liftwaveletpack

利用小波分析原理对某信号进行分解与重构，并可提取指定层数上的高、低频信号。(A signal is decomposed and reconstructed by using wavelet analysis principle, and high and low frequency signals can be extracted from the specified number of layers.)

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 )

图像的压缩感知进行稀疏化时，首先需要进行创建字典，本程序就可以创建gabor字典(to create the gabor dicitionary)

离散小波变换的简单程序，适合初学者学习，附有通用函数。(Simple procedures discrete wavelet transform, suitable for beginners to learn, with common functions.)

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)

Savitzky-Golay滤波是一种工程应用数据处理中高效的滤波方法，能同时得到平滑后的数据和数据梯度。(Savitzky-Golay filter is an efficient filtering method in engineering application data processing, which can simultaneously obtain the smoothed data and data gradient.)

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。(Wavelet transform (WT) is a new transform analysis method. It inherits and develops the idea of localization of short-time Fourier transform and overcomes the shortcomings that window size does not vary with frequency. It can provide a frequency-dependent The Time-Frequency window is ideal for time-frequency analysis and processing of signals. Its main feature is that by transforming some features that can fully highlight some aspects of the problem, the localization of the time (space) frequency can be analyzed, and the signal (function) can be gradually and multi-scale refined by the scaling operation, finally reaching the high frequency Time subdivision, frequency subdivision at low frequencies, can automatically adapt to the requirements of time-frequency signal analysis, which can focus on any details of the signal to solve the difficulties of Fourier transform has become a major breakthrough in the scientific method since Fourier transform.)

本人自己编写的小波变换脊提取程序，可用与信号分析．欢迎指导．(I have written wavelet transform ridge extraction procedures, can be used with the signal analysis. Welcomed the guidance.)

Multiscale Curvature-Based Shape Representation Using B-Spline Wavelets

Fast wavelet transforms and numerical algorithms 1