实现图像的匹配，用最大流最小割的算法实现

这是一个人眼识别的C++程序（源码），希望对大家能有帮助。-This is a human eye to identify the C++ Procedure (source), and they hope to have everyone able to help.

matlab在图像处理中的应用，包括模糊，锐化，图像增强-matlab in image processing applications, including blur, sharpening, image enhancement, etc.

边界提取后出现断线，用此程序将边缘连接-Disconnected after the edge extraction, using this procedure will be the edge connecting

本目录存放的是第2章文档的程序源代码，子目录说明： wvltlib 中存放的一些基本的小波基定义和相关库函数； wvltwrefine 中存放的是小波基细化的程序代码； wvltwxfrm 中存放的是一维小波变换的数学实现-Catalog store is the first of the two chapters of the document source code, subdirectories : wvlt lib stored in the basic definition of small Porgy and related library functions; wvlt wrefine stored in the small Porgy sophisticated code; wvlt wxfrm is stored in the wavelet transform one-dimensional mathematical achievement

计算图像调制传递函数（MTF）。提高图像清晰度。可以处理普通图像以及卫星照片-Calculation of image modulation transfer function (MTF). Improve image clarity. Can deal with ordinary images and satellite photos

一阶小波（9/7）变换，图像大小为512*512，可以变换成小波形式并返回，显示方案已被量化的方式

各种基本图像处理功能：1、格式转换：将RAW格式转换成BMP格式；2、线性变换；3、图像平滑；4、图像增强；5、边缘检测：梯度算子，Robert梯度算子，Prewitt算子，Laplacian算子，Sobel算子，Marr算子；6、直方图显示；7、形态运算（二值化、腐蚀、膨胀、开运算、闭运算）；8、自动分类及类别提取：K均值分类。其中：1.2.3.4.5.7仅能对灰度图处理，6.8不仅能处理灰度图还能处理彩色图-Basic image processing functions: 1, format: RAW format will be converted to BMP format 2, linear transformation 3, image smoothing 4, image enhancement 5, Edge Detection: Gradient Operator, Robert gradient operator, Prewitt operator, Laplacian operator, Sobel operator, Marr operator 6, histogram display 7, computing forms (two-value, corrosion, swelling, open computing, closing operation) 8, automatic classification and type of extract: K-means classification. One of: 1.2.3.4.5.7 only treatment for grayscale, 6.8 can not only deal with deal with grayscale color map

基于复杂背景的人体手势识别，以及对它的鲁棒性的测试-Based on complex background of human gesture recognition, as well as its robustness test

8种常用图像处理算法（函数）,带注释，想研究一下的朋友可以-8 kinds of commonly used image processing algorithm (function), with Notes, I would like to look at friends can

理论上实现无噪信道的信噪比的比较，在快跳频中-Theoretically achieve the noise-free channel SNR comparison of the fast frequency hopping