Source-code

基于vc++6.0的SURF算法的程序代码，可以直接运行(Based on the SURF algorithm for vc++6.0 program code can be run directly)

本代码主要给出了激光粒度仪颗粒散射光强分布以及4种粒度反演算法，以及4种算法之间的比较。四种反演算法为：TSVD、Chaine、Tikhonov和l1正则化。(The code gives the Zetasizer particle scattering intensity distribution, and four kinds of particle inversion algorithm, as well as a comparison between the four algorithms. Four kinds of inversion algorithm is: TSVD, Chaine, Tikhonov and l1 regularization.)

New Tracking Algorithm for Wireless network

说明：  实现对图像的归一化处理，为图像进行水印嵌入等操作打下基础(The realization of the normalized image processing, for image watermark embedding operation, such as laying a foundation)

说明：  Z. Liang, J. Xu, D. Zhang, Z. Cao, L. Zhang, "A Hybrid L1-L0 Layer Decomposition Model for Tone Mapping," in CVPR 2018.

将经过二值化的车道线图利用hough变换提取车道线(After binarization the lane line graph using hough transform to extract lane)

该软件可实现图像间格式的转换,主要实现: (e)ps,bmp, jpg, png,tif,gif, psdi图像格式之间的转换(The software enables format conversion between images, the main achievement: (e) ps, bmp, jpg, png, tif, gif, psdi image format conversion between)

说明：  sift算法实现的图像匹配程序，使用matlab编写的，多用于图像拼接，融合等领域。(The image matching program implemented by SIFT algorithm is written by MATLAB, and it is mostly used in image splicing, fusion and other fields.)

MAD相似性度量准则的改进，实现模板匹配程序(MAD similarity measurement criteria to improve and achieve template matching procedures)

（1）计算图像中每个像素点的LBP模式(等价模式,或者旋转不变+等价模式)。 （2）然后计算每个cell的LBP特征值直方图，然后对该直方图进行归一化处理(每个cell中，对于每个bin,h[i]/=sum,sum就是一副图像中所有等价类的个数)。 （3）最后将得到的每个cell的统计直方图进行连接成为一个特征向量，也就是整幅图的LBP纹理特征向量； 然后便可利用SVM或者其他机器学习算法进行分类识别了。((1) calculate the LBP pattern of each pixel in the image (equivalent mode, or rotation invariant + equivalent mode). (2) then the LBP eigenvalue histogram of each cell is calculated, and then the histogram is normalized (for each cell, for each bin, h[i]/=sum, sum is the number of all the equivalent classes in a pair of images). (3) finally, the statistical histogram of each cell is connected into a feature vector, that is, the LBP texture feature vector of the whole picture. Then, SVM or other machine learning algorithms can be used for classification and recognition.)