chapter10

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)

时频分析，同步挤压小波变换，一种更精细的时频表示！(Signal time-frequency analysis, synchronous extrusion wavelet transform, a finer time-frequency said!!!!)

心电图(ECG)是临床上诊断心血管疾病的重要方法。 数字滤波作为数字信号处理技术的重要组成部分，广泛应用于诸如信号分离、恢复、整形等多种场合中。为了使信号不失真及在可编程逻辑器件中容易实现，采用具有严格线性相位特性的FIR滤波器进行低通滤波（0-150Hz），用整系数梳状滤波器来去工频干扰及基线漂移,从而达到对心电信号进行预处理的目的。(Electrocardiogram (ECG) is an important method for clinical diagnosis of cardiovascular diseases. As an important part of digital signal processing technology, digital filtering is widely applied to many occasions, such as signal separation, recovery, shaping and so on. In order to make the signal undistorted and easy to be realized in programmable logic device, the FIR filter with strict linear phase characteristics is used for low pass filtering (0-150Hz), and the entire coefficient comb filter is used to get the interference of the power frequency and the baseline drift, thus the purpose of preprocessing the ECG signal is achieved.)

利用CVX进行优化，得到期望加权矢量，从而的得到需要的波束形成(CVX using optimized to give the desired beamforming)

使用傅里叶变换和小波变换提取心电信号中的呼吸信号(Using the Fourier transform and the wavelet transform to extract the breathing signal ECG)

说明：  图像小波变换，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。(Image Wavelet Transform)

关于小波分析的程序，用于分析振动信号的程序，很好用(Wavelet analysis on the procedures used to analyze the vibration signal of procedures, very good use)

图像的三级小波分解,小波变换,小波图像重构.(Three-level wavelet decomposition of image.)

形态成分析（MCA）用于图像分割与去噪的实验代码(Form into analysis (MCA) for image segmentation and denoising experimental code)

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.)