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drfi图像显著性检测算法源码,基本上是目前表现最好的算法，需要m和c混合编程(source code of DRFI model)

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：  polsarpro官方学习教程，系统的说明了polsarpro软件的操作使用，可进行树高反演，地物分类，已经森林模拟数据生成(polsarpro tutorial note)

很好的点云滤波的文章，主要介绍了K-d树的滤波方法(Good point cloud filtering articles, Kd tree filtering method)

vssamp算法，图像变步长自动匹配重构重构算法，基于samp算法，更快速有效的重构复杂图像(vssamp variable step size image reconstruction algorithm automatically matches reconstruction, samp algorithm based on more quickly and efficiently reconstruct complex images)

一个快速而精确的一阶稀疏图像复原算法。主要应用于图像去噪声。(A fast and accurate first-order sparse image restoration algorithm. Is mainly used in the image to the noise.)

为了提高数字图像中椭圆检测的效率和准确性,提出了一个基于最小二乘法的改进的随机椭圆检测算法. 该算法随机选取图像中的3 个边缘点,在以这3 个点为中心的窗口内,从边缘点中拟合出可能椭圆,并通过随机选 取的第4 个边缘点来确认可能椭圆. 利用直接最小二乘法椭圆拟合的特性,引入可能椭圆边缘点收集和椭圆重新 拟合的迭代过程来提取最终的椭圆参数. 通过对含有不同噪声的仿真图片和包括残缺椭圆的实际图片的实验表 明,新算法的改进是有效的. 与原算法相比,新算法降低了对参数的依赖性,提高了检测的速度、稳定性和准确性, 同时保留了原算法的抗噪声能力.(: An imp roved randomized ellip se detection algorit hm based on least square approach was proposed to enhance t he efficiency and accuracy of ellip se detection in digital images. This algorit hm randomly se2 lect s three edge point s in t he image , and t hen uses least square approach to fit all t he edge point s in three windows , which are defined by t he t hree edge point s. The forth edge point is randomly selected to judge whet her a possible ellip se exist s in t he image. Utilizing the characteristic of direct least square fit ting of ellip se , an iteration process of edge point collecting and ellip se refit ting of possible ellip se was int roduced to ext ract t he final ellip se’s parameters. Artificial images wit h different level s of noise and nature images containing incomplete ellip ses were employed to test t his algorithm. Experimental result s show that t he improvement s are notable. Compared with the original algorit hm , t he propo sed algorit hm reduces)

基于区域方差取大的图像融合算法 代码编写经典(Based on the regional variance max of the image fusion algorithm )

说明：  该课题为基于MATLAB平台的PCA的人脸识别图像考勤系统。传统的人脸识别都是直接人头和人头的对比，现实意义不大，这块都做烂了，不易通过毕设答辩，而且论文不好写。该课题识别原理为：从一副生活照中寻找到人脸，并且分割人脸图象，利用PCA算法进行降维，和库里图片进行对比，输出目标人脸以及记录识别的时间，可以统计人脸打卡的当月次数，从而统计出勤率。该课题还可以继续二次开发，做成库内外人脸的识别，如果是库外人脸则实现报警。GUI界面有清除数据功能，统计工资等功能。(This project is based on the MATLAB platform PCA face recognition image attendance system. The traditional face recognition is the comparison of direct head and head, which is of little practical significance. This part is not easy to pass the final defense, and the paper is not easy to write. The recognition principle of this subject is: find the face from a living picture, segment the face image, reduce the dimension by PCA algorithm, compare with the library picture, output the target face and record the recognition time, and then count the number of times in the month when the face is punched, so as to count the attendance rate. The subject can also be further developed to make face recognition inside and outside the database. If it is outside the database, the alarm can be realized. The GUI interface has the functions of data clearing and salary statistics.)

基于SURF算法的图像拼接程序，执行效率高于SIFT算法(Executive efficient than SIFT algorithm based on the the SURF algorithm of image stitching procedure)