coif11

说明：  最小噪声分离变换（Minimum Noise Fraction Rotation，MNF Rotation）工具用于判定图像数据内在的维数（即波段数），分离数据中的噪声，减少随后处理中的计算需求量(Minimum Noise Fraction Rotation (MNF Rotation) tool is used to determine the intrinsic dimension (i.e. band number) of image data, separate the noise in data, and reduce the computational requirements in subsequent processing.)

图像直方图统计，并生成灰度图。 matlab程序(Histogram of the image statistics, and generate grayscale. Matlab program)

主要完成图像特征出提取，包括5个特征选择算法：SFS，SBS，SFBS(Description The DEMO includes 5 feature selection algorithms: Sequential Forward Selection (SFS) Sequential Floating Forward Selection (SFFS) Sequential Backward Selection (SBS) Sequential Floating Backward Selection (SFBS) ReliefF)

二维线性判别 功能比较强 二维线性判别 功能比较强(Img = imread( twoObj.bmp ) )

matlab程序，利用主元分析、T2统计图和贡献率图方法对数据进行故障检测和诊断，贡献率图是变量对失控得分进行贡献率计算(matlab program, using principal component analysis, T2 charts and maps of the contribution rate of the data for fault detection and diagnosis, the contribution rate of the variable on the map is out of control scores calculated contribution rate)

混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。通观整个高斯模型，他主要是有方差和均值两个参数决定，,对均值和方差的学习,采取不同的学习机制,将直接影响到模型的稳定性、精确性和收敛性。由于我们是对运动目标的背景提取建模，因此需要对高斯模型中方差和均值两个参数实时更新。为提高模型的学习能力,改进方法对均值和方差的更新采用不同的学习率 为提高在繁忙的场景下,大而慢的运动目标的检测效果,引入权值均值的概念,建立背景图像并实时更新,然后结合权值、权值均值和背景图像对像素点进行前景和背景的分类。(Gaussian mixture model using K (essentially 3-5) Gaussian model to characterize the features of each pixel in the image, in the image of the new frame for updated Gaussian mixture model, with each pixel in the image with a Gaussian mixture current model matching, if successful, determined that the point of the background points, otherwise the former attraction. Throughout the entire Gaussian model, he mainly has two parameters determine the variance and the mean, the mean and variance of the study, to take a different learning mechanism, will directly affect the stability, accuracy and convergence model. Since we are moving object extraction of the background modeling, so the need for the Gaussian model variance and mean two parameters real-time updates. In order to improve the learning ability of the model, an improved method for updating the mean and variance of different learning rates to improve in the busy scene, large and slow moving object detection results, the introduction of)

基于直接最小二乘法的椭圆拟合程序，比较实用，适用于图像处理，椭圆拟合方面研究的初学者(Direct least square method based on ellipse fitting procedure more practical for image processing, aspects of ellipse fitting for beginners)

6Improved discriminate analysis for high dimensional data and its application to face recognition. 2007-Zhuang-Dai.pdf

matlab与C++混编的grabcut分割程序，只需画框即可提取目标(grabcut algorithm)

说明：  图像处理中的变分和偏微分方法图像处理中的变分和偏微分方法图像处理中的变分和偏微分方法图像处理中的变分和偏微分方法(asdf dsfsa fsddf sadf aasdfas sdfdsaf afas sf asdfasf asfdg)