Segmentation

说明：  编程实现对bmp图像最大值，最小值，标准差，熵，各灰度值频率的计算(Programming to calculate the maximum value, minimum value, standard deviation, entropy and gray value frequency of BMP image)

这个matlab程序实现图像的任意角度的顺时针旋转。(The matlab program images at any angle of clockwise rotation.)

基于VisualC_和DCMTK的医学DICOM图像显示与调窗,同时在MFC 下完成鼠标拖动进行窗宽/窗位的调节(Medical image of DICOM VisualC_ and DCMTK display and window based on, at the same time in MFC complete the mouse to drag the window width/window regulator )

斯坦福大学的姚邦鹏开发的一个图像分类算法，使用random forest实现了图像的精细区域描述，赢得了PASCAL VOC2011图像分类竞赛中的winner prize.经测试，程序完全可运行，且提供了MAC和Windows下的两种程序。(Image Classification: An Integration of Randomization and Discrimination in A Dense Feature Representation The goal of our method is to identify the discriminative fine-grained image region that distinguishes different classes. To achieve this goal we sample image regions from dense sampling space and use a random forest algorithm with discriminative classifier. Each node of the tree of random forest is trained and tested with fine-grained image patches combining the information from upstream nodes together. We implemented each node of the tree with a discriminative SVM classifier, which makes the node as a strong classifier. )

说明：  用于绘制节理面粗糙度风玫瑰图的Matlab程序，包含节理面粗糙度各向异性的案例数据！(Matlab program for drawing wind rose diagram of joint surface roughness, including case data of joint surface roughness anisotropy)

说明：  对遥感影像融合质量评价的程序，输出均值 标准查 信息熵 相关系数 光谱保真(To evaluate the fusion quality of remote sensing image, output the mean value standard to check the spectral fidelity of entropy correlation coefficient)

无监督分类方法，包括kmeans，som和fcm，非常好用(Unsupervised classification methods, including kmeans, som and fcm, very easy to use)

立体匹配，包括计算基本矩阵，极线校正，和SSD计算匹配点(Matching, including the calculation of fundamental matrix, epipolar correction, and SSD calculation of matching points)

本程序应用相位一致性进行边缘检测，较以往应用灰度信息进行边缘检测算法，该算法与光照无关，且抗噪声性能强(phase of the application process consistency edge detection, gray than in the past Application information edge detection algorithm, The algorithm has nothing to do with illumination, and strong anti-noise performance)

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