chap01

一套基于VC++的遥感影象处理系统,可以实现空间域,频率域以及光谱的处理(yi tao ji yu VC++ de yaohan yingxiang chuli xitong)

基于halcon图像处理平台的相机标定算法，相当不错。。。。。(Halcon based image processing system camera calibration algorithm is quite good. . . )

指纹识别demo 演示方向图、roc曲线(fingerprint demo show orientation and ROC curve)

计算机图形学基础算法z-buffer， 实现隐藏面消除(Computer graphics based algorithm z-buffer, to achieve hidden surface removal)

包含基于VC++的各种图像、视频处理的源码如图像增强、灰度位图处理、图像平移旋转、bmp2txt等程序源码(Contains various images VC++ based video processing source code, such as image enhancement, grayscale bitmap processing, image translation and rotation, bmp2txt program source code, etc.)

Opencv处理图像，用ostu法实现图像的二值化(Opencv image processing, using ostu method to achieve image binarization)

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. )

处理Gamma乘性噪声的PPB方法，考虑了非局部patch的相似性，可处理SAR图像去噪。(The PPB method for multicative noise removal, which based on the Probabilistic Patch similarity.)

实现鱼眼图 圆形视场和全视场的校正、分为2幅图像、4幅图像、任意角度、任意位置的校正、全景图拼接等(Fish eye diagram of a circular field of view and full field calibration is divided into two images, four images at any angle, any position of the correction, and panoramic stitching.)

基于HOG的行人检测，作者的源代码有错误，现代码已经进行了改变，并可以调试通(Histograms of Oriented Gradients for Human Detection, the writer s code has some errors, and I have correct the errors, and the code is right under C++ buidler)