read_txt

说明：  基于角谱理论艾里光束的传播,该MATLAB程序，大体上模拟出了Airy光束的二维光强分布，并在此基础上利用角谱理论，编写出了其在二维平面内的传播，只需改变其中的参数就可以展示Airy光束的移动。在此基础上加上障碍物，可以得到Airy光束的自愈合特性等特殊性质(The matlab program, in general, simulates the two-dimensional light intensity distribution of Airy beam, and on this basis, using the angle spectrum theory, compiles its propagation in the two-dimensional plane, only changing the parameters can show the movement of Airy beam. On this basis, the self-healing properties of Airy beams can be obtained by adding obstacles)

说明：  python语言，三种阈值分割方式，简单阈值分割，自适应阈值分割，OTsu分割方式(Python language, three methods of image segmentation , simple threshold segmentation, adaptive threshold segmentation, OTsu segmentation)

基于CVI的二维码图像识别 QR Code的认识和识别(Awareness and recognition of the two-dimensional code image QR Code)

Camshift和MOG结合的目标检测与跟踪算法(An alg of detecting object with camshift and mog)

说明：  基于小波变换的图像融合用matlab实现的源代码(image fusion)

说明：  可以实现金字塔加速处理模板匹配，vs2015+opencv3.30.(The template matching can be accelerated by pyramid)

利用matlab进行图像数据的剪裁，需要提供需剪裁影像的中心点行列号；RMSE.m是计算均方根误差RMSE的程序。(Using MATLAB to tailor the image data, we need to provide the central point and row number of the image to be tailored. RMSE.m is a program to calculate the root mean square error RMSE.)

基于大津法和迭代法的图像二值化程序，相当于利用该方法进行了图像的分割，源码已调试，很好使！(Based on the Otsu method and iterative method of image binarization procedure is equivalent to using the method of image segmentation, source code has been debugging, very good to make!)

以python语言为平台，对机载激光雷达原始数据Las格式和txt格式进行读取，并根据信息熵确定维度特征计算的最佳邻域半径，最后计算得到最佳邻域半径和最佳维度特征值(Based on Python language, the Las format and TXT format of airborne lidar raw data are read, and the optimal neighborhood radius is determined according to the information entropy. Finally, the optimal neighborhood radius and the optimal dimension eigenvalue are calculated.)

逆透视变换的数学原理，在文档中有详细的逆透视变换的矩阵推导过程，但是没有代码，opencv逆透视变换代码可以看我发的另一篇资源。。。。。。。。。。。。。。。。。。(The mathematical principle of reverse perspective transformation, in the document there is a detailed matrix rendering process of the inverse perspective transformation, but there is no code, opencv reverse perspective transformation code can see another resource I sent)