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Earth Science Informatics

Erschienen in:

08.07.2018 | Research Article

Building area extraction from the high spatial resolution remote sensing imagery

verfasst von: Wenzao Shi, Zhengyuan Mao, Jinqing Liu

Erschienen in: Earth Science Informatics | Ausgabe 1/2019

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Abstract

An approach to building area extraction from high-resolution remote sensing imagery is proposed based on the local gradient orientation density function (LGODF) and the bimodal density function (BDF). Firstly, the LGODF is calculated by moving the window of 35 × 35 based on the gradient magnitude and the gradient direction of each pixel in the image. Then, the BDF is obtained by multiplying the movable bimodal Gaussian mixture function and LGODF in each window. Finally, peaks with difference of 90° are searched for in the BDF, and the central point of the corresponding windows are determined as building pixels. For the validity of the proposed method, seven representative sub-images from PLEIADES images covering Shenzhen China are selected. Experimental results reveal that the precision achieve 94.08% and the recall up to 96.70%.

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Titel: Building area extraction from the high spatial resolution remote sensing imagery
verfasst von: Wenzao Shi
Zhengyuan Mao
Jinqing Liu
Publikationsdatum: 08.07.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Earth Science Informatics / Ausgabe 1/2019
Print ISSN: 1865-0473
Elektronische ISSN: 1865-0481
DOI: https://doi.org/10.1007/s12145-018-0355-5

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