motionEstES

DCT水印，简单实用，基于8*8分块的DCT域水印嵌入算法水印图像为64*64(DCT watermark, simple and practical, based on the 8* 8 sub-block DCT domain watermark image watermark embedding algorithm is 64* 64)

说明：  光流计算得到运动场。使用算法为Lucas Kanade算法。(optical flow calculated Sports Ground. Lucas uses algorithms to Kanade algorithm.)

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.)

Image Fusion With Guided Filtering基于向导滤波的图像融合。将图像分解成基础层和细节层，用一种新型的滤波融合图像，使融合效果更显著更高效。(The image is decomposed into a base layer and layer of detail, the fused image with a new filter, the fusion effect is more pronounced and more efficient.)

一个光流算法的matlab源程序，在图像处理、前景检测与跟踪等方面有很多应用，推荐(An optical flow algorithm matlab source code in image processing, the prospects for detection and tracking, etc. There are many applications, the recommendation)

基于格子玻尔兹曼方法模拟泊肃叶流，边界条件用非平衡格式(Poiseuille flow based on the lattice Boltzmann method to simulate the boundary conditions with unbalanced format )

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)

一个老外用matlab 编写的5点法图像相对定向程序，是目前最新的算法实现。(5 point to prepare for a foreigner relative orientation program)

C# 水平交错效果显示图像 实例

本人在写论文时自己编写的虹膜瞳孔的分割，采用二值化方法，并附有图片。希望有人和我一起研究。(I am writing papers prepared by his pupil iris division of the value of using two methods, accompanied by a caption. And I want people to see.)