lfceratfre

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.)

使用小波框架来实现图像融合算法。文件中有测试图片。(Framework to achieve the use of wavelet image fusion algorithm. Document the test picture.)

鸟瞰图校正，基于OPENCV的应用，可以把鸟瞰图校正为平面图。(Aerial view of the correction, based on the application of OPENCV, bird' s eye view can be corrected for the plan.)

将matlab处理得到的三维矩阵转化为envi软件可读取的数据格式raw(change the 3-D data from matlab to the raw form ENVI can read)

用于植物叶片分类的图形界面,是Matlab源码，用BP神经网络实现(For plant leaf classification graphical interface, the Matlab source code, using BP neural network)

The focus of this project is to experiment with intensity transformations to enhance an image.

基于mfc对话框开发的图片位深度转换器，源码部分截图如下。 CImage img;    img.Load("D:\qrcode.png");    img.Save("D:\qrcode.bmp");    CxImage ximage;    ximage.Load("D:\qrcode.bmp", CXIMAGE_FORMAT_BMP);    ximage.AlphaStrip();    ximage.Save("D:\11.bmp", CXIMAGE_FORMAT_BMP);

背景音乐只是随便写了写,具体的可以改数组里的数字.有点闪的效果还是不太好看. (Background music just casually write write array of specific numbers can be changed. Bit flash effect is still quite nice.)

说明：  图像处理实验matlab的图像预处理：边缘检测、二值化、形态学滤波、灰度化(Image processing experiment matlab image preprocessing:Edge detection, binarization, morphological filtering)

本代码是用Matlab实现图像的超分辨率重建，方法为凸集投影法，能从多幅低分辨率图像重建一幅高分辨率图像。(We use Matlab to reconstruct image. The method is convex projection on suoer-resolution(POCS).)