图像纹理基元分类的马尔柯夫随机场方法  

A Method of Image Texture Texton Classification with Markov Random Field

作　　者：郑肇葆[1] 潘励[1] 郑宏[2] ZHENG Zhaobao PAN Li ZHENG Hong(School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079 School of Electronic Information, Wuhan University, Wuhan 430079, China)

机构地区：[1]武汉大学遥感信息工程学院,湖北武汉430079 [2]武汉大学电子信息学院,湖北武汉430079

出　　处：《武汉大学学报（信息科学版）》2017年第4期463-467,共5页Geomatics and Information Science of Wuhan University

基　　金：国家973计划(2012CB719905)~~

摘　　要：提出基于马尔柯夫随机场(MRF)的图像纹理基元分类新方法。利用MRF里中心像元特征值与邻近像元特征值之间的约束关系,反映图像纹理基元的特征以及不同的MRF参数。根据由同一类别的图像求得的MRF参数计算出的标准差最小这一性质来进行图像纹理的分类。通过不同实验方案的对比,以及与不同分类方法的比较,证实提出的图像纹理基元分类方法具有一定的优势。In this article a new method based on MRF to classify image texture texton has been put forward.The constraint relationship between the center pixel feature value and the neighbor pixels feature value in MRF can reflect the features of image texture texton as well as different MRF parameters.Standard deviation based on the MRF parameter of the same category is the smallest.So we can use this property to classify image texture.By comparing the different experimental scheme and different classification method,we can come to the conclusion that the method of image texture element classification proposed in this paper has certain advantages,and it is a good methold of image classification.

关 键 词：图像纹理基元 马尔柯夫随机场 图像纹理分类 

分 类 号：P231[天文地球—摄影测量与遥感]