pianzhen

说明：  边缘检测算法 速度快 你一定会满意的。以前是要收费的。现在免费给你们。 源码经过测试真确无误。 (edge detection algorithm faster you will surely satisfied. Prior to the charges. Now free to you. Source tested truthful.)

均值滤波去噪声程序，效果显著，已经通过调试(Mean filter to the noise process, achieved significant results, have been through the debugging)

说明：  声呐或者雷达系统发射信号后，通过波束形成算法对两个目标（方位分别为theta1、theta2）回波进行仿真，经过相位补偿，可以看出图像有两个波峰，波峰处指向性函数峰值最大，峰值所对应的的角度值即为目标的方位角。所以该程序对数字波束形成（DBF）的原理进行了仿真，适合初学者掌握阵列信号处理中数字波束形成的原理。(After the sonar or radar system transmits the signal, the echo of the two targets (the azimuth is theta1 and theta2 respectively) is simulated by the beamforming algorithm. After the phase compensation, it can be seen that the image has two peaks, the peak of the directivity function is the largest, and the corresponding angle value of the peak is the azimuth of the target. So the program simulates the principle of DBF, which is suitable for beginners to master the principle of DBF in array signal processing.)

很好的解析bmp图片的源代码，很不错的初学者的例子，换页大家下载(Very good analytical bmp image of the source code, it is a good example for beginners, for everyone to download page)

基于阈值分割的运动车辆检测跟踪，在视频中按灰度阈值不同进行图像分割，并标记结果。(Threshold-based segmentation to track the movement of vehicles detected in the video by a different gray level threshold for image segmentation, and mark the results.)

使用Matlab生成一维光栅条纹，可用于结构光三维重建。(Matlab Generate One Dimensional Grating)

说明：  实现直方图规定化的函数和直方图均衡化的函数(Histogram specification to achieve the function and the histogram equalization function)

说明：  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.)

基于改进遗传算法的单阈值图像分割方法，该方法在基础遗传算法的基础上进行了改进(Application of Basic Genetic Algorithms in Image Segmentation)

在自适应中值滤波的基础上，采用均值与方差得到一个阈值，来判断极值点是不是噪声点！(On the basis of adaptive median filtering, a threshold is obtained by means of mean and variance to determine whether the extreme point is a noise point!)