iris_image_segmentation

KSVD图像去噪,组稀疏编码，新的去噪思路(KSVD image denoise，group spare coding)

摄影测量后方交会matlab源代码,用于解算外方位元素,课堂编程作业(Photogrammetry Resection matlab source code for solving the exterior orientation elements, classroom programming assignments)

本算法在Matlab2008b 环境下实现。包括main,san 和ssd 三个函数。 这次实现的算法并不是比较两个已经知道的点是否匹配，而是已知一个图形中的特征点，在另外一个图像中找到与其最匹配的点，匹配度用SAD 或者SSD 来度量。 main.m 是程序的入口，包括生成和读入实验数据，调用sad 函数和ssd 函数求匹配点，最后绘 制出最后的结果。sad.m 是用sad 度量方法在另一图中求解匹配点的函数实现，有3 个参数 y=sad(x,image1,image2)。其中x 是代匹配的数据，image1 是图像1 数据，image2 是图像2 数据。 从理论上分析，ssd 比sad 算法要复杂一点，经过测试，在一幅640*480 的图像中寻找10 个匹配点数据SAD 用时25.062519 秒，SSD 用时25.291432 秒。(The algorithm Matlab2008b environment to achieve. Including the main, san, and ssd three functions. The implementation of the algorithm is not the point of comparing two matches already know, but the known feature points in a graphic, an image found in the other match with the most points, matching measured with the SAD or SSD. main.m is the entry, including the generation and reading test data, call the sad ssd function evaluation functions and matching points, and finally draw the final result. sad.m measure is sad figure in another match point in the function implementation to solve, there are three parameters y = sad (x, image1, image2). Where x is the generation of matching data, image1 is the data image 1, image2 is the image 2 data. From the theoretical analysis, ssd little more complicated than the sad algorithm, tested in a 640* 480 images of 10 match points in the search for data using time 25.062519 seconds SAD, SSD with time 25.291432 seconds. )

Object Recognition with Hierarchical Kernel Descriptors,In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2011.(Hierarchical Kernel Descriptors.)

利用Hough变换，可以检测图像中的多条线段，效果很好(using hough transform for line detection)

这个代码是基于论文“Saliency Detection via Graph-Based Manifold Ranking”下的程序源码，作者是Chuan Yang, Lihe Zhang, Huchuan Lu, Ming-Hsuan Yang, and Xiang Ruan 功能1：使用canny算子计算图像的二值边缘图 (The code is for paper "Saliency Detection via Graph-Based Manifold Ranking" by Chuan Yang, Lihe Zhang, Huchuan Lu, Ming-Hsuan Yang, and Xiang Ruan Procedures: 1. compute a binary edge map of the image using the canny method. )

使用大津法选定二值化阈值，并对彩色图像做二值化处理(Otsu binarization threshold is selected, and the color images do binarization processing)

C# 动态绘制曲线

本代码主要给出了激光粒度仪颗粒散射光强分布以及4种粒度反演算法，以及4种算法之间的比较。四种反演算法为：TSVD、Chaine、Tikhonov和l1正则化。(The code gives the Zetasizer particle scattering intensity distribution, and four kinds of particle inversion algorithm, as well as a comparison between the four algorithms. Four kinds of inversion algorithm is: TSVD, Chaine, Tikhonov and l1 regularization.)

用于读取SAR数据处理中的干涉图和SAR强度图的函数，可以制定具体大小进行读取。(The functions used to read the interferograms and SAR intensity diagrams in SAR data processing can be read by specific sizes.)