Building Extraction from High-Resolution Remote Sensing Images by Adaptive Morphological Attribute Profile under Object Boundary Constraint

A novel adaptive morphological attribute profile under object boundary constraint (AMAP-OBC) method is proposed in this study for automatic building extraction from high-resolution remote sensing (HRRS) images. By investigating the associated attributes in morphological attribute profiles (MAPs), th...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2019-08, Vol.19 (17), p.3737
Main Authors: Wang, Chao, Shen, Yi, Liu, Hui, Zhao, Kaiguang, Xing, Hongyan, Qiu, Xing
Format: Article
Language:English
Subjects:
AMAP–OBC
automatic building extraction
Automation
Buildings
Classification
high–resolution
Methods
Morphology
Remote sensing
Semantics
Wavelet transforms
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Summary:A novel adaptive morphological attribute profile under object boundary constraint (AMAP-OBC) method is proposed in this study for automatic building extraction from high-resolution remote sensing (HRRS) images. By investigating the associated attributes in morphological attribute profiles (MAPs), the proposed method establishes corresponding relationships between AMAP-OBC and building characteristics in HRRS images. In the preprocessing step, the candidate object set is extracted by a group of rules for screening of non-building objects. Second, based on the proposed adaptive scale parameter extraction and object boundary constraint strategies, AMAP-OBC is conducted to obtain the initial building set. Finally, a further identification strategy with adaptive threshold combination is proposed to obtain the final building extraction results. Through experiments of multiple groups of HRRS images from different sensors, the proposed method shows outstanding performance in terms of automatic building extraction from diverse geographic objects in urban scenes.
ISSN:1424-8220
1424-8220
DOI:10.3390/s19173737