An-Efficient-Randomized-Algorithm-for-Detecting-C

基础时频峰值滤波程序，为初学者提供参考。(Based time-frequency peak filtering procedures, and provide a reference for beginners.)

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.)

对基于小波变换的电能质量扰动检测和识别方法进行研究，在总结前人经验的基础上提出自己对算法的改进，并且利用MATLAB软件对改进算法进行仿真分析,取得令人满意的效果,验证所用方法的可行性。 (Power quality disturbances detection and identification method based on wavelet transform and make their own improvements on the algorithm on the basis of previous experience, and improved algorithm for the simulation analysis using MATLAB software, obtain satisfactory results, verify thethe feasibility of the method.)

关于小波变换的一些常用函数，有关多尺度变换，希望可以帮助您(Wavelet commonly used functions, on multi-scale transformation, I hope to help you)

说明：  小波变换算法的C语言实现，包括DWT,INDWT,提升小波，以及小波去噪的MATLAB源代码(wavelet transform algorithm in C language, including DWT, INDWT upgrade wavelet Wavelet denoising and MATLAB source code)

说明：  整数Haar小波变换和逆变换 可用于差值扩展等(Integer Haar wavelet transform and inverter)

MATLAB实现的高斯平滑滤波源代码，用了高斯函数的定义来做，附实例，效果很好(gauss filter by matlab)

小波模极大值去噪程序，希望对大家有用哈！(modulus maxima wavelet denoising procedures in the hope that it may be useful for Kazakhstan.)

Second generation wavelets and applications

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.)