eigen_decomposition

经典矩量法点匹配程序，重推导，注释说明详细(Classical point matching moment method procedure)

说明：  一、课题介绍 本设计为基于MATLAB的火焰烟雾火灾检测系统。传统的采用颜色的方法，误识别大，局限性强。结合火焰是实时动态跳跃的，采用面积增长率，角点和圆形度三个维度相结合的方式判断是否有火焰。该设计测试对象为视频，通过下一帧和上一帧的差异发现是否有火情，并可发出语音报警。本设计带有一个人机交互式GUI界面，界面友好。是个不错的bishe选题。 二、算法流程 结合火焰的面积增长率，角点和圆形度三个维度综合判断。并且得出每帧图像火焰部分的该三个参数，实时显示在GUI上。 三、GUI界面设计(This design is based on MATLAB flame smoke fire detection system. The traditional method of using color has large error recognition and strong limitation. Considering that the flame is real-time and dynamic jumping, the area growth rate, corner and roundness are combined to determine whether there is flame. The test object of the design is video. Through the difference between the next frame and the previous frame, whether there is fire is found and the voice alarm can be sent out. This design has a personal computer interactive GUI interface, the interface is friendly. It's a good choice for BiShe.)

图片浏览源码例程，程序调用API函数实现图片的浏览。包括浏览文件夹对话框的“SHBrowseForFolderA”，以及配合它使用的从列表ID取路径“SHGetPathFromIDListA”(Picture Viewer source code routines , the program calls API functions for image browsing. )

图像的自动拼接和缝补，采用sift算法作为匹配，是学习全景图像拼接的基础，大家可以下载下来看看(Automatic image stitching and sewing, using sift algorithm as a match, is the basis for learning panoramic image mosaic, you can download to see)

polSARpro4.0手册 能够对极化SAR图像进行读取，处理和分类。(General Presentation of PolSARprov4.0 Software)

说明：  增广拉格朗日乘子法ALM算法是机器学习中十分常用且有效的一种优化算法，经常用于低秩和稀疏问题的优化求解中，这个包是增广拉格朗日乘子法的matlab代码(ALM algorithm of augmented Lagrange multiplier method is a very common and effective optimization algorithm in machine learning. It is often used in the optimization of low rank and sparse problems. This package is the matlab code of augmented Lagrange multiplier method)

数字图像处理,离散小波dwt变换域中水印的嵌入(digital image processing, discrete wavelet transform domain dwt watermark embedding)

说明：  利用遗传算法进行的 单阈值的图像分割 程序采用matlab编写(The use of genetic algorithm the single-threshold segmentation procedure prepared using matlab)

说明：  LTP算子提取图像的纹理特征，这种方法对于光照变化十分有效。(LTP operator image texture feature extraction, this method is very effective for the illumination changes.)

用于小波的图像的去噪，对于刚接触图像处理的人来说简单 易懂(For wavelet image denoising, image processing for刚接触people who are easy-to-read)