NDLI: Automatic road extraction based on local histogram and support vector data description classifier from very high resolution digital aerial

Content Provider	IEEE Xplore Digital Library
Author	Rui Zhang Xiangguo Lin
Copyright Year	2010
Description	Author affiliation: Department of Geography and Geoinformation Science, George Mason University, Fairfax, Virginia 22030, USA (Rui Zhang) \|\| Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing, China (Xiangguo Lin)
Abstract	In this paper, an automatic road extraction algorithm for very high resolution aerial imagery based on the local histogram and the support vector data description (SVDD) classifier is proposed. The road maps are extracted by the classification technique. Compared to most existing approaches, the proposed algorithm does not employ the direct stack of spectral bands to form feature spaces, but take the local histogram vector, which calculated from a moving window or a tile of image, as the predictor instead. To evaluate the effectiveness of the algorithm, we apply our algorithm to very high resolution aerial images acquired by Zeiss Imaging's DMC camera. The experimental results indicate that the proposed algorithm is robust and can extract most road pixels correctly even for very complicated scenes.
Starting Page	441
Ending Page	444
File Size	412491
Page Count	4
File Format	PDF
ISBN	9781424495658
ISSN	21537003
e-ISBN	9781424495665
e-ISBN	9781424495641
DOI	10.1109/IGARSS.2010.5654117
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Roads Classification algorithms Histograms Pixel Feature extraction Support vector machine classification very high resolution image Road extraction SVDD histogram
Content Type	Text
Resource Type	Article

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