SIFT_VC.lib

说明：  一个用VC++6.0编的程序例子，实现远程屏幕图像的传输 (a VC 6.0 Provision procedures example, remote screen image transmission)

VapourSynth-BM3D-master BM3D算法的原创代码，运行速度超快，参考文献《Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering》(VapourSynth-BM3D-master BM3D original algorithm code, run super-fast, Reference " Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering" )

数字图像处理第二版英文版（冈萨雷斯）.pdf(Digital Image Processing Second Edition English (Gonzalez). Pdf)

说明：  标定用的c++程序，可以用来标定得到相机的内参矩阵和畸变参数。(Calibration using matlab toolbox, can be used to calibrate the camera s internal control matrix image obtained.)

利用回转窑生产氧化铝的工艺中，提出了一种新的基于SVR（支持向量回归）的烧成带温度软测量方法。即首先对从回转窑采集到的烧结图像进行预处理，消除噪声的干扰；然后利用大津方法分割出物料区和火焰区，并提取这些区域的图像特征；其次利用基于SVR方法建立的烧成带温度模型计算温度值；参数计算.(The use of alumina rotary kiln production process, a new-based SVR (support vector regression) of the burning zone temperature soft measurement method. That is first collected from the rotary kiln sintering image pre-processing to eliminate noise interference Otsu method and then use the materials division of the district and flame zones, and extraction of image features in these regions SVR-based method followed by the establishment of the burning zone temperature model temperature parameters.)

1.打开左右两张影像2.Harris算法提取同名点3.显示提取同名点（若要进行下一步匹配则不建议显示，这里只是用于查看是否提取出）4.相关系数匹配（只在找出的同名点内匹配）5.LSM最小二乘匹配（先进行粗匹配，再精匹配）(1 Open the left and right images 2.Harris algorithm to extract two tie points 3 shows the extraction of corresponding points (not recommended to proceed to the next match show, here is used to see if extracted) 4. Correlation coefficient matching (just looking match within a point of the same name) 5.LSM least squares matching (rough first match, then fine match))

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. )

VC编写的位图图像处理的源代码，包括了增强、变换等内容(VC prepared bitmap images deal with the source code, including the enhanced transformation, etc.)

图形图像处理中的平滑处理，可以实现部分的功能，但是还可以继续完善(Graphic image processing smoothing, can achieve some of the functions, but can also continue to improve)

Image processing using sobel operator