基于小波变换的信号奇异性检测及去噪例程

介绍傅立叶变换的漫画，不是大量公式叙述或证明，简洁生动，易于理解。(The caricature that introduces Fourier transform, is not a lot of formula narration or proof, concise and vivid, easy to understand.)

此函数基于二进小波的分解、重构的图像去噪(This function is based on the dyadic wavelet decomposition, reconstruction of the image denoising)

小波基contourlet变换 其中包含spiht编码 去噪 纹理识别(Wavelet transform contourlet transform includes SPIHT coding and denoising texture recognition.)

说明：  利用Gabor滤波器提取图像纹理特征，用于图像分类模式识别(Extract the texture feature using Gabor filter/wavelet. You should first generate cell array G, which is a set of kernels in freq domain, then pass G and the image to the function GABORCONV.)

由仿真结果时域和频域图可以看出，工频50Hz干扰信号很好被滤除掉，说明所设计的自适应滤波器效果较好。(It can be seen by the domain and frequency domain simulation results in Figure, the frequency 50 Hz interference signals very well be eliminated, the design of the adaptive filter is better.)

对输入的二维灰值图像，先进行提升Haar小波变换，再用经典的EZW算法对小波系数进行压缩，然后反变换重构原图像。(On the importation of two-dimensional gray value of images, first upgrade the Haar wavelet transform, and then classical EZW algorithm to compress the wavelet coefficients, and then inverse transform reconstruction of the original image.)

说明：  基于小波的图像分解与重构以及各种灰度图像。(Wavelet-based image decomposition and reconstruction, and various gray scale images.)

说明：  计算小波分解后的能量及小波熵。里面还有OFDM信号和WPM信号的程序。(After calculating the energy of wavelet decomposition and wavelet entropy. There is also OFDM signal and the WPM signal process.)

matlab计算haar 小波各级近似系数和细节系数的频率响应（CA1，CD1，CA2，CD2，CA3），并画出幅频图，便于理解小波变换的意义，(U191 u7197 u5c1 u5c1 u5Fc1 u4Fc u653 u564C u548C u7286 u8282 u7CFB u6570 u7684 u9891 u54CD u5E94 uFF08CA1 uFF0CCD1 uFF0CCA2 uFF0CCD2 UFF0CCA3 uFF09 uFF0C u5E76 u753B u51FA u5E45 u9891 u56FE uFF0C u4FBF u4E8E u7406 u89E3 u5C0F u6CE2 u53D8 u6362 u7684 u610F u4E49 uFF0C)

图像的5/3小波变换的matlab代码。程序简短，易懂。(Image 5/3 wavelet transform matlab code. Program brief and easy to understand.)