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利用随机霍夫变换进行圆的检测，matlab编写(Randomized Hough transform for circle detection, Matlab prepared)

图着色问题（Graph Coloring Problem, GCP）又称着色问题，是最著名的NP-完全问题之一。路线着色问题是图论中最著名的猜想之一。(Graph coloring problem (Graph Coloring Problem, GCP), also known as coloring problem, is the most famous NP-complete problems. Line graph coloring problem is one of the most famous conjecture.)

VC++图像平滑处理+程序源码，实现图象的平滑（去噪声），锐化功能，测试时请在C盘下放一个测试用的Bmp图片，路径：C: est.bmp，没有的话没法测试。如上图所示是水平平滑处理，可以对比下，不过感觉颜色失真了，有兴趣的看一下。命令行编译过程如下： 　　vcvars32 　　rc bmp.rc 　　cl smooth.c bmp.res user32.lib gdi32.lib(VC++ image smoothing+ program source code, to achieve a smooth image (to noise), sharpening function in the C drive when testing a test of decentralization Bmp picture, path: C: test.bmp, no words can not test . Is shown above the level of smoothing, you can compare the next, but the feeling of color distortion, interested look. Command-line compiler as follows: vcvars32 rc bmp.rc cl smooth.c bmp.res user32.lib gdi32.lib)

基于MRF模型的变化检测算法仿真 MRF建模用于SAR去噪，再通过EM算法实现变化检测(MRF model-based change detection algorithm simulation)

高光谱图像的分类，适合各种光谱数据或者RGB图像。只需要调整输出路径就好了。(Hyperspectral image classification, for a variety of spectral data or RGB images. Only you need to adjust the output path just fine.)

遥感图像分类工具箱，包含多种基于支持向量机分类器的主动学习算法(active learning toolbox, used for remote sensing data classification, includes most popular svm-based active learning algorithms.)

使用改进的点锐度算法对不同程度的模糊图像进行清晰度评价。(The improved algorithm of point sharpness is used to evaluate the blurred image in different degree.)

IDL编程：tif图像批量layerstacking，并保留原有地图投影。使用时只需要修改输入和输出路径。(IDL programming: tif image batch layerstacking, and retain the original map projection. Only need to modify the input and output paths use.)

多类 kmeans 图像分割，基于灰度的图像分割。(Kmeans image segmentation, segmentation based on gray-scale images.)

从一个模式识别toolbox中摘取的计算zernike不变矩的源代码，结果为图像的n阶m重zernike不变矩(From a pattern recognition toolbox extracted Zernike moment invariants calculation of the source code, the results of image re-n-order m Zernike moment invariants)