AviPclass

基于openvc平台的，用vc语言实现的，根据输入的图像，对图像进行腐蚀操作。(Based on openvc platform, with vc language, according to the input image, the image erosion operation.)

在vs平台下利用opencv程序，可以处理图像的膨胀、腐蚀以及开闭运算。(Availability v Understanding use of open platform opencv degree, permissible processing, swelling, corrosion and opening and closing operation)

网格简化， 将复杂的带有很多细节的物体的三维立体网格进行任意比例的简化，使得其减少点和面片的数量并保持物体的基本特征，以达到加快图像显示及压缩文件的效果。(Mesh simplification, the complex three-dimensional grid with many of the details of the object simplified in any proportion, such that it reduce the number of points and surfaces of the sheet and keep the basic characteristics of the object, in order to achieve the speed up of the image display and the effect of the compressed file .)

小球沿斜线运动,可以扩展到其他程序中，第一次上传，谢谢。(a ball along with a line.)

基于区域的稠密立体匹配方法（论文） 关键词：种子点；区域增长；稠密匹配(Based on Region Dense Three—dimensional Match Method)

说明：  在VC中实现了使用Moravec算子对遥感影像进行特征点的提取，缺点是速度较慢。不过提取效果不错！(Implemented in VC using Moravec operator of remote sensing images feature point extraction, the disadvantage is slow. However, extracting good results!)

用大整数乘法来计算两个n位二进制数相乘(With large integer multiplication to calculate the multiplication of two n-bit binary number)

卡尔曼滤波是一种数据处理方法，它是一种线性最小方差无偏估计准则，基于系统 状态估计和当前观测，通过引入状态空间而获得的新的状态估计.本篇论文陈述了卡尔曼滤 波的基本思路和算法；并通过仿真，显示卡尔曼滤波的功能，以及如何用它来跟踪方向确定、速度恒定的飞行器。 (Kalman filter is a data processing method, which is a linear minimum variance unbiased estimation criteria, based on system state estimation and the current observations, obtained by introducing the state space of the new state estimate of the Kalman filter thesis statement the basic ideas and algorithms and through simulation, shows Kalman filtering functions, and how to use it to keep track of the direction determined constant speed aircraft.)

用C++编写的产生文章的程序，方便有需要的人(C generated articles prepared by the procedures that are accessible to people in need)

各种图像处理技术举例。其中原代码可以直接使用，非常不错。(various image processing technology, for example. The original code which can be used directly, very good.)