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从Cbitmap派生的位图类，可通过指定一种颜色把一幅位图变透明，而它的使用差不多同Cbitamp一样简单。类中包含了两个文件：CISBitmap.cpp和CISBitmap.h，使用时附加进工程，可快速实现BMP位图图像的透明处理。(Cbitmap derived from the bitmap type, you can specify a color by a bitmap becomes transparent, and it s almost as simple as using the same Cbitamp. Class contains two files: CISBitmap.cpp and CISBitmap.h, into the use of additional works can be quickly processed to achieve a transparent bitmap BMP images.)

这是用C++实现图像立体匹配的一个完整的论文代码，主要特性是提出了一种全新的跨规模代价聚合方法，适合对于图像的立体匹配有一定基础的人学习(Cross-Scale Cost Aggregation for Stereo Matching)

Pyramid methods in image processing

三维激光点云配准是点云三维建模的关键问题之一。经典的 ICP 算法对点云初始位置要求较高且配准 效率较低，提出了一种改进的 ICP 点云配准算法。该算法首先利用主成分分析法实现点云的初始配准，获得较好 的点云初始位置，然后在经典 ICP 算法的基础上，采用 k － d tree 结构实现加速搜索，并利用方向向量夹角阈值去除 错误点对，提高算法的效率。实验表明，本算法流程在保证配准精度的前提下，显著提高了配准效率。 (Three-dimensional laser point cloud registration is one of the key three-dimensional point cloud model. High classical ICP algorithm to the initial position of the point cloud registration requirements and low efficiency, proposed an improved ICP point cloud registration algorithm. Firstly, the use of principal component analysis of the initial point cloud registration, get a better initial position of the point cloud, then the basis of classical ICP algorithm using k- d tree structure to achieve speed up the search, and using the direction vector angle the removal of the threshold point error and improve the efficiency of the algorithm. Experiments show that the algorithm processes to ensure the accuracy of registration under the premise, significantly improve the efficiency of registration.)

这块程序是用来求取圆面和矩形面积的，分为几个子程序。(This procedure is used to strike a round face and a rectangular area, divided into several subroutines.)

原创基于c++语言编程实现了MC算法在三维图像处理中的应用，以及有许多二维图像到三维图像表面的重建过程算法。通过VC2008，编译已通过。(I have realized MC algorithm about the application of processing 3-D image based on C++ language also realised the technology on image surface reconstruction from 2-D to 3-D image.They are all compiled successfully using VS2008)

根据D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis 以及 C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision.这两篇文献提供的方法编写的图像分割代码，作者是 Chris M. Christoudias, Bogdan Georgescu，代码经我看了后加了丰富的中文注释，希望可以给各位带来阅读上的方便。 基于meanshift的聚类分割方法包括滤波、区域融合等操作，通过调整sigma和sigmar来调整分割效果。(According to D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis, and C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision. These two documents prepared by the methods provided by image segmentation code , the author is Chris M. Christoudias, Bogdan Georgescu, after I read the code, add a rich Chinese notes, hoping to bring you the convenience of reading. Segmentation method based on clustering meanshift including filtering, regional integration and other operations, and by adjusting the sigma sigmar to adjust segmentation results.)

使用GDAL库，用于遥感影像的特征点提取(Using the GDAL library, used for remote sensing image feature point extraction)

读取图像，将RGB图像转化为灰度图像，显示并保存(The RGB image is transformed into gray image)

基于meanshift/camshift的视频运动目标跟踪实现，通过鼠标手动选择跟踪目标。基于HSV空间模型，可手动调节H S V的阈值，显示前景、背景、反响投影图。开发工具是VS2008、OPENCV.(Based meanshift/camshift video moving target tracking achieved manually using the mouse to select the target track. HSV space model, you can manually adjust the threshold HSV, showing foreground, background, reaction projection. Development tools are VS2008, OPENCV)