基于空间语义模型的高分辨率遥感图像目标检测方法  

Spatial Semantic Model Based Geo-objects Detection Method for High Resolution Remote Sensing Images

作　　者：冯卫东[1,2] 孙显[1] 王宏琦[1] 

机构地区：[1]中国科学院电子学研究所,北京100190 [2]中国科学院大学,北京100049

出　　处：《电子与信息学报》2013年第10期2518-2523,共6页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(41001285)资助课题

摘　　要：该文提出一种基于空间语义模型的方法,用于高分辨率遥感图像复杂场景中典型地物目标的自动检测。该方法通过分割获取图像对象,引入主题模型统计对象的多维特征,提高了对象特性描述的精度。在此基础上,对图像中有意义的地物目标及它们之间的空间关系建模表达和定量计算,通过获取场景的语义解析树,辅助实现对复杂地物目标的准确提取和定位。在测试数据集上的实验结果表明,该文方法具有较高的智能化程度和较强的稳定性。A spatial semantic model based method is proposed to solve the issue of automatically detecting geo-objects in high resolution remote sensing images. This method obtains firstly image segments through over-segmentation algorithm, and calculates the multiple features by using topic models, in order to improve the description accuracy of segments attribution. Then, this method investigates and models the spatial relationship between geo-objects in whole images, and a semantic parsing tree of the scene category is extracted, which could be used to detect and locate the geo-objects. The experimental results on the dataset demonstrate the robustness and accuracy of this method.

关 键 词：目标检测 高分辨率遥感图像 空间语义 

分 类 号：TP753[自动化与计算机技术—检测技术与自动化装置]