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Building Extraction from High-Resolution Remote Sensing Images Based on GrabCut with Automatic Selection of Foreground and Background Samples

Lookup NU author(s): Dr Wen Xiao

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Abstract

This article proposes a new building extraction method from high-resolution remote sensing images, based on GrabCut, which can automatically select foreground and background samples under the constraints of building elevation contour lines. First the image is rotated according to the direction of pixel displacement calculated by the rational function Model. Second, the Canny operator, combined with morphology and the Hough transform, is used to extract the building's elevation contour lines. Third, seed points and interesting points of the building are selected under the constraint of the contour line and the geodesic distance. Then foreground and background samples are obtained according to these points. Fourth, GrabCut and geometric features are used to carry out image segmentation and extract buildings. Finally, WorldView satellite images are used to verify the proposed method. Experimental results show that the average accuracy can reach 86.34%, which is 15.12% higher than other building extraction methods.


Publication metadata

Author(s): Zhang K, Chen H, Xiao W, Sheng Y, Su D, Wang P

Publication type: Article

Publication status: Published

Journal: Photogrammetric Engineering and Remote Sensing

Year: 2020

Volume: 86

Issue: 4

Pages: 235–245

Print publication date: 01/04/2020

Acceptance date: 01/01/2020

ISSN (print): 0099-1112

Publisher: American Society for Photogrammetry and Remote Sensing

URL: https://doi.org/10.14358/PERS.86.4.235

DOI: 10.14358/PERS.86.4.235


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