小目标视频

Image analysis to create a histogram in python language

提取并显示鼠标所在图像点的颜色，C++精选学习源码，很好的参考资料。(To extract and display the image color, select learning C++ source code, a good reference.)

说明：  超分辨率图像重建。具有非常好的效果，程序效率较高，有完整的注释和说明文档。(super-resolution image reconstruction. Very good results, the higher the efficiency, integrity of the Notes and documentation.)

点云特征提取 详细 实用 经典的讲述过程及方法(Point Cloud Feature Extraction practical details about the processes and methods of classic)

基本图像处理用C++的实现。包括平移旋转翻转边缘提取canny算子等(The basic image processing with C + +.)

包括常用的IHS,PCA 加权图像融合三种算法的Matlab源代码(Which are used in the IHS, PCA-weighted Image Fusion Algorithm three Matlab source code)

图像配准，首先实现了简单的图像预处理，然后根据两种不同的配准准则，互信息和边交互方差作图像配准(Image registration, first of all to achieve a simple image pre-processing, and then two different registration criteria, mutual information and edge interaction variance for image registration)

另一款BP/TP使用的SVGA图形模式程序。效果也不错(Another BP/TP use SVGA graphics mode procedures. The results would be good)

分块压缩感知中稀疏表示增加方向性提高重构质量(Block compression to increase directional to improve the reconstruction quality perception in sparse)

说明：  采用模糊C均值聚类算法求到欧式距离和方差，对数据集（特征+标签）进行分类并得到分类准确率(The Euclidean distance and variance are calculated by fuzzy c-means clustering algorithm, and the data set (feature + label) is classified and the classification accuracy is obtained)