小波对图像的二次压缩.

波的合成及拍频现象实例，输入两正弦波的振幅、初相位及频率观察波的合成及拍频现象(Synthesis and beat frequency wave phenomena instance, enter the two sine wave amplitude, initial phase and frequency of observation of waves synthesis and beat frequency phenomenon)

基于小波变换方法的去雾源代码图像复原代码(Wavelet-based approach to image restoration fog source code)

此程序仿真了一个被污染了的信号源，然后通过小波去噪，成功取出了信号中的杂波(This procedure simulation has polluted the supply oscillator, then through the wavelet denoising, the success took out in the signal clutter )

对雾天图像利用小波变换分解，实现图像去雾增强，分解的层数越多，处理后的效果越明显。(On the fog image using wavelet transform decomposition, to achieve the image to fog enhancement, decomposition of the number of layers, the more obvious the effect of the treatment.)

说明：  带有多种小波基的小波变换程序，可用于图象识别，信号突变检测。(with multiple small Porgy wavelet transform procedures can be used to image recognition, signal mutation detection.)

说明：   这是一个用小波神经网络进行非线性函数逼近的例子，拟合效果非常好，保证能运行！有详细注释！我是参考《青岛海洋大学学报》 2001年第1期 一种基于BP算法学习的小波神经网络编写的，大家可以针对原文更好的理解我的程序！(This is a wavelet neural network with nonlinear function approximation example of fitting results is very good, guaranteed to run! Detailed Notes! I refer to Journal of Ocean University of Qingdao，2001 ，“a learning algorithm based on BP wavelet neural network ”, you will understand me better for program!)

利用Harr将图像进行3层小波变换，并进行重建。里面包含测试图片及变换后系数重新排列后的结构图。(Harr is used to transform the image into three-layer wavelet transform and reconstruct it. It contains the test picture and the structure chart of the coefficient rearrangement after transformation.)

小波基矩阵乘法快速算法工具箱，里面有目录，供大家学习参考！(Tools for Fast Matrix Multiplication in Wavelet Basis)

说明：  提出了一种结合SVD的小波变换方法，对其在外弹道测量数据中的野值剔除进行了研究。对观测数据进行小波分解，将小波分解后的近似分量和细节分量组合实现相空间重构，作为SVD方法的输入观测矩阵，根据奇异 熵增量准则，对奇异值进行筛选，根据SVD逆变换重构原信号。这一方法克服了Hankel矩阵相空间构建方法数据 端点失真问题。以小波分解后分量重构的相空间可以满足正交性，进一步提高了SVD进行数据降噪和野值检测的精度。仿真数据和试验数据处理结果证明了这一方法的有效性。(Proposed a method of combining the SVD wavelet transform its outer ballistic measurement data in excluding outliers were studied. Observational data on wavelet decomposition, wavelet decomposition of the approximate combined component and detail component to achieve the phase space reconstruction, as the input observation matrix SVD method, based on singular entropy increment standards, singular value filter, according to the inverse transform heavy SVD structure of the original signal. This approach overcomes the Hankel matrix phase space construction method data endpoint distortion. Wavelet decomposition component of reconstruction phase space satisfy orthogonality, to further improve the SVD for data noise reduction and outlier detection accuracy. Simulation data and experimental data processing results prove the effectiveness of this approach.)

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).)