20111209_1D_CPML_Lorentz

图像加入水印提取水印的Matlab代码，包括的内容较多，能够完成各种实验的要求。(Extracted watermark image watermark to join the Matlab code, including the contents of more to complete the requirements of various experiments.)

利用小波提升算法实现了第二代小波变换,将之应用在信号去噪中,实现了数据的边界对称延拓,去噪效果较好.(Wavelet Lifting algorithm using the second generation wavelet transform, to be used in signal de-noising, the realization of the data symmetric boundary extension, denoising better.)

美国Rice大学提供的matlab 小波代码，要比matlab自带的matlab更易用(Rice University, USA matlab wavelet code comes than easier to use)

说明：  小波标架的共轭梯度算法（Mallat，信号处理的小波导引）(Conjugate gradient algorithm for computing daul function.)

说明：  可用于信号的EMD、EEMD、VMD分解，里面都加了自己的注释，通俗易懂(It can be used for signal EMD, EEMD, VMD decomposition. Because the algorithm adds its own annotations, it's easy to understand)

本程序实现了db2提升小波的消噪，可直接运行成功。(This program achieved a db2 lifting wavelet denoising can be directly run successfully.)

说明：  给出了在matlab环境下的源代码，经过了上机调试，可以实现小波变换对图像的二次压缩！(given Matlab environment in the source code, after the Machine, can achieve a wavelet transform of the second image compression!)

离散小波变换，再用OMP算法重构出原始信号(DWT transmission，OMP )

小波包和EMD方法对信号分析后的频谱图比较，可以对EMD的运行参数进行修改。(Spectrum comparison of Wavelet package and EMD)

在理解了离散小波变换的基本原理和算法的基础上，通过设计VC程序对简单的一维信 号在加上了高斯白噪声之后进行Daubechies小波、Morlet小波和Haar小波变换，从而得到小波分解系数；再通过改变分解得到的各层高频系数进行信号的小波重构达到消噪的目的。在这一程序实现的过程中能直观地理解信号小波分解重构的过程和在信号消噪中的重要作用，以及在对各层高频系数进行权重处理时系数的选取对信号消噪效果的影响。(In understanding the basis of discrete wavelet transform basic principles and algorithms, through the design VC program Daubechies wavelet, Morlet wavelet and Haar wavelet transform after a simple one-dimensional signal plus a Gaussian white noise, resulting wavelet coefficients wavelet reconstruction signal again by changing the layers to achieve high-frequency coefficients decomposed noise cancellation purposes. Can intuitively understand wavelet decomposition and reconstruction process and an important role in signal de-noising in the process of implementation of this program, and in the high-frequency coefficients when the weight of the layers selected for signal processing coefficients denoising affected.)