The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
An Integrated Method for Urban Main-Road Centerline Extraction From Optical Remotely Sensed Imagery
Abstract
Road information has a fundamental role in modern society. Road extraction from optical satellite images is an economic and efficient way to obtain and update a transportation database. This paper presents an integrated method to extract urban main-road centerlines from satellite optical images. The proposed method has four main steps. First, general adaptive neighborhood is introduced to implement spectral-spatial classification to segment the images into two categories: road and nonroad groups. Second, road groups and homogeneous property, measured by local Geary's C, are fused to improve road-group accuracy. Third, road shape features are used to extract reliable road segments. Finally, local linear kernel smoothing regression is performed to extract smooth road centerlines. Road networks are then generated using tensor voting. The proposed method is tested and subsequently validated using a large set of multispectral high-resolution images. A comparison with several existing methods shows that the proposed method is more suitable for urban main-road centerline extraction.
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Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
A systematic analysis of performance measures for classification tasks
Sokolova, M., & Lapalme, G. (2009) · Information Processing & Management · doi:10.1016/j.ipm.2009.03.002 · Cited by 7,515
Cited by
A review of road extraction from remote sensing images
Wang, W., Yang, N., Zhang, Y., Wang, F., Cao, T., & Eklund, P. (2016) · Journal of Traffic and Transportation Engineering (English Edition) · doi:10.1016/j.jtte.2016.05.005 · Cited by 299
Metadata
- Authors
- Shi, W., Miao, Z., & Debayle, J.
- Venue
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2014-06
- Volume
- 52
- Issue
- 6
- Pages
- 3359-3372
- ISSN
- 0196-2892 (ISSN-L)
- 1558-0644
- OpenAlex
- W2097375363
- Cited by
- 199
- References
- 3
- FWCI
- 25.28
- Type
- journal article
- Language
- en
- Open access
- closed
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- Shi, W., Miao, Z., & Debayle, J. (2014). An Integrated Method for Urban Main-Road Centerline Extraction From Optical Remotely Sensed Imagery. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/tgrs.2013.2272593
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