demo

这是我做的一个二维傅里叶变换的程序，可以对图像进行2DFFT变换得到频谱图，并利用2DIFFT得到原图像(I do a two-dimensional Fourier transform procedure, 2DFFT transform spectrogram image and utilize 2DIFFT original image)

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. )

做项目时写的关于相机图像采集、控制、图像处理、坐标计算、坐标显示等功能的小软件(Do item written on the camera image acquisition, control, image processing, coordinates of the calculation, the coordinates show features such as small software)

能够计算傅里叶描述子，并对图像进行重构，实现对目标图像和源图像的辨认(Fourier descriptors can be calculated, and the image reconstruction, image and the source image to target identification)

online random forest 在线随机森林做跟踪和分类的代码(online random forest-line tracking and classification random forest to do the code)

将图片转化为BMP位图，然后通过逐行扫描识别图片中的数字。(A picture into a BMP bitmap, and then through the progressive scanned image in the figure.)

CT（computer tomography ）图像重建算法，FBP，是目前商用CT的主流重建算法(computer tomography reconstruction algrithm)

直线检测 Visual C++编写 用于图像处理(line segment detection)

光流法、帧间差分法、高斯背景模型差分法，在opencv环境下实现运动目标检测(moving objective detection matlab)

这本是用VC++来实现图像处理的书藉,对于学习图像处理的来说是非常有用的.(This is VC++ to realize image processing books, for learning image processing is very useful.)