improveeight

包含五个文件夹。 （1）MATLAB程序：其中包含10余个MATLAB程序或（函数）的源代码。程序中所作的注释，与书中关于对应算法的描述是一致的 （2）二值图像：其中的图像可供形态学图像处理实验用，也可通过提取对象的边界，供曲线演化实验使用。 （3）灰度图象和彩色图像：其中的图像，可以作为图像分割，平滑滤波，反差增强，彩色增强以及图像放大等实验的素材。 （4) 视频剪辑：，"two_cells"是采用改进的变分水平集方法，实现GAC模型图像分割的演化过程；"denoissing"是利用P_M方程，对图像平滑去噪的演化过程 "curve_linear_heat_flow"是利用FT实现的闭合曲线的线性热流演化过程。 (These codes are focused on PDE image processing)

摄影测量后方交会matlab源代码,用于解算外方位元素,课堂编程作业(Photogrammetry Resection matlab source code for solving the exterior orientation elements, classroom programming assignments)

harris角点检测，并且实现两幅图像特征点的匹配，最终完成图像的拼接(harris corner detection, and realize two image feature point matching, the final completion of image stitching)

说明：  对加载的图像进行灰度处理，简单处理matlab程序，效果不错，利于后面对图形进一步加工处理(Gray-scale processing of loaded images)

灰度图像到RGB彩色的伪彩色图像的转变程序(Gray-scale image to RGB color of the pseudo-color image change procedures)

说明：  残差灰色模型的改进算法。可以得到高精确度的预测，很实用，并附有测试文件(Improved algorithm for gray model residuals. Can be predicted with high accuracy, very practical, with a test file)

一种基于改进DRLSE的运动目标分割方法,为了得到精准、连续的运动目标轮廓，提出将帧间差分法和改进的距离规则水平集演化(DRLSE)方法结合应用于运动目标分割。(In order to get an accurate and continuous contour of moving target, a novel method to segment moving object by combining the frame difference and an improved distance regularized level set evolution (DRLSE) is proposed. )

一个关于数据降维的工具包，外国牛人编写，囊括了各种降维方法，是一个很好的工具！(A tool for data reduction package, foreign cattle were written, include a variety of dimension reduction method is a good tool!)

图像轮廓提取，Snakes方法来提取CT图像的外轮廓(Snakes method)

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.)