TotalVariationAlgorithms-master

用MATLAB软件产生一个被高斯噪声污染的lenna图像，使用T3、T5、高斯滤波、中值滤波进行处理；(MATLAB software with a Gaussian noise pollution Lenna image, the use of T3, T5, Gaussian filtering, median filtering for processing )

说明：  当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复，本程序实现了泊松噪声下的图像恢复，泊松噪声为信号依赖噪声，能够更加有效逼近实际成像系统噪声。( This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems", "Tikhonov Regularized Poisson Likelihood Estimation: Theoretical Justification and a Computational Method", "An Efficient Computational Method for Total Variation with Poisson Negative-Log Likelihood", "An Analysis of Regularization by Diffusion for Ill-Posed Poisson Likelihood Estimation," "An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is Poisson", and finally, "Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation". See my publications page for more details. The main algorithm is for nonnegatively constrained, regularized Poisson likelihood estimation. At this point you can choose Tikhonov, total variation regularization, and diffusion regularization. A number of other methods are also implemented. Regularizatio)

用广义高斯模型（GGM）拟合分布代码，包括生成直方图，参数估计等(for GGM simulation)

说明：  在用Mean-shift进行跟踪中，采用颜色与纹理相结合的特征空间(Mean-Shift using features of color combined with texture.)

对图像进行灰度处理，乘除处理法处理，加法处理，减法处理(Gray scale, multiplication and division of image)

主要介绍关于图像匹配的相应matlab程序设计(Focuses on the appropriate image matching matlab program )

能实现VFW编程，调用本地视频设备，实现视频捕捉和RGB-YUV颜色空间转换。 (To achieve VFW programming, call the local video equipment, the implementation of video capture and RGB-YUV color space conversion.)

说明：  图像多尺度几何分析 contourlet 变换的matlab工具箱(Multiscale geometric analysis contourlet transform matlab toolbox)

感兴趣区域提取，能用于车牌号及台风等图像，效果不错(Extract the interesting area, it can be used in license plate number and typhoons images and so on, has good results )

document about computer vision - image processing