期刊
REMOTE SENSING
卷 10, 期 8, 页码 -出版社
MDPI
DOI: 10.3390/rs10081287
关键词
building detection; built-up areas extraction; local feature points; saliency index; morphological building index
类别
资金
- Strategic Priority Research Program of the Chinese Academy of Sciences: CAS Earth Big Data Science Project [XDA19030501]
- National Natural Science Foundation of China [91547107, 41271426, 41428103]
- Major Program of High Resolution Earth Observation System [30-Y20A37-9003-15/17]
- Science and Technology Research Project of Xinjiang Military
Automatic detection of buildings from very high resolution (VHR) satellite images is a current research hotspot in remote sensing and computer vision. However, many irrelevant objects with similar spectral characteristics to buildings will cause a large amount of interference to the detection of buildings, thus making the accurate detection of buildings still a challenging task, especially for images captured in complex environments. Therefore, it is crucial to develop a method that can effectively eliminate these interferences and accurately detect buildings from complex image scenes. To this end, a new building detection method based on the morphological building index (MBI) is proposed in this study. First, the local feature points are detected from the VHR remote sensing imagery and they are optimized by the saliency index proposed in this study. Second, a voting matrix is calculated based on these optimized local feature points to extract built-up areas. Finally, buildings are detected from the extracted built-up areas using the MBI algorithm. Experiments confirm that our proposed method can effectively and accurately detect buildings in VHR remote sensing images captured in complex environments.
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