matlab最小二乘法曲面拟合

matlab源文件，可以实现利用matlab来画各种饼图，显示直观，对做数据分析和论文的同志会有帮助。(matlab source files, can be achieved using matlab to draw a variety of pie, intuitive display, and to do data analysis and papers comrades would help.)

matlab电子稳像块匹配算法程序代码 图片路径请自行更改(Electronic Image Stabilization matlab code image block matching algorithm to change the path at your own)

针对高分辨率遥感图像进行的道路提取，效果还行。(The road extraction for high resolution remote sensing images is good.)

程序是实现交通标志图像的分割GUI界面，采用分割的方法主要有Ostu，阈值迭代选择法及区域生长法。(Program is to achieve a traffic sign image segmentation GUI interface, the mainly segmentation methods are Ostu, iterative threshold selection method and region growing method.)

图像的三种分水岭分割方法，一般分水岭分割，使用梯度的两次分水岭分割及使用梯度加掩模的三次分水岭算法(images of the three watershed segmentation method, the general watershed segmentation, gradient of the two watershed segmentation and the use of the gradient increases mask the three watershed algorithm)

采用相邻一定距离的邻域图像差，提高了抗干扰能力，对亮度变化不敏感(Matching based on neighborhood difference feature)

一个非常简小灵便的DICOM文件阅读器,支持多种格式的文件，支持图片的大多数编辑功能。(A very simple and handy DICOM file reader supports multiple formats of files and most editing functions of pictures.)

摄像标定法求T R矩阵的方法 摄像标定法求T R矩阵的方法 摄像标定法求T R矩阵的方法(how to calculate the matrix R and T using the Camera Calibration method)

图像的特征用到了Dense Sift，通过Bag of Words词袋模型进行描述，当然一般来说是用训练集的来构建词典，因为我们还没有测试集呢。虽然测试集是你拿来测试的，但是实际应用中谁知道测试的图片是啥，所以构建BoW词典我这里也只用训练集。 其实BoW的思想很简单，虽然很多人也问过我，但是只要理解了如何构建词典以及如何将图像映射到词典维上去就行了，面试中也经常问到我这个问题，不知道你们都怎么用生动形象的语言来描述这个问题？ 用BoW描述完图像之后，指的是将训练集以及测试集的图像都用BoW模型描述了，就可以用SVM训练分类模型进行分类了。 在这里除了用SVM的RBF核，还自己定义了一种核： histogram intersection kernel，直方图正交核。因为很多论文说这个核好，并且实验结果很显然。能从理论上证明一下么？通过自定义核也可以了解怎么使用自定义核来用SVM进行分类。(Image features used in a Dense Sift, by the Bag of Words bag model to describe the word, of course, the training set is generally used to build the dictionary, because we do not test set. Although the test set is used as the test you, but who knows the practical application of the test image is valid, so I am here to build BoW dictionary only the training set. In fact, BoW idea is very simple, although many people have asked me, but as long as you understand how to build a dictionary and how to image map to the dictionary D up on the line, and interviews are often asked me this question, do not know you all how to use vivid language to describe this problem? After complete description of the image with BoW, refers to the training set and test set of images are described with the BoW model, the training of SVM classification model can be classified. Apart from having to use the RBF kernel SVM, but also their own definition of a nuclear: histogram intersection kernel, histogram )

matlab编写多种图像边缘检测与分割处理(matlab to prepare a variety of image processing edge detection and segmentation)