ruihuafudiao

使用K近邻算法对一个2维德样本集进行分类，样本集的分布为混合高斯分布。(K nearest neighbor to use a 2 Verde sample set for classification, the distribution of sample set for mixed Gaussian distribution.)

可以实现bmp图象的sobel边缘检测运算，并含有可图象重建功能。简单，易懂，使用了DIB接口，适合作数字图象处理的初学者作参考(Bmp images can be achieved sobel edge detection operator, and contains the reconstruction of functional images. Simple, understandable, the use of the DIB interface, suitable for beginners of digital image processing for information)

说明：  vc++调用matlab函数混合编程实现二值图像的区域标记。(vc++ call matlab function Matlab binary image of the regional markers.)

画图源程序-图像数据显示，可以对数据进行时间轴的曲线显示，也可以是空间轴的多维显示 (Paint source- the image data, the data can be curve shows the time axis, it can be multi-dimensional display space axis)

说明：  利用c++实现的PCA算法，直接对数据进行处理，适合初步学习(C++ implementation using PCA algorithm to process the data directly)

采用MFC，实现遥感图像的基本增强，滤波，变换等功能。还可以保存数据。(Using MFC, to achieve the basic enhancement of remote sensing images, filtering, transformation and other functions. You can also save data)

关于MC三维重建算法的二义性消除的文章，很好的消除了MC算法中的二义性(it s the article about Three-dimensional reconstruction algorithm to eliminate ambiguity in MC)

运动目标检测与跟踪，包括目标定位，匹配与跟踪!(moving target detection and tracking, including Target, matching and tracking!)

根据D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis 以及 C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision.这两篇文献提供的方法编写的图像分割代码，作者是 Chris M. Christoudias, Bogdan Georgescu，代码经我看了后加了丰富的中文注释，希望可以给各位带来阅读上的方便。 基于meanshift的聚类分割方法包括滤波、区域融合等操作，通过调整sigma和sigmar来调整分割效果。(According to D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis, and C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision. These two documents prepared by the methods provided by image segmentation code , the author is Chris M. Christoudias, Bogdan Georgescu, after I read the code, add a rich Chinese notes, hoping to bring you the convenience of reading. Segmentation method based on clustering meanshift including filtering, regional integration and other operations, and by adjusting the sigma sigmar to adjust segmentation results.)

说明：  PCL+ MFC+ Visualization 点云显示(PCL+ MFC+ Visualization)