FCMLSM

一种基于形貌特征识别圆形的方法，通过拟合圆方程来实现的经典hough变换方法(A method of Circle Recognition Based on morphological features is introduced. The classical Hough transform method is implemented by fitting the circle equation.)

说明：  实现了双线性插值、三次样条插值、B样条插值和最大阶次优化差值等传统多项式图像插值办法(Traditional polynomial image interpolation methods such as bilinear interpolation, cubic spline interpolation, B spline interpolation and maximum order optimization difference are realized.)

采用形态学进行开闭运算，及纹理等分割方法。(The Methods of Image Segmentation on Application and Analysis of Remote Sensing Images)

sar图像处理的滤噪小程序 用于图像的增强。(sar Denoising image processing applet for image enhancement.)

最大熵，求概率密度分布。目前的程序问题，是初始值选取需要完善。希望高手能解决。(The maximum entropy seeking probability density distribution. The current program, the initial value selected to be perfected. Expert can solve.)

对输入的一张彩色图像，自己写代码实现Harris Corner 检测算法： 1. 不能直接调用OpenCV 里面与Harris 角点检测相关的一些函数； 2. 只能用C/C++，不能用其他语言； 3. GUI 只能用自带的HighGUI，不能用QT 或其他的； 4. 平台可以用Windows， Linux, MacOS； 5. 显示中间的处理结果及最终的检测结果，包括最大特征值图，最小特征值图，R 图（可以考虑彩色 展示），原图上叠加检测结果等，并将这些中间结果都输出成图像文件； 6. 命令格式： “xxx.exe 图片文件 k 参数(=0.04) Aperture_size(=3)”。(The input of a color image, write your own code to achieve Harris Corner Detection Algorithm: 1. Can not be called directly inside OpenCV some functions associated with the Harris corner detection 2. To only use C/C++, can not be used in other languages 3. GUI only with their own HighGUI, can not use QT or other 4. The platform can be used Windows, Linux, MacOS 5. Display intermediate and final results of the test results, including the largest eigenvalues diagram, the minimum feature value graph , R chart (you can consider color display), picture superimposed on the test results, etc., and these intermediate results are output as an image file 6. Command Format: " xxx.exe picture file k parameters (= 0.04) Aperture_size (= 3 ). " )

红外和可见光图像配准和融合算法，采用仿射变换(Registration and fusion of infrared and visible images)

采用了Harrtraining和离子滤波算法实现了拥挤人群人头计数，非常有用。VC++和Opencv开发，采用Oepncv中的Harrtraining训练一个分类器即可运行(Human detection and tracking in high density crowds is an unsolved problem. Standard preprocessing techniques such as background modeling fail when most of the scene is in motion. We integrate human detection and tracking into a single framework, and in- troduce a conrmation-by-classication method to estimate condence in a tracked trajectory, track humans through occlusions, and eliminate false positive detections.)

这是一个印度人编的程序，用于两图像单应矩阵和变换结果的求取(This function estimates 2D-2D plane projective homography between two perspective images using Direct Linear Transformation, RANSAC and Levenberg Marquardt optimisation.)

说明：  内含多种图像去噪的方法，包括高斯，椒盐噪声等问题(Contains a variety of image denoising methods, including Gaussian, salt and pepper noise and other issues)