geom2d-2015.05.13

说明：  用matlab编写界面，并实现图像的方向滤波和同态滤波，实用方便，效果较好(Matlab prepared to use interface, and the realization of the direction of image filtering and homomorphic filtering, practical convenience, better)

GM(1,1)的程序,要用就下啥,可以预测的,里面有详细的说明,很容易看懂的！,(GM (1, 1) program, want to use is what, predictable, there are detailed instructions, it is easy to understand!)

读取RAW格式文件，将其转换为BMP格式文件并存储，主要实现灰度图像的转换(Read the RAW format, convert it to BMP format file and stored, mainly to achieve the conversion of grayscale images)

图像纹理特征提取在图像处理中有着非常重要的作用，这个是提取图像纹理特征的程序！(Image texture feature extraction in image processing has a very important role, this is the image texture feature extraction procedure!)

晨宇思远博客的代码------文件中代码实现小波图像融合，对低频和高频系数采用不同准则，有详细说明文件中代码实现小波图像融合，对低频和高频系数采用不同准则，有详细说明( morning yu siyuan blog code----------- file code implements wavelet image fusion, the low frequency and high frequency coefficient using different criteria, there are detailed description file code implements wavelet image fusion, the low frequency and high frequency coefficient using different criteria, there are elaborate)

火焰识别系统，支持图片、视频、摄像头实时监测

基于T熵的多阈值分割,实现了灰度图像的自动转换,以及对灰度图像的二阈值和三阈值的分割算法(T entropy-based multi-threshold segmentation grayscale image automatically converted, and the threshold grayscale images and three threshold segmentation algorithm)

说明：  按照最邻近原则把待分类样本点分到各个簇。然后按平均法重新计算各个簇的质心，从而确定新的簇心。一直迭代，直到簇心的移动距离小于某个给定的值。(According to the nearest neighbor principle, the sample points to be classified are divided into clusters. Then the centroid of each cluster is recalculated according to the average method to determine the new cluster center. Iterate until the moving distance of the cluster center is less than a given value)

说明：  基于Online Learning for Matrix Factorization and Sparse Coding的在线字典学习算法，本压缩包为作者的源代码(The online dictionary learning based on the paper "Online Learning for Matrix Factorization and Sparse Coding". This compression package is the author's source code.)

基于直方图的多阈值分割可以求出三个阈值，适合CT图像分割(Histogram-based multi-threshold segmentation can be obtained three threshold for CT image segmentation)