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RobustPCA 是最近提出的一种非常新的图像矩阵分解算法，该算法具有对噪声不敏感、能处理高维图像数据的特点。这是论文作者提供的 MATLAB 实现代码。(Oct 2009 This matlab code implements the augmented Lagrange multiplier method for Robust PCA. )

IDL环境下的EVF矢量数据创建，代码清晰。(IDL environment EVF vector data creation, code clarity.)

本代码的主要功能是实现数据格式之间的转换，实用的是IDL代码，好用实用且清晰。(The main function of the code is to achieve conversion between data formats, practical IDL code, good with practical and clear.)

应用到了操作系统界面功能支持库和图像格式转换支持库，在截取窗口位置时调用了API函数，大家做屏幕截图时可以参考下本例程中的代码。(Applied to the operating system interface features support libraries and image format conversion support library , in the interception of the window position API function calls , you can refer to the code in this routine when we do screenshots .)

利用otsu算法实现图片的自动多阈值分割；用matlab编写的自动多阈值分割程序，分割图像之前采用自动平滑图像(Using otsu algorithm to realize multi- threshold segmentation of pictures)

通过区域迭代合并与定位切图的图像分割算法，非常好的。(Image Segmentation by Iterated Region Merging with Localized Graph Cuts)

本文主要介绍遗传算法的基本理论，叙述遗传算法在图像增强的的主要应用，即将原始图像变得更加清晰，特征变得更加明显。 现今关于图像增强的算法有很多，而这些算法大多是基于退化函数或者点扩展函数的知识进行图像处理的。当图像出现模糊或噪声影响大时，设计出的图像清晰化的效果肯定不够理想，因此有必要对图像进行增强处理。于是，可利用到遗传算法这种成熟稳定的仿生物进化的全局寻优算法，进行图像增强，由于遗传算法控制参数少、自适应度高，将选择该方法对图像退化分别进行不同的清晰化处理. 这样既增强了图像的对比度,又克服了传统直方图均衡化处理所造成的灰度级损失等缺点。 通过实验去表明，遗传算法从全局寻优的角度出发，能够较为精确地估计退化系统函数。和传统的线性增强、直方图均衡进行比较。实验结果表明该方法能改善原图像视觉效果，便于之后的图像分析。 (This paper mainly introduces the basic theory of genetic algorithm, genetic algorithm (ga) in the main application of image enhancement, the original image is more clear, characteristic becomes more obvious. Today about the image enhancement algorithm are many, and most of these algorithms is based on the degradation function or the knowledge of the point spread function of image processing. When the image appears fuzzy or noise influence, designed the image clarity of effect must not ideal, therefore it is necessary to enhance the image. Then, genetic algorithm is available to the mature and stable evolution of the global optimization algorithm, for image enhancement, due to less genetic algorithm control parameters, since the high fitness, will choose the method of image degradation, respectively, to manipulate the different motivation. It can enhance the image contrast, and overcome the traditional histogram equalization processing grayscale loss caused by the faults. Throug)

1.设计一个程序，对一幅灰度图像的实现如下几何变换,1)放大为原图1.5倍 2)绕中心旋转30度(CW) 3)采用偏移量插值实现一个透视变换. 灰度差值用最近邻插值和双线性插值 2. 绘制一幅灰度图像的梯度幅度图像（三点法求梯度），针对梯度幅度图像合理的选择一个阈值（通过试验即可）将其二值化，以获得图像边缘检测图像。 ((1) design a program, a grayscale image as geometric transformation, zoom 1) for 1.5 times the original 2) around the center of rotation of 30 degrees (CW) 3) interpolation of the offset to achieve a perspective transformation.gray level difference between the nearest neighbor interpolation and bilinear interpolation (2) draw a grayscale image of the gradient magnitude image (three-point method seeking gradient), the gradient magnitude image is reasonable to select a threshold value (the test can be) the second value to the image edge detection image.)

本文主要是针对传统混合高斯模型运动目标检测算法的不足做出了一些改进(This article is for the shortcomings of traditional Gaussian mixture model moving object detection algorithm made some improvements)

说明：  可自选输入和参数的中值/均值/拉伸滤波，各项参数说明详见.m文件注释(Median/Average/Linear Stretch Filter)