source_code_TBM_activecontours.tar

使用GDAL库，用于遥感影像的特征点提取(Using the GDAL library, used for remote sensing image feature point extraction)

一种简单高效地基于压缩感知的跟踪算法。首先利用符合压缩感知RIP条件的随机感知矩对多尺度图像特征进行降维，然后在降维后的特征上采用简单的朴素贝叶斯分类器进行分类。该跟踪算法非常简单，但是实验结果很鲁棒，速度大概能到达40帧/秒(A simple and efficient tracking algorithm based on compressed sensing. Firstly, with the random sensing matrix compressed sensing RIP conditions for multi-scale image feature dimension reduction, and then use the naive Bias classifier simple classification in the feature reduction after the. The tracking algorithm is very simple, but the results are robust, speed can reach 40 frames per second)

一种二值图像连通区域标记方法，能用于目标跟踪，我已经应用过，效果不错。(It is a new connected componet labeling algorithm for binary image,and can be used in object tracking. It is effective to be proved.)

实现bmp位图的图像放大缩小，包含整个mfc的源码文件。(Achieve bmp bitmap image zoom, contains the entire mfc source files.)

基于Sift算法开发商标图案匹配程序，(1)各个CBIR模块及其技术； (2)Sift算法及其在图像匹配、目标识别中的应用； (3)Sift算法在图像检索中的应用。 (Sift algorithm development based on pattern matching program mark (1) Each CBIR module and its technology (2) Sift algorithm and its application in image matching, object recognition application (3) Sift algorithm in image retrieval applications.)

集成ITK、VTK、MFC读取DICOM的代码，建成win32程序即可。运行完美(Integrated ITK, VTK, MFC to read DICOM code, built win32 program can. Works perfect)

说明：  利用GMS对特征点匹配进行约束，降低误匹配率，代码包含python版本，C++版本，matlab版本。(GMS is used to constrain the matching of feature points to reduce the error matching rate. The code includes Python version, C + + version and Matlab version.)

图像处理软件，功能齐全，简单，而且逻辑清除，很适合图像处理编程初学者(Image processing software, full-featured, simple, clear and logical, it is suitable for image processing programming beginners)

论解读DICOM医学图像文件及其显示的VC++实施方法 是一份比较新的讨论dicon的vc实现方法的文章(read DICOM medical images and documents show that the implementation of the VC is a relatively new discussion di vc con method of the article)

可以将256色度级的图像转化为灰度图象，挺值得新手学习一下的，希望大家能喜欢(256 chroma level images can be converted to grayscale images, very worth novice to learn about, and I hope you like)