CTImageReconstruction

This is a Scaling function definition Image cutoff ratio for H = 3

数字图像处理，对彩色图像的拉普拉斯算子锐化以及梯度算子锐化的比较，VC/MFC实现。(Digital image processing, color image of the Laplacian and the gradient operator sharpening sharpening comparison, VC/MFC implementation.)

说明：  基于各种算法的运动视频背景消除。使用opencv工具库，通过读取视频文件，处理视频，最后存储。(Background Subtract Algorithm)

三维点云配准kd-tree搜索算法，用于特征点的搜索匹配(3 d point cloud registration kd- tree search algorithm, is used to search of feature point matching)

连续投影算法的Matlab程序 下载后可以直接使用(Successive projections algorithm )

自己毕业设计做的改进的基于某vc视频处理框架代码的重心多目标跟踪代码(The center of gravity of a vc video processing framework code-based target tracking code own graduation design improvements do)

运用在fluent中的udf，解决边界正弦运动的情况，非常珍贵(Border harmonic vibration UDF, use them in fluent, very precious resource)

用于图像检测的正态分布计算的c代码实现，现在将这个函数写在头文件中了(Normally distributed computing for image detection of the c code, this function will now be written in the header file in the)

说明：  压缩感知的经典代码，包括观测，稀疏表示，重建，其中观测用的高斯观测矩阵，稀疏用的DCT，重建用的OMP算法(Compressed sensing of the classic code, including observations, sparse representation, reconstruction, observed with a Gaussian observation matrix, sparse use of the DCT, re-use of the OMP algorithm)

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. )