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实现图像识别，基于小波变换实现图像特征提取，然后神经网络进行训练(The image recognition is realized, the image feature extraction is realized based on wavelet transform, and then the neural network is trained.)

adaboost的实现算法，可进行人脸的样本训练(implementation of the AdaBoost algorithm, can be a sample of people face training)

说明：  关于全变分的图像修复算法。。 。。 。。 。。 (On the whole variational image restoration algorithm. . . . . . . .)

垂直投影算法。可以直接在matlab上跑(err)

本程序实现位图的读写，均衡化，滤波，LBP，LTP特征提取以及基于LBP，LTP和卡方距离，最近邻分类的人脸识别，批量给图片改名等功能(The program can read and write a bitmap, equalization, filtering, LBP, LTP feature extraction and nearest neighbor classifier for face recognition based on LBP, LTP and chi-square distance, rename picture and some other functions.)

论文《Enhancing The Low Quality Images Using Unsupervised Colour Correction Method》提出的算法代码(algorithm code of pape《Enhancing The Low Quality Images Using Unsupervised Colour Correction Method》)

说明：  数字图像处理(Digital Image Processing)是通过计算机对图像进行去除噪声、增强、复原、分割、提取特征等处理的方法和技术。 [1] 数字图像处理的产生和迅速发展主要受三个因素的影响：一是计算机的发展；二是数学的发展（特别是离散数学理论的创立和完善）;三是广泛的农牧业、林业、环境、军事、工业和医学等方面的应用需求的增长(Digital Image Processing (DIP) is a method and technology of removing noise, enhancing, restoring, segmenting and extracting features from images by computer. [1] The emergence and rapid development of digital image processing are mainly influenced by three factors: first, the development of computer; second, the development of mathematics (especially the establishment and improvement of discrete mathematics theory); third, the growth of the demand for extensive applications in agriculture, animal husbandry, forestry, environment, military, industry and medicine.)

此程序为shearlet程序，用于对图像进行分解变换，有兴趣的可以下载(This procedure for shearlet program for image decomposition transform, are interested can download)

说明：  水下图像融合，图像融合，matlab语言(Underwater image fusion, image fusion, MATLAB language)

说明：  用matlab利用压缩感知CS实现对一位信号的处理~小波稀疏分解，正交追踪算法重构~1-D信号压缩传感的实现(正交匹配追踪法Orthogonal Matching Pursuit) 测量数M>=K*log(N/K),K是稀疏度,N信号长度,可以近乎完全重构(CS with matlab using compressed sensing to achieve a sparse signal processing- wavelet decomposition, the orthogonal tracking reconstruction algorithm)