MRF_SEGMENT

本代码实现了对高光谱遥感图像进行混沌序列置乱加密，其中包括读取三维立体遥感图像、混沌加密以及灰度直方图绘制(This code implements the hyperspectral remote sensing images chaotic sequence of scrambling encryption, including reading the three-dimensional sensing image, and histogram drawing Chaotic Encryption)

基于统计算法的红外图像非均匀性矫正算法，场景类算法，实现实时校正(IRFPA NUC)

自己编的nsct和pcnn结合的融合程序,简单易懂，pcnn采用的不是改进型的，传上来供大家参考，运算复杂，出结果很慢。(A fusion algorithm based on NSCT-PCNN.It is easy to understand,but the quantity of arithmetic is large, and it costs a long time.)

亮度代表了图像的明暗程度，颜色代表了图像的色度，它包含了色调和饱和度。这个代码可以自动对这三个参数进行调整。(Brightness represents the degree of image brightness, color represents the color image, which includes hue and saturation. This code can be automatically adjusted to the three parameters.)

针对镜头畸变失真模型，进行镜头畸变失真校正的小程序(Distortion model for lens distortion, lens distortion distortion correction for a small program)

连续投影算法选出最优波段，一般是选出光谱图形的最优波段(Successive projection algorithm chooses the optimal band, typically selected spectral graph of the optimal band)

图像二值化，采用Niblack算法，采用Matlab编写，可以做个参考。(It accomplishes the binary work to an imge, using Niblack algorithm.)

可评价影像融合质量，信息熵、标准差、相关系数等(Evaluable image fusion quality, information entropy, etc.)

非常全面介绍了阴影检测算法以及如何去除阴影的算法，基本涵盖了该领域的所有知识点。(Is a comprehensive introduction to the shadow detection algorithm and how to remove the shadow of the algorithm, covering all the knowledge in the field point.)

程序将界面与数据处理分开，界面采用MFC的对话框模板，对注册、训练、识别和主界面分别建立一个类，通过消息处理函数与用户进行交互，利用多线程来实时显示图像。 数据处理又分为了CFaceAlign（人脸检测+几何归一化）、CLightPrep（光照归一化）、CFaceFeature（Gabor特征提取）、CSubspace（计算Fisherface子空间）四个类，还有一个类 CFaceMngr 负责管理界面与数据之间的交流。这样的程序结构使对界面和算法彼此独立，互不影响。 每个类的具体方法请见相应头文件中的注释。(The program will interface with the data processing separate interface using MFC dialog template, registration, training, recognition and the main interface, respectively, to create a class that interacts with the user through a message handler, using multiple threads to display images in real time.   Data processing is divided into a CFaceAlign (Face Detection+ geometric normalization), CLightPrep (illumination normalization), CFaceFeature (Gabor feature extraction), CSubspace (computing Fisherface subspace) four categories, as well as a class is responsible for managing CFaceMngr interface and data exchange between. Such a program structure allows for interfaces and algorithms are independent of each other. Specific methods of each class, see the comments in the appropriate header files.)