keypointExtraction

本代码是基于数学形态学的多尺度多结构算子的腐蚀与膨胀算法(This code is corrosion and expansion algorithm based on mathematical morphology of multi-scale multi-structure operator)

说明：  使用python语言实现多张图像的拼接，并且处理拼接之后的裂缝和黑边。(Use python language to achieve splicing of multiple images, and deal with cracks and black edges after splicing.)

ISODATA算法是在k-均值算法的基础上，增加对聚类结果的“合并”和“分裂”两个操作，并设定算法运行控制参数的一种聚类算法,从而实现遥感影像的非监督分类(ISODATA algorithm is a clustering algorithm based on K-means algorithm, which adds two operations of "merging" and "splitting" of clustering results, and sets the operation control parameters of the algorithm, so as to realize unsupervised classification of remote sensing images.)

经典的基于距离变换的图像细化的骨架提取方法。(Classic based on distance transform refining skeleton extraction method. )

混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。通观整个高斯模型，他主要是有方差和均值两个参数决定，,对均值和方差的学习,采取不同的学习机制,将直接影响到模型的稳定性、精确性和收敛性。由于我们是对运动目标的背景提取建模，因此需要对高斯模型中方差和均值两个参数实时更新。为提高模型的学习能力,改进方法对均值和方差的更新采用不同的学习率 为提高在繁忙的场景下,大而慢的运动目标的检测效果,引入权值均值的概念,建立背景图像并实时更新,然后结合权值、权值均值和背景图像对像素点进行前景和背景的分类。(Gaussian mixture model using K (essentially 3-5) Gaussian model to characterize the features of each pixel in the image, in the image of the new frame for updated Gaussian mixture model, with each pixel in the image with a Gaussian mixture current model matching, if successful, determined that the point of the background points, otherwise the former attraction. Throughout the entire Gaussian model, he mainly has two parameters determine the variance and the mean, the mean and variance of the study, to take a different learning mechanism, will directly affect the stability, accuracy and convergence model. Since we are moving object extraction of the background modeling, so the need for the Gaussian model variance and mean two parameters real-time updates. In order to improve the learning ability of the model, an improved method for updating the mean and variance of different learning rates to improve in the busy scene, large and slow moving object detection results, the introduction of)

图像从背景图中提取 可以用来提取边缘，将背景图与图像分离(Images extracted from the background image can be used to extract the edge of the background map and image separation)

自己编写的字幕提取代码，matlab简单易用(Caption extraction)

matlab编写的harris程序,对初学者还是很有帮助的(harris program written in matlab, or helpful for beginners)

一个非常实用的las文件处理工具，可以实现很多功能，如读写las文件，分类，分块，抽稀，合并，生成边界线，生成DEM，点云高度归一化，数据格式转换，波形数据压缩等(A very useful the las file processing tools, you can achieve a lot of features, such as read and write las file classification block Rarefy merge to generate the boundary line, generated DEM point cloud height normalized data format conversion, waveform data compression, etc.)

这是一个有界差分方法进行分割的例子，对于学习数学图像处理的同学，有启发作用(This is a difference method has industry segmentation example, for image processing mathematics students, has inspired the role of)