全连接条件随机场高分辨率遥感影像面状地物交互提取  

Interactive Extraction of High-Resolution Remote Sensing Image Surface Feature Based on Full-Connected Conditional Random Field

作　　者：张春森[1] 胡艳[1] 于振 崔卫红[2] 吴蓉蓉 ZHANG Chunsen;HU Yan;YU Zhen;CUI Weihong;WU Rongrong(College of Geomatics,Xi'an University of Science and Technology,Xi'an 710054,China;School of Remote Sensing and Information Engineering,Wuhan University,Wuhan 430079,China)

机构地区：[1]西安科技大学测绘科学与技术学院,陕西西安710054 [2]武汉大学遥感信息工程学院,湖北武汉430079

出　　处：《武汉大学学报（信息科学版）》2020年第10期1594-1601,共8页Geomatics and Information Science of Wuhan University

基　　金：国家自然科学基金(41601467);陕西省自然科学基金(2018JM5103)。

摘　　要：提出一种基于全连接条件随机场高分辨率遥感影像面状地物交互式提取方法。通过人工交互标记估计前景模型,结合光谱与纹理特征,在利用简单线性迭代聚类算法对输入影像进行过分割的基础上,通过基于区域的最大相似融合对前景区域进行扩充,建立全连接条件随机场描述影像的全局信息。以均值场估计为基础,利用高维高斯滤波方法实现模型推断,进而获取面状地物轮廓。通过对高分遥感影像上水域、林地、梯田等面状地物的实验提取,证明了该方法的有效性。An interactive extraction method of high-resolution remote sensing image surface features based on full-connected conditional random field is presented. Through human interaction tag estimation foreground model, combined with color and texture features, and using the simple linear iterative clustering(SLIC) algorithm to over segment the input image, the maximal similarity based on region merging(MSRM) is used to expand the foreground region and establish the global information of the full-connected conditional random field to describe image. The model inference is realized by the high-dimensional Gauss filtering method which is based on the mean-field estimation. The contours of the area features are obtained.The method is proved to be effective by experimental extraction of surface features such as water, woodland and terraced fields in high-resolution remote sensing images.

关 键 词：高分辨率遥感影像 全连接条件随机场 特征提取 均值估计 高维高斯滤波 

分 类 号：P237[天文地球—摄影测量与遥感]