Open AccessHierarchical detection method of specific artificial region using local structural constraint in remote sensing images
Author(s) -
Bi Fukun,
Lei Mingyang,
Qin Yanyan,
Hou Jinyuan,
Yang Zhihua,
Zhang Jie
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0711
Subject(s) - computer science , artificial intelligence , pattern recognition (psychology) , constraint (computer aided design) , similarity (geometry) , matching (statistics) , process (computing) , feature (linguistics) , image (mathematics) , remote sensing , computer vision , mathematics , geography , linguistics , statistics , philosophy , geometry , operating system
Automatic detection of specific artificial region is one of the research hotspots in remote sensing image. In this study, a hierarchical detection method of specific artificial region using local structure constraint in remote sensing images is proposed. The process can be divided into two main stages: screening of keypoints based on the description of structural pattern, and specific artificial regions detection based on the local structural similarity. This method can greatly reduce the calculation of feature description in the redundant non‐specific regions, and effectively reduce the error matching points to achieve the rapid and reliable detection of the specific artificial region. The authors test the proposed method on the artificial region sets with different types and time phase. The experimental results show that the method has high computational efficiency and detection accuracy.