snake_examples

利用霍夫变换进行直线检测的算法实现 设置不同的阈值来控制直线的输出(detect lines in image)

马尔可夫（MRF）图像分割MATLAB源码,有30几个函数。Markov随机场的例子程序,对于初学MRF的人很有用,能得到直观的印象(Markov (MRF) image segmentation MATLAB source code, 30 a number of functions. Markov random field example of the procedure, for beginner person MRF useful that they can get a visual impression)

wpf各种统计图展示（直方图，饼图，折线图）

使用Matlab实现LMS自适应滤波，实现的主要功能有：读入原始音频，加入高斯噪声后用LMS自适应滤波滤除，比较原始音频，加入噪声音频和滤波后音频的区别。(Matlab achieved using LMS adaptive filtering to achieve the main features are: read the original audio, adding Gaussian noise is filtered using LMS adaptive filtering, comparing the original audio, add audio and noise filtered audio difference.)

说明：  基于边缘特征的SAR图像与光学图像匹配，测度为Hausdorff距离(SAR images based on edge features and optical image matching, for the Hausdorff distance measure )

极化合成孔径雷达中，常用的精致极化lee滤波器程序，可以较好的表现出图像信息(Polarization synthetic aperture radar (SAR), commonly used delicate polarization lee program, we can better filter show image information )

对两帧图像进行ICM调试.包含内容：1估计姿态和摄像机内参数；2两幅图做四次金字塔；3利用输入特征点采用ransac算法估计姿态R, T。4sift特征匹配；5摄像机标定。(ICM images on two debugging. Contains: 1 Estimated posture and intrinsic parameters 2 two plans to do four pyramids 3 using the input feature points using ransac algorithm estimates gesture R, T. 4sift feature matching 5 camera calibration.)

利用多用方法进行数字图像去模糊实例，便于初学者理解反卷积去模糊、伪逆去模糊等基本算法(Example scripts for image debluring, try to give general introduction of some basic algorithms, such as pseudo inverse debluring.)

斯坦福大学的姚邦鹏开发的一个图像分类算法，使用random forest实现了图像的精细区域描述，赢得了PASCAL VOC2011图像分类竞赛中的winner prize.经测试，程序完全可运行，且提供了MAC和Windows下的两种程序。(Image Classification: An Integration of Randomization and Discrimination in A Dense Feature Representation The goal of our method is to identify the discriminative fine-grained image region that distinguishes different classes. To achieve this goal we sample image regions from dense sampling space and use a random forest algorithm with discriminative classifier. Each node of the tree of random forest is trained and tested with fine-grained image patches combining the information from upstream nodes together. We implemented each node of the tree with a discriminative SVM classifier, which makes the node as a strong classifier. )

VC计算机图形学原理及算法教程 VC计算机图形学入门教程(VC theory and algorithms of computer graphics computer graphics tutorial Tutorial VC)