pingjiehefengbu

基于EM-马尔科夫随机场-ICM的图像分割程序，很好的学习代码(EM-based Markov random-ICM image segmentation procedures, good learning code)

curvelet图像融合，一个很好的程序，对大家应该有帮助(curvelet fusion)

Itti模型的显著图提取，使用matlab编写，很好的代码，可供参考学习(Itti model saliency map extraction, the use of matlab prepared very well the code)

基于马尔可夫随机场的图像恢复，给出产生MRF的程序并应用于图像去噪(GMRF based on the image restoration, MRF is generated and applied to the procedures Image Denoising)

说明：  实现了离散小波变换和连续小波变换，用于小波分析。(Discrete wavelet transform and continuous wavelet transform are implemented for wavelet analysis.)

说明：  在一幅图像中对单人脸进行定位,原理是基于多模板匹配(locate face in one picture in which there is a single face，its theory base on many templates matching)

Jianchao Yang 的基于稀疏表示的单幅图像重建的原始代码，先将高低训练图像分块，再将块训练成高低字典，将测试图像映射到低字典上，得到系数，再乘以高子典就得到最后的图像。对学习超分辨率同学的参考作用很大。(This is the original matlab code for super resolution by Jianchao Yang 。The method is sparse represent based on the overcomplete dictionary。)

说明：  基于matlab的简易小波阈值去噪，小波变换基础上变换阈值实现对图像的去噪(Matlab based on the simple wavelet transform, simple image denoising)

模式识别应用范围广泛，在机器学习，图像处理，运动目标检测与跟踪方面具有较大的应用价值。是本好书，值得推荐。(pattern recognition applied extensively in machine learning, image processing, moving target detection and tracking with greater value. Is a book worth recommending.)

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.)