visual-cPP-image-process

计算机图形学中实现多边形平移，旋转，缩放变换。(Polygons in computer graphics to achieve translation, rotation, scaling transformation.)

说明：  使用gpu、cpu并行进行sift算子计算匹配，能够在原来的基础上加速处理，但对显卡要求较高，具体环境配置使用方法可以参照mannual(SiftGPU is an implementation of SIFT [1] for GPU. SiftGPU processes pixels parallely to build Gaussian pyramids and detect DoG Keypoints. Based on GPU list generation[3], SiftGPU then uses a GPU/CPU mixed method to efficiently build compact keypoint lists. Finally keypoints are processed parallely to get their orientations and descriptors. SiftGPU is inspired by Andrea Vedaldi s sift++[2] and Sudipta N Sinha et al s GPU-SIFT[4] . Many parameters of sift++ ( for example, number of octaves, number of DOG levels, edge threshold, etc) are also available in SiftGPU. The shader programs are dynamically generated according to the parameters that user specified. SiftGPU also includes a GPU exhaustive/guided sift matcher SiftMatchGPU. It basically multiplies the descriptor matrix on GPU and find closest feature matches on GPU. Both GLSL and CUDA implementations are provided. )

摄影测量的一个开源代码，内部含有后方交会、前方交会、相对定向、立体量测、像点匹配等功能源代码。(An Photogrametry open source project, including intersection, relative oriention, stereo measure, image matching source code.)

图像边缘检测，实现了几种边缘检测算法，像Roberts，Sobel，Prewitt，Canny等(Edge detection, edge detection algorithm to achieve several, such as Roberts, Sobel, Prewitt, Canny, etc.)

图形处理，Visual C++图形编程技巧与实例源代码3(Graphics Visual C++ graphics programming techniques and source code examples 3)

根据RBM深度网络（Hinton，2006）进行MINST手写文字的分类器的训练，利用训练得到的权值制作了这个小程序，通过这个程序可以看出训练结果对数据集内的测试样本和训练样本都能进行很好的识别，但是对其他的手写字体识别就没有那么好了。(According to RBM depth network (Hinton, 2006) conducted MINST handwritten text classifier training, using the training to get the right value to produce this small program, this program can be seen through the results of the training data set and the training sample test samples are can be well identified, but on the other handwriting recognition is not so good.)

生成四副条纹图，进行四步相移，并且进行相位解包裹，并以图片形式输出结果(Generate four fringes, were four-step phase shift and phase unwrapping, and output as a picture)

对图像进行纹理处理，为图像识别、目标跟踪创造条件。主要分析：惯性矩、熵以及局部平衡性。(The image texture processing for image recognition, target tracking and create conditions. Main analysis: moment of inertia, entropy, and local balance.)

Graph Cutshi是最近在计算机视觉中研究和应用比较多的优化算法，典型的用于stereo matching, image restortion, texture synthesis等应用，以上代码给出了graph cut，mean shift, 以及相关的ppm/pgm图像借口，本来是用于stereo matching的，已经把相关的matching的实现代码给去掉了。大家可以以此为平台做一些相关的研究和应用。 (Graph Cutshi recently in computer vision research and application of a relatively large number of optimization algorithms, typical for the stereo matching, image restortion, texture synthesis applications, the above code gives the graph cut, mean shift, and the associated ppm/pgm images an excuse, it is used for stereo matching, and has been related to matching the code to realize removed. U.S. can also be used as a platform to do some related research and applications.)

解决一些图像处理的小问题，具体的划分和问题，文件里有提到(Solve some small problems in image processing)