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毕业设计的程序 用VC++6.0做的 主要是测试几个边缘检测算子的效果(Graduate programs designed to use VC++ 6.0 to do is to test several of the main edge detection operator effect)

说明：  可以实现旋转，错切，各种投影图，透视图。是学习三维变换很好的原始参考资料(Can rotate, shear, a variety of projection, perspective. Is to learn the original three-dimensional transform good reference)

本程序实现了对影像特征点自动提取，利用Morevac、Forstner、Harris3个经典算子。在此基础上利用相关系数法实现影像自动匹配，并且引入最小二乘平差，使匹配点精度有所提高。 在搜索点过程中，利用了核线影像特性，对二维影像搜索使用了爬山法启发式搜索。对大数据量影像采用影像金字塔结构处理。 1、使用GDAL库读取影片，支持TIFF、PNG、JPEG、JPG、BMP、GIF、IMG格式读取。使用GDI绘图。 2、防止大数据量绘图视图闪烁，图片显示采用双缓存技术。 3、保存视图数据为图片文件，支持TIFF、PNG、JPEG、JPG、BMP、GIF格式保存。 4、TreeCtrl控件、ListCtrl控件的基本操作。 5、MFC单文档程序视图通讯、更换视图、视图分割。(This program of image features automatic extraction point, use Morevac, Forstner, Harris3 a classic operator. Based on the correlation coefficient method using the image matching, realization and introducing least squares adjustment, the matching point to improve precision. In the search process, the use of the image characteristics of nuclear line, 2d image search using the heuristic method of climbing. For large quantity of data using image processing image pyramid structure. 1, using film, read GDAL repository support JPEG, TIFF, PNG, GIF, BMP, JPG, read IMG format. Use GDI drawing. 2 and prevent large amount of data, drawing view pictures showed adopt double caching techniques. 3, save for the image file, views data support JPEG, TIFF, JPG, PNG, GIF, BMP format. 4 and TreeCtrl controls, the basic operation ListCtrl controls. 5 and MFC single document procedure view communication, replace view, view.)

实现了灰度共生矩阵，并应用到了几张图片上。 C++ 和OPENCV 代码。 图像处理(GLCM achieved and applied to a few pictures. C++ and OPENCV code. Image Processing)

HOG adaboost pedestrian-detect

MRF代码实现,visual C++ 代码，不错，可以尝试(an implementation of MRF)

在图像传输时，常常需要对图像进行压缩，这些代码用来对图像进行压缩编码。(In the image transmission, it is often the need for image compression, the code used to image compression.)

医学图像配准，医学图像2D_3D配准，基于vc++开发。(The registration of pre-operative volumetric datasets to intra-operative two-dimensional images provides an im- provedway of verifying patient positionandmedical instru- ment location. In applications from orthopedics to neuro- surgery, it has a great value in maintaining up-to-date in- formation about changes due to intervention. We propose a mutual information-based registration algorithm which es- tablishes the proper alignment via a stochastic gradient as- centstrategy. Ourmaincontributionliesinestimatingprob- ability density measures of image intensities with a sparse histogrammingmethodwhichcouldlead to potentialspeed- up over existing registration procedures and deriving the gradient estimates required by the maximization procedure. Experimental results are presented on fluoroscopy and CT datasets of a real skull, and on a CT-derived dataset of a real skull, a plastic skull and a plastic lumbar spine seg- ment.)

计算机图形学基础算法z-buffer， 实现隐藏面消除(Computer graphics based algorithm z-buffer, to achieve hidden surface removal)

一个很实用图象处理原码(a practical source image processing)