过小波交叉谱分析在时频域中计算dt的核心功能。 plotting_example.py 在合成数据上使用cwt函数的示例。 一键即可绘制图。 ori_waveform.npy new_waveform.npy 用于测试代码的两个合成波形ori_wavef

Infrared and visible image fusion with spectral graph wavelet transform

在信号处理中，小波变换效果受到整形参数、小波长度、中心频率、频带宽度及小波个数等参数的制约，特别是整形参数与小波中心频率及频带之间关系对小波变换起到决定性作用。在信号的实际处理中，可选取恰当的整形参数，同时采用合适的小波中心频率以避免小波变换对信号产生的遗漏和冗余，自适应连续小波变换就能达到此目的。

nicely organized and thoroughly pedagogical handbook … The book is very much 'figure driven' and they are extremely useful for illustrating the mathematics and conveying the concepts in an uncomplicated matter … an eminently readable style in motivating and explaining wavelets throughout the course … this book, written as it is in a simple, forthright, and stimulating manner with balanced blend will prove a worthy addition to the understanding of wavelet transforms across disciplines. -Guruprasad Madhavan, Stony Brook Heart Center, IEEE-EMBS The book works on two levels: it is an excellent introduction for readers new to wavelet transforms, and it is a useful source of information and some inspiration to anyone who has been working in the field for some time. … The book presents the field in an authoritative way but not too deeply. It has been designed as an overview and introduction to this dynamic area of computational analysis, and it achieves this with complete success. To conclude, I found this a thought provoking book on a fascinating subject: in fact once into the text I found it hard to put down. -Dr. K.O. Jones, Measurement+Control, Vol. 36/7, Sept. 2003 The book is extremely well put together and lavishly illustrated (as one might infer from the title). … I largely enjoyed reading this book and I strongly recommend it to anyone with an interest in wavelets, or in the general field of signal processing for that matter. -Keith Worden, Journal of Sound and Vibration, 274 (2004) 1135-1136 The book … provide[s] the reader with an overview of theory and practical applications of wavelet transforms methods, a new time-frequency decomposition tool for data analysis … The book can be recommended to the people interested above all in applications in science, engineering, medicine, finance, or elsewhere. An account of the theory of continuous and discrete wavelet transforms, with a large number of examples of their use across a wide range of disciplines, is convenient both for newcomers to the subject ad readers already acquainted with wavelets methods working in particular area of application. -Miloslav Duchori Illustrations really do help in understanding wavelet transforms. It might be taken for granted that illustrations can aid in the understanding of a subject matter as this, but there is sound logical reasoning behind this claim that makes it especially true for this particular subject matter and also a great motivation for the text. This handbook goes the distance and shows that wavelet transforms are powerful data analysis tools that readily lend themselves to intuitive visual analysis and graphical representation, both of which can be critical to correct analysis in practice. -Raymond Martin

二维连续小波变换Matlab源代码，超级宝贵的资源，无私分享。

包含经验小波第四版的工具箱以及作者的三篇参考文献

基本概念（概要） 1. 读取输入图像2. 将图像大小调整为 1024 x 1024 图像3. 定义 Haar 滤波器矩阵 { 1/sqrt(2)*[1 1; 1 -1] } 4. 执行过滤沿着 Colms 然后沿着 Rows 并向下采样 2 迭代更新输出图像5. 多分辨率图像的显示6. 执行恢复沿行然后沿 Colms 并按 2 上采样迭代更新输出图像7. 显示最终恢复的 Img