matlab

基于条件迭代法与马尔可夫随机场的遥感图像分割的matlab代码(the image segmentation based on the ICM and Markov random field)

Graph Cutshi是最近在计算机视觉中研究和应用比较多的优化算法，典型的用于stereo matching, image restortion, texture synthesis等应用，以上代码给出了graph cut，mean shift, 以及相关的ppm/pgm图像借口，本来是用于stereo matching的，已经把相关的matching的实现代码给去掉了。大家可以以此为平台做一些相关的研究和应用。 (Graph Cutshi recently in computer vision research and application of a relatively large number of optimization algorithms, typical for the stereo matching, image restortion, texture synthesis applications, the above code gives the graph cut, mean shift, and the associated ppm/pgm images an excuse, it is used for stereo matching, and has been related to matching the code to realize removed. U.S. can also be used as a platform to do some related research and applications.)

用SLM法降低PAPR的CCDF,调用SLM函数来实现，毕业设计很有用的源代码(SLM method used to reduce PAPR of the CCDF, call the SLM function to achieve graduation design of the source code is useful)

说明：  sprites communication to windows in unix sys

Matlab程序，利用curvelet变换和高斯逆滤波进行图像去雾，含效果图(Matlab program, using curvelet transform and inverse Gaussian image filtering to fog, with the effect of map)

对多目标航迹跟踪进行关联和融合,采用JPDA（联合概率数据关联算法）对目标跟踪(And the multi-target track tracking is combined and merged)

2维的基于互信息的图像配准算法，使用powell法作为优化算法(2-dimensional mutual information based image registration algorithms, the use of law as the optimization algorithm powell)

转：https://blog.csdn.net/jinshengtao/article/details/26278725 混合高斯背景建模是基于像素样本统计信息的背景表示方法，利用像素在较长时间内大量样本值的概率密度等统计信息(如模式数量、每个模式的均值和标准差)表示背景，然后使用统计差分(如3σ原则)进行目标像素判断，可以对复杂动态背景进行建模，计算量较大。 在混合高斯背景模型中，认为像素之间的颜色信息互不相关，对各像素点的处理都是相互独立的。对于视频图像中的每一个像素点，其值在序列图像中的变化可看作是不断产生像素值的随机过程，即用高斯分布来描述每个像素点的颜色呈现规律单模态(单峰)，多模态(多峰)(Gaussian mixture background modeling is a background representation method based on the statistical information of pixel samples. Statistical information such as the number of patterns, the mean and standard deviation of each pattern are used to represent the background. Statistical difference (such as 3_principle) is used to judge the target pixel. Complex dynamic background modeling has a large amount of computation. In the Gaussian mixture background model, it is considered that the color information between pixels is uncorrelated and the processing of each pixel is independent of each other. For each pixel in a video image, the change of its value in a sequential image can be seen as a random process that produces pixel values continuously, i.e. Gaussian distribution is used to describe the regularity of color rendering of each pixel in single mode (single peak) and multi-mode (multi-peak).)

讨论了OpenCV(Open Source Computer Vision Library)相对于现有的计算机视觉软件包所具有的优势，描述了OpenCV的 环境配置、数据定义、图像元素访问方式。OpenCV成为一种源码开放、包含丰富的高级数学计算函数、图像处理函数和计算机视觉 函数、不断更新和平台无关性的计算机视觉软件包。(Discussed the OpenCV (Open Source Computer Vision Library) relative to the existing computer vision, the advantages of packages, description of OpenCV environment configuration, data definition, the image element access mode. OpenCV become an open-source, contains a wealth of advanced mathematical calculations, functions, image processing functions, and computer vision functions, continuously updated, and platform-independent package of computer vision.)

IDL关于图像感兴趣图像区域进行编辑并将结果输出，多ROI区域DN值信息比较(IDL about the region of the image interested in editing and exporting the results, and comparing the DN value information of the multiple ROI regions)