ImgHazeRemoval_Test

遥感图像处理源代码，包括遥感影像读入、几何校正、影像重采样等等(Remote sensing image processing code)

利用形态学，霍夫（Hough）变换，实现畸变QR码的4个角点的定位。(To correct the distortion of the QR code,use morphology operation, Hough transform, to locat the positioning of the four corner points)

应用Intel® JPEG Library v1.5处理图像的例子(Using Intel® JPEG Library v1.5 to process image.)

源码包括了常用的图像处理方法，代码详细，适合初学者(Source code, including the commonly used image processing method, the code in detail, suitable for beginners)

线性插值射线追踪法，设置模型为一三层模型，范围100m×100m(Linear interpolation ray tracing method, set the model for a three-tier model, the range 100m100m)

基于VC++的图像处理类，可以用于bmp文件的读写，显示(Based on the image processing VC++ classes that can be used to read and write bmp files, display)

说明：  实现了图像的打开功能，并能实现图像打开时的扫描，渐进，马赛克等功能(To realize the image of the open function, and can achieve image scans open, progressive, mosaic and other functions)

说明：  基于力场分布的图像处理源程序。包括基于力场的图像分割、边缘检测等。(Distribution of image processing based on force field source. Include force field-based image segmentation, edge detection.)

图像处理程序中图像处理多运动目标程序，完整程序。下载就能用(Image processing program, image processing of multiple moving targets program, complete the program. Download will be able to use)

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. )