lift97mlhard

音频数字水印技术，采用小波变换，psnr、snr、nc等参数计算(Audio watermarking, DWT translation,parameter caculation)

单分量仿真信号进行小波变换后，小波脊线的提取(After the simulation of a single component signal wavelet transform, wavelet ridge extraction)

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)

说明：  代码主要应用于图像融合的处理方面，包含Matlab在图像方面的工具箱，小波变换算法的源代码（包含多分辨率小波算法，自适应小波算法的研究）等等(Code is mainly used in image fusion processing, the image area contains Matlab toolbox, wavelet transform algorithm source code (including multi-resolution wavelet algorithm, adaptive wavelet algorithm), etc.)

基于小波变换的碰磨故障信号的特征提取，可以画出信号原图，轴心轨迹，频谱图以及多层小波变换的重构信号(Based on wavelet transform rubbing fault signal feature extraction, the signal can be drawn artwork, orbit, spectrum and signal reconstruction wavelet multi-)

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)

对仿真信号进行复morlet小波变换后，绘制的时频图。(After the simulated signal multiplexing morlet wavelet transform, time-frequency diagram drawn.)

说明：  2.1 傅里叶变换 2.1.1 经典傅里叶变换 2.1.2 傅里叶变换的基本性质 2.1.3 快速傅里叶变换 2.1.4 短时傅里叶变换 2.2 小波分析与多分辨率分析的历史 2.3 小波分析与傅里叶变换的对比 2.4 小波变换 2.4.1 连续小波变换 2.4.2 离散小波变换 2.4.3 高维小波连续变换 2.5 常用小波基函数 2.5.1 小波函数 2.5.2 小波函数系 2.5.3 复数小波 2.6 构造紧支撑正常小波基 2.7 多分辨率分析与小波构造 2.8 分析小波包 2.8.1 小波包的定义及性质 2.8.2 分解小波包的空间 2.8.3 小波包算法(2.1 Fourier transform 2.1.1 classical Fourier transform 2.1.2 The basic properties of the Fourier transform 2.1.3 Fast Fourier Transform 2.1.4 short time Fourier transform 2.2 wavelet analysis and multi-resolution analysis of the history of 2.3 Wavelet Analysis and comparison of the Fourier transform 2.4 Wavelet Transform 2.4.1 Continuous Wavelet Transform 2.4.2 Discrete Wavelet Transform 2.4.3 Continuous high-dimensional wavelet transform 2.5 Common wavelet basis function 2.5.1 wavelet function 2.5.2 Department of wavelet function 2.5.3 Complex Wavelet 2.6 Construction of compactly supported wavelets normal More than 2.7 resolution analysis and wavelet construction 2.8 Analysis of Wavelet Packet 2.8.1 Definition and properties of wavelet packet 2.8.2 wavelet packet decomposition space 2.8.3 Wavelet Packet Algorithm)

数字全息和计算程式 计算全息图的制作和再现过程主要分为以下几个步骤： 1抽样。得到物体或波面在离散样点上的值。 2.计算。计算物光波在全息平面上的光场分布。 3.编码。把全息平面上光波的复振幅分布编码成全息图的透过率变化。 4.成图。在计算机控制下，将全息图的透过率变化在成图设备上成图。如果成图设备分辨率不够，再经光学缩版得到实用的全息图。 5.再现。这—步骤在本质上与光学全息图的再现没有区别。 (Digital Holography and CGH for calculating the production and reproduction process is divided into the following steps: 1 sampling. Be objects, or wavefront-like point in the discrete value. 2. Calculated. Calculation of complex light plane in the holographic optical field distribution. 3. Coding. The hologram plane the complex amplitude distribution of light into a hologram coding changes in the transmittance. 4. As Fig. Under the control of the computer, the hologram transmittance change in the mapping device mapping. Mapping equipment, if not resolution, then reduced by the optical version of a hologram to be practical. 5. Reproduction. This is- these in essence a hologram and the optical reproduction is no different.)

2002年，MN Do和Martin Vetterli提出了一种“真正”的图像二维表示方法：Contourlet变换，也称塔型方向滤波器组(Pyramidal Directional Filter Bank, PDFB)。Contourlet变换是利用拉普拉斯塔形分解(LP)和方向滤波器组(DFB)实现的另一种多分辨的、局域的、方向的图像表示方法。(In 2002, MN Do and Martin Vetterli proposed a "real" two-dimensional representation of images: Contourlet transform, also known as Pyramidal Directional Filter Bank (PDFB). Contourlet transform is another multi-resolution, local and directional image representation method based on Laplacian pyramid decomposition (LP) and directional filter banks (DFB).)