visual-cPP-image-process

锐化图片 拉普拉斯算法 两种方法 一种是自己写的一种是用了matlab里面自带的函数(ruihua picture Laplace there are two mechof a fi [as fs aflasl;nvb)

分类程序的实现，可在vc++平台中运行，方便大家对算法的熟悉与学习(Classification procedures to achieve, can be run in vc++ platform to facilitate learning of the algorithm are familiar with)

用神经网络方法筛选图片，从而判断某一图片是否存在病变(Neural network)

重要的纹理分割分类基础程序，可以进行更深入的探讨和优化，应用于遥感影像中。(Important basis for classification of texture segmentation procedure can be carried out more in-depth exploration and optimization, application of remote sensing images.)

红外图像的亚像素边缘检测，检测边缘，用于图像配准。(Infrared image of the sub-pixel edge detection, edge detection for image registration.)

* 说明: 该函数将对图象进行（成对函数匹配）操作。需要注意的是，此程序先要求对图像进行特征提取及形态学操作等，使其成为二值图像。(* Note: This function will be images (paired function matching) operation. Note that this procedure require image feature extraction and morphological operations, making it a binary image.)

一种基于non-sample的纹理合成demo，程序性能还有待优化，效果还不错.(texture synthesis demo.)

基于OPENCV的SIFT特征提取与匹配算法。包含完整的从图像高斯金字塔、DOG、空间极值点提取、关键点描述、KDtree匹配等关键步骤的全部函数实现，对全面深入理解Lowe的SIFT算法有莫大帮助。程序运行前须安装（1）OpenCV: http://opencvlibrary.sourceforge.net （2）SIFT: http://web.engr.oregonstate.edu/~hess/index.html，并配置其环境参数。(OPENCV the SIFT-based feature extraction and matching algorithm. Contains a complete Gaussian pyramid from the image, DOG, space extremum point extraction, description of key points, KDtree matching key step in the realization of the full function of the comprehensive and in-depth understanding of Lowe s SIFT algorithm of tremendous help. Program to run before the installation of (1) OpenCV: http://opencvlibrary.sourceforge.net (2) SIFT: http://web.engr.oregonstate.edu/ ~ hess/index.html, and configure the parameters of their environment.)

说明：  利用vc++实现avi文件图像截取，avi图像即视屏图像(Use vc++ Achieve avi file image capture, avi video image that is, images)

Moravec算子，实现对数字图像处理中的点特征提取，可用于图像拼接，特征提取，三维点生成(Moravec operator, the realization of digital image processing in point feature extraction, can be used for image stitching, feature extraction, 3D point generation)