DirFilter-test_pic

小波方法进行降噪，阈值函数来完成不同设计，核心程序如下面的所示，使用的小波基有coif5，db3，sym4，bior2.4，haar，rbio(Wavelet method for noise reduction, design to complete different threshold function, the core program as shown below, using the wavelet base coif5, db3, sym4, bior2.4, haar, rbio )

使用小波变换进行图像去噪，对得到的高频部分利用软阈值和硬阈值法去噪(Image denoising using wavelet transform, the high frequency part by the use of soft threshold and hard threshold denoising)

基于墨西哥草帽小波函数进行连续小波变换的matlab变换程序，望对大家有所帮助。(Mexican hat wavelet function based on continuous wavelet transform matlab transformation process, hope to be helpful.)

图像的小波去噪,给灰度图像加上一定量的高斯噪声,再采用小波变换的方法去噪,计算去噪前后图像的PSNR。(Wavelet Denoising images to grayscale images coupled with a certain amount of Gaussian noise, and then using the method of wavelet transform denoising calculated before and after denoising images PSNR.)

说明：  心电信号的处理，包括低通滤波器滤除肌电信号，带陷滤波器抑制工频干扰，以及IIR零相移数字滤波器纠正基线漂移。(ECG signal processing includes low-pass filter to filter EMG signal, band notch filter to suppress power frequency interference, and IIR zero phase shift digital filter to correct baseline drift.)

使用DCT和小波变换的数字音频水印生成/解码程序，可存活于方差0.05的高斯白噪声及不同程度的剪切。内含程序/测试文件介绍。(Digital wartermarking encoding/decoding program with DCT and wavelet transform. nice robustness against Gaussian noise with variance less than 0.05 and any type of cropping attack. functions/test files introduction included)

本程序应用小波变换进行电力系统的在线监测。电力系统在线监测中的检测信号含有大量的背景噪声，不便于检测。应用小波变换解决这一问题。程序中应用db3小波对信号进行5层分解，并得出了各层的细节信号与逼近信号。(This procedure based on wavelet transform power-line monitoring system. Online monitoring of power system test signal contains a lot of background noise, not easy to detect. Application of wavelet transform to resolve this problem. Application procedures for db3 wavelet signal decomposition layer 5, and arrive at different levels of detail signal and approximation signal.)

基于小波变换的通信信号码元速率估计.pdf(Estimated rate based on the communication signal element wavelet transform. Pdf)

离散小波变换与离散小波反变换 快速小波变换（Mallat小波分解算法）：对一幅图像做2级小波分解（离散小波变换）与合成（离散小波反变换）(Discrete wavelet transform and discrete wavelet inverse transform fast wavelet transform (Mallat wavelet decomposition): For an image to do 2 wavelet transform (DWT) and synthesis (discrete wavelet inverse transform))

根据小波变换和噪声信号地能量分布特性，提出了一种先用小波变换对含噪图像进行多尺度分解，求出各尺度小波变换高频系数地噪声方差和阈值，利用各尺度地阈值对高频系数进行处理，然后利用小波变换系数重构图像，实现图像降噪地方法。(According to wavelet transform and noise signal and energy distribution characteristics, a first wavelet transform of the noisy image multiscale decomposition, obtained the high-frequency-scale wavelet transform coefficients and noise variance and thresholds, using the scale to the threshold value of the deal with high-frequency coefficients, and then the use of wavelet transform coefficients reconstructed image, to realize image denoising methods.)