CAJ | 학술논문

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。
해문제출일충기우공간어의모형적방법，용우고분변솔요감도상복잡장경중전형지물목표적자동검측。해방법통과분할획취도상대상，인입주제모형통계대상적다유특정，제고료대상특성묘술적정도。재차기출상，대도상중유의의적지물목표급타문지간적공간관계건모표체화정량계산，통과획취장경적어의해석수，보조실현대복잡지물목표적준학제취화정위。재측시수거집상적실험결과표명，해문방법구유교고적지능화정도화교강적은정성。
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.