LSM_Match

利用opencv工具包的图像缩小程序利用opencv工具包的图像缩小程序利用opencv工具包的图像缩小程序(image shrink with opencv image shrink with opencv image shrink with opencv)

第8章 图象的检测及模板匹配 图象的分割与检测(识别)实际上是一项非常困难的工作。很难说清楚为什么图象应该分割成这样而不是那样。(Chapter 8 Detection of image template matching and image segmentation and detection (recognition) is actually a very difficult task. It is hard to say clearly why the image should be divided into such and not as.)

人脸检测与跟踪，我的毕业论文，使用我自己改进的ADABOOST和CAMSHIFT算法,附带我的毕业论文,opencv1.0或以上自己配置(face detection use adaboost and camshift algorithm，relevant paper enclosed，OPENCV1.0 is necessary)

1.打开左右两张影像2.Harris算法提取同名点3.显示提取同名点（若要进行下一步匹配则不建议显示，这里只是用于查看是否提取出）4.相关系数匹配（只在找出的同名点内匹配）5.LSM最小二乘匹配（先进行粗匹配，再精匹配）(1 Open the left and right images 2.Harris algorithm to extract two tie points 3 shows the extraction of corresponding points (not recommended to proceed to the next match show, here is used to see if extracted) 4. Correlation coefficient matching (just looking match within a point of the same name) 5.LSM least squares matching (rough first match, then fine match))

photoshop的各个效果的详细介绍，方便研究photoshop的各种算法，值得一看啊！！(photoshop detailed description of the various effects, photoshop various algorithms to facilitate research, worth ah! !)

摄影测量源码，连续法的相对定向算法，提供实验数据和程序(Photogrammetric source, the relative orientation algorithm of the continuous method, the experimental data and procedures)

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.)

利用k—mean算法根据U、V进行聚类分块，最后完成图像分割，分割出得块用不同的灰度等级表示出来。(K-mean algorithm to cluster sub-blocks according to the U, V, to finalize the image segmentation, segmentation have blocks with different gray levels represented.)

高光谱图像的地物分类技术，对光谱分析并对比检测出地景的算法(Fifth hyperspectral image classification techniques, algorithms for spectral analysis and contrast detect landscapes)

模式识别经典方法之一 K均值算法（KMeans）进行图像分割 有完善的图形界面 可以通过柱状图的形式动态展示聚类程序(One of the classical method of pattern recognition K means algorithm (KMeans) for image segmentation has improved graphical interface can be dynamically displayed in the form of histogram clustering procedure)