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Proceedings Paper

Building extraction from high-resolution remotely sensed imagery based on morphology characteristics
Author(s): Xiuli Xu; Xianfeng Feng; Chuanhai Wang
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Paper Abstract

Information extraction and target recognition are key technologies for high-resolution remote sensing, as well as the foundation of carrying out high resolution remote sensing application. Buildings are the most important ground objects of urban areas. Therefore, the thematic information extraction of buildings from high resolution remote sensing data is of great significance in many fields. The extraction results have been widely used in urban planning, geographical data updates, population and socio-economic census, environmental monitoring and other fields. This paper proposes an algorithm based on morphological characteristics of connected components to segment image and extract buildings from high-resolution image, and successfully extracted the buildings information. First of all, select the 0.6 m pan sharpened band integrated with 3 multispectral bands QUICKBIRD image which imaged in May 2004 as experimental data, and preprocess with geometric correction and integration. Then, process images with closing and opening morphology filter in different scales and build mask to remove the background interference. Finally, use the method of gray-scale threshold, edge detection to segment and select different features to extract buildings respectively. The results proved that the object-oriented building extraction method based on morphology characteristics is superior to the general per-pixel or per-field extraction method. On the one hand, this method improves the extraction accuracy, on the other hand ,improves the contours of buildings.

Paper Details

Date Published: 10 July 2009
PDF: 9 pages
Proc. SPIE 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering, 74890F (10 July 2009); doi: 10.1117/12.836961
Show Author Affiliations
Xiuli Xu, Institute of Geographical Sciences and Natural Resources Research (China)
Hohai Univ. (China)
Xianfeng Feng, Institute of Geographical Sciences and Natural Resources Research (China)
Chuanhai Wang, Hohai Univ. (China)

Published in SPIE Proceedings Vol. 7489:
PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering
Honghua Tan; Qi Luo, Editor(s)

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