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图形图像感兴趣区域提取的方法，个人总结的~可以直接运行！(Graphic method of region of interest extraction, can be directly run personal summary!)

1、去条带噪声（通道均衡）程序 2、去冲击噪声程序 3、KSVD程序 均为matlab源代码(1 to band noise (channel equalization) program 2, to the impact of noise program 3, KSVD program Matlab source code are)

基于MRF模型的变化检测算法仿真 MRF建模用于SAR去噪，再通过EM算法实现变化检测(MRF model-based change detection algorithm simulation)

十分有用的 图像pocs算法，内有图片说明及示例(A very useful POCS algorithm for images, with illustrations and examples)

光学计算中跟衍射相关的很多公式，有详细说明，很好用(err)

层析成像的数学方法与应用-一本关于层析成像的使用方法的详细讲解，对于初学者具有指导性意义。(Mathematical methods and applications of tomography- a detailed on the use of tomography methods to explain, for beginners with a guiding significance.)

维的简单LDA和2维LDA人脸识别的matlab代码，注释详细，可以直接运行，非常好用，还有1维LDA算法讲解，很适合入门的同学！( U7EF4 u7684 u7352 u5355 u548C2 u7A4 u7A1 UFF0C u9H09 u5976 u5E8 u5L0 u5B0 )

改程序就代码可以找出从不同角度或区间的两幅遥感影像的同名点(Change the program code can find it from different angles of the same name point or interval of two remote sensing images)

以多光谱数据为原始数据，通过空间变换、滤波、融合、纹理及图像处理等手段，提取遥感图像多维、多尺度特征，最终建立面向目标检测、识别和分析的特征空间，并使用NASA的实测数据对方法的性能进行验证和分析。(Multi-spectral data to the original data, through space conversion, filtering tools, integration, texture and image processing, remote sensing images to extract multi-dimensional, multi-scale features, for the eventual establishment of target detection, identification and analysis of the characteristics of the space, and measured using NASA performance of the method for data verification and analysis.)

说明：  该课题为基于MATLAB的汽车出入库识别系统，带有丰富的人机交互GUI界面。目前毕业设计选题中，传统的中规中矩的车牌识别不易得到高分，必须要在此基础上有所创新方得可以避开其他雷同课题，不会轻易被导师被否决而导致毕设不过。因此建议在车牌识别基础上加入多种方法的对比，看看哪种方法的精度高。虽然目前有很多方法的车牌识别，但是都是在各自的测试库里面测试的，比如测试的车牌图像不同，字符库不同，导致无法做对比。整个设计在一个GUI界面上完成。(This project is based on MATLAB vehicle in and out of the warehouse identification system, with rich human-computer interaction GUI interface. At present, in the topic selection of graduation project, the traditional regular license plate recognition is not easy to get high scores, so it is necessary to innovate on this basis to avoid other similar topics, and it will not be rejected easily by the tutor, leading to the failure of graduation project. Therefore, it is suggested to add a variety of methods on the basis of license plate recognition to see which method has high accuracy. Although there are many methods of license plate recognition, they are tested in their own test library, for example, the test license plate image is different, the character library is different, so it can not be compared. The whole design is completed on a GUI interface.)