eegwave

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.)

离散小波分解，把图像分为高频细节与低频概貌。(Discrete wavelet decomposition, the image is divided into high and low frequency detail overview)

在matlab环境下，实现ECG信号R波的检测，使用的方法是小波变换。(Matlab environment, the realization of the R wave of the ECG signal detection, the methods used wavelet transform.)

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)

基于小波变换的异步电机的故障诊断，本文采用三层小波包分析，诊断效果较好(Wavelet-based fault diagnosis of induction motors, this paper, three wavelet packet analysis, diagnosis, better)

说明：  采用5/3小波提升算法编写的一维和二维信号小波分解与重构程序。给出了图象分解的演示示例。(using 5/3 wavelet algorithm to enhance the one-and two-dimensional wavelet decomposition and reconstruction process. Given the decomposition of images demonstration examples.)

基于多级树集合分裂排序（spiht）的图像压缩算法(Image compression algorithm based on a collection of multi-level tree split-Sort (spiht) of)

基于小波变换的图像拼接。 本程序利用小波变换的原理实现图像的上下，左右以及斜方向的无缝拼接(Wavelet-based image stitching. The procedure to achieve the principle of wavelet transform image from top to bottom, left and right oblique direction and seamless)

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.)

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.)