zhixinsuanfafangan

说明：  模式识别与图像处理，图像的边缘处理，增强(Pattern recognition and image processing, image edge processing, to enhance)

实现基于四叉树分解的局部化互信息。参考文献：Image fusion performance metric based on mutual information and entropy driven quadtree decomposition(Compute the Image fusion performance metric based on mutual information and entropy driven quadtree decomposition.)

基于visual c++平台，相机标定方法中的直接线性变换方法，即DLT方法(Based on visual c++ platform, camera calibration method of direct linear transformation method, namely DLT method)

this codes describe several kind of image filters

自适应的图像增强，使用matlab编的代码，实现一篇核心文献的算法(Adaptive image enhancement using matlab compiled code to achieve a core algorithm literature)

对Vladimir Kolmogorov，Yuri Boykov大牛的算法杰作——Graph Cut进行使用演示，代码力求精简，可供Graph Cut初学者参考学习。已通过VS2005编译。(Of Vladimir Kolmogorov, Yuri Boykov big cow masterpiece algorithm- Graph Cut for the use of demonstration, the code to be simple, for beginners Reference Graph Cut Study. VS2005 compiler has passed.)

彩色图像分割算法，首先基于直方图粗分，而后通过kmeans细分，得到分割结果(Color image segmentation algorithm, first, rough segmentation based on histogram and then broken down by kmeans get segmentation results)

Harris角点检测算法,已经测试通过,程序中有清晰的注解，对于算法的理解有较大的帮助．(Harris corner detection algorithm has been tested, there is a clear process of annotation, the algorithm has a greater understanding help.)

黑塞矩阵（Hessian Matrix），又译作海森矩阵、海瑟矩阵、海塞矩阵等，是一个多元函数的二阶偏导数构成的方阵，描述了函数的局部曲率。黑塞矩阵最早于19世纪由德国数学家Ludwig Otto Hesse提出，并以其名字命名。黑塞矩阵常用于牛顿法解决优化问题，利用黑塞矩阵可判定多元函数的极值问题。在工程实际问题的优化设计中，所列的目标函数往往很复杂，为了使问题简化，常常将目标函数在某点邻域展开成泰勒多项式来逼近原函数，此时函数在某点泰勒展开式的矩阵形式中会涉及到黑塞矩阵。(Hessian Matrix, is a square matrix of the second order partial derivative of the multivariate function, which describes the local curvature of the function. The Hesse matrix was first proposed by the German mathematician Ludwig Otto Hesse in the 19th century and named after it. Hesse matrix is often used in Newton method to solve the optimization problem, using the black plug matrix to determine the extreme function of the extreme value problem.)

采用harris角点特征完成图像拼接，包含特征点的选取以及最终拼接后的结果输出(Harris corner feature complete image stitching, contains the feature points selected and the resulting output after final stitching)