新建文件夹

本程序采用迎风方案实现推广GAC模型的水平集方法，希望大家借鉴。(This procedure uses the wind to promote GAC model programs to achieve the level set, and I hope everybody' s reference.)

介绍matlab下求解偏微分方程的函数和用法(Introduction matlab function for solving partial differential equations and usage)

用matlab开发的计算给定曲面点云的，高斯和平均曲率图(Matlab calculation developed by a given surface point cloud, the Gaussian and mean curvature map)

复杂场景中的红色交通标志牌检测与识别，结合颜色与圆形的标志牌定位，然后提取特征，最后用模板匹配的方法实现识别，内附图片和程序说明，对初学者有帮助(Red detection and recognition of traffic signs in complex scenes, the combination of colors and circular signs positioning, and feature extraction, the last with template matching methods to achieve recognition, included pictures and a description of the procedures for beginners)

SPCA The SPCA algorithm for computing sparse principal components.

基于模型匹配的永磁同步电机混沌化控制例子，是本人一点点做出来的。(this is a example for Chaos Anti-Control of Permanent Magnet Synchronous Motor Based on Asymptotic Model Matching. it was completed by myself.)

标准GS相位恢复算法，利用傅里叶变换与反变换进行逼近，直至收敛，误差下降算法。(Standard GS phase recovery algorithm, using Fourier transform and inverse transform approximation, until convergence, error reduction algorithm.)

cvpr2012_oral On Multiple Foreground Cosegmentation(In this paper, we address a challenging image segmentation problem called multiple foreground cosegmentation (MFC), which concerns a realistic scenario in general Webuser photo sets where a finite number of K foregrounds of interest repeatedly occur over the entire photo set, but only an unknown subset of them is presented in each image. This contrasts the classical cosegmentation problem dealt with by most existing algorithms, which assume a much simpler but less realistic setting where the same set of foregrounds recurs in every image. We propose a novel optimization method for MFC, which makes no assumption on foreground configurations and does not suffer from the aforementioned limitation, while still leverages all the benefits of having co-occurring or (partially) recurring contents across images. Our method builds on an iterative scheme that alternates between a foreground modeling module and a region assignment module, both highly efficient and scalable. In part)

这是基于张亶，陈刚《偏微分方程的图像处理》书的实验及程序(image processing )

说明：  利用fista算法进行图像复原的matlab源码。(The matlab source code of image restoration using the fista algorithm.)