DDE

基于分块的人脸图像超分辨率学习算法实验平台，利用学习到的训练集图像信息对低分辨率图像超分辨率，并可以查看超分辨率后的图像块匹配结果（用鼠标双击结果显示窗口中的实验图像），可以设置实验参数。(Block-based face image super-resolution algorithm for the experimental platform to learn, learning to use the training set of low-resolution image information super-resolution images and can view the image super-resolution block-matching results (double-click with the mouse results display window of the experimental images), the experimental parameters can be set.)

相机的单目标定，使用张正友标定法，可靠使用(The monocular camera calibration, using the zhangzhengyou calibration method, reliable use)

把视频分割成一帧一帧并且保存为图像，实现视频录制(Put the video into a frame of a frame and saved as image segmentation)

说明：  对给定图片求图片中的染色体个数。具体步骤：中值滤波方法，二值化处理，膨胀和腐蚀，开闭运算，求连通区的个数(Of a given picture for the picture of the chromosome number. Concrete steps: median filter method, binarization processing, expansion and corrosion, opening and closing operations, and the number of connected areas)

基于OpenCV实现的图像切割程序，通过程序中参数设置分块的数量和大小(The project is uesd to break an image into block)

我写的贝叶斯fusion的Visual C+++源码，简明易懂，提供参数说明 可直接使用。 (The Bayesian fusion the Visual C+++ of what I wrote source, easy-to-understand parameters can be used directly.)

对于二值图像进行labeling,求的对象个数，每个对象的像素数，中心点，长宽高矮值等(labeling for bianry image)

本程序可以使用图像处理算法对图片进行处理，对于一个含有各种物体的图片，如米粒，可以计算物体的个数。使用前请配置好opencv环境。希望对大家学习图像处理和opencv有所帮助...(This procedure can use the image processing algorithm for processing images for a picture with a variety of objects, such as a grain of rice, can calculate the number of objects. Configured before use opencv environment. We would like to learn opencv image processing and help ...)

稀疏矩阵的实例，讲述如何用稀疏矩阵进行实际的编程。本例是以超市购物为实际背景。(Examples of sparse matrix)

光线跟踪，计算机图形学的实验，实现的是消隐，光线之间的遮挡等(Ray-tracing, computer graphics experiments, realize that the hidden light, such as between the block)