97wavelettansform

数字图像获取, 处理及实践应用源代码——很多有用的图像处理的源代码：图像显示（原图、抖动），图像增强（灰度变换、直方图均衡、多种滤波器、伪彩色增强等），图像复原（运动模糊、逆滤波等等），图像变换（傅立叶变换、快速傅立叶变换、离散余弦变换、沃尔什变换、霍特林变换、小波变换、小波反变换），图像编码（霍夫曼编码、香浓-费诺编码、算术编码、位平面编码等），图像识别。(Digital image acquisition, processing and practical application source code- a lot of useful image processing source code: Image Display (image, jitter), image enhancement (gray-scale transformation, histogram equalization, multi-filter, pseudo-color enhancement, etc. ), image restoration (motion blur, inverse filtering, etc.), image transform (Fourier transform, fast Fourier transform, discrete cosine transform, Walsh transform, Hotelling transform, wavelet transform, wavelet transform), image coding (Huffman coding, Shannon- Fenno coding, arithmetic coding, bit plane coding, etc.), image recognition.)

vc实现虚拟示波器，没有测试过不知道能用吧(vc virtual oscilloscope not tested do not know can)

基于论文<<Blur Detection for digital images using wavelet transform>>,使用Haar小波变换实现图像模糊度检测。(Based on paper <Blur Detection for digital images using wavelet transform> > , Using the Haar wavelet transform of image blur detection.)

一维信号的小波去噪,这是一个很好的基于小波变换的小波去噪，是针对一维的，去噪效果非常好！(1DWT wavelet denoide)

任意阶daubechies小波函数的构造，包括尺度函数和小波函数以及滤波器系数的构造(arbitrary order PG wavelet function, including scaling function and wavelet function and the structure of the filter coefficients)

基于小波变换的语音识别，内含毕业论文和摘要以及可执行源程序(Speech recognition based on wavelet transform, containing thesis and summary of executable source code)

基于小波变换的ECG信号去噪系统设计,在信号采集时，身体的任一微小运动都会产生“基线漂移”，这是一种低频干扰，同时，由于肌电的存在又产生了高频的肌电噪声，由于空间电磁场的存在又使心电信号中混有50Hz的工频干扰。这些噪声不去除，就会影响下一步的信号处理。 综合运用数字信号处理的理论知识进行生物医学信号增强系统设计，实现ECG信号的去噪，从而加深对小波变换及其应用的理解，建立概念多分辨分析的概念，加深理解信号增强的原理、方法和步骤。本设计的主要内容是设计一个基于小波变换的ECG信号去噪系统，实现ECG信号的去噪。 (ECG signal denoising based on wavelet transform system design, signal acquisition, any small movement of the body will have a " baseline drift" , which is a low-frequency interference, while the high frequency due to the existence of the EMG muscle electrical noise due to the presence of electromagnetic field and the ECG signal mixed with a 50Hz power frequency interference. The noise is not removed, it will affect the next step in the signal processing. Use the theoretical knowledge of digital signal processing for biomedical signal enhancement system design to achieve the de-noising of ECG signal, so as to deepen understanding of the wavelet transform and its applications, to establish the concept of multi-resolution analysis of the concept, deepen the understanding of signal enhancement of the principle, the method and steps. The main elements of this design is the design of an ECG signal denoising based on wavelet transform denoising the ECG signals.)

小波阈值法去噪的程序，其中有关于信噪比和均方根误差的公式(wavelet denoising)

基于gabor小波变换的论文，对做人脸识别很有用(Gabor wavelet transform-based papers, do face recognition is useful)

its c-wavelet transform