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Modified Superpixel Segmentation for Digital Surface Model Refinement and Building Extraction from Satellite Stereo Imagery

Gharibbafghi, Zeinab and Tian, Jiaojiao and Reinartz, Peter (2018) Modified Superpixel Segmentation for Digital Surface Model Refinement and Building Extraction from Satellite Stereo Imagery. Remote Sensing, 10 (11), pp. 1-18. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/rs10111824 ISSN 2072-4292

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Official URL: https://www.mdpi.com/2072-4292/10/11/1824

Abstract

Superpixels, as a state-of-the-art segmentation paradigm, have recently been widely used in computer vision and pattern recognition. Despite the effectiveness of these algorithms, there are still many limitations and challenges dealing with Very High-Resolution (VHR) satellite images especially in complex urban scenes. In this paper, we develop a superpixel algorithm as a modified edge-based version of Simple Linear Iterative Clustering (SLIC), which is here called ESLIC, compatible with VHR satellite images. Then, based on the modified properties of generated superpixels, a heuristic multi-scale approach for building extraction is proposed, based on the stereo satellite imagery along with the corresponding Digital Surface Model (DSM). First, to generate the modified superpixels, an edge-preserving term is applied to retain the main building boundaries and edges. The resulting superpixels are then used to initially refine the stereo-extracted DSM. After shadow and vegetation removal, a rough building mask is obtained from the normalized DSM, which highlights the appropriate regions in the image, to be used as the input of a multi-scale superpixel segmentation of the proper areas to determine the superpixels inside the building. Finally, these building superpixels with different scales are integrated and the output is a unified building mask. We have tested our methods on building samples from a WorldView-2 dataset. The results are promising, and the experiments show that superpixels generated with the proposed ESLIC algorithm are more adherent to the building boundaries, and the resulting building mask retains urban object shape better than those generated with the original SLIC algorithm.

Item URL in elib:https://elib.dlr.de/123352/
Document Type:Article
Title:Modified Superpixel Segmentation for Digital Surface Model Refinement and Building Extraction from Satellite Stereo Imagery
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Gharibbafghi, Zeinabzeinab.gharibbafghi (at) dlr.deUNSPECIFIED
Tian, Jiaojiaojiaojiao.tian (at) dlr.deUNSPECIFIED
Reinartz, Peterpeter.reinartz (at) dlr.dehttps://orcid.org/0000-0002-8122-1475
Date:17 November 2018
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:No
Volume:10
DOI :10.3390/rs10111824
Page Range:pp. 1-18
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2072-4292
Status:Published
Keywords:superpixels; building extraction; DSM refinement; stereo satellite imagery; multi-scale segmentation; SLIC; ESLIC
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - Vabene++ (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Zielske, Mandy
Deposited On:22 Nov 2018 17:15
Last Modified:21 Sep 2019 05:06

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