Share Email Print
cover

Proceedings Paper

Automatic road extraction from high resolution remote sensing image by means of topological derivative and mathematical morphology
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Automatic road extraction from High Resolution Remote Sensing Image is a challenging problem. In this paper we present a new approach for road automatically extraction which is based on topological derivative and mathematical morphology. This approach for road extraction can be divided into three main steps: using topological derivative for image segmentation, using mathematical morphology for road network identification and filtering. The experimental results show that this approach can effectively extract roads from high-resolution remote sensing image.

Paper Details

Date Published: 8 March 2018
PDF: 7 pages
Proc. SPIE 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 1061104 (8 March 2018); doi: 10.1117/12.2282998
Show Author Affiliations
Hongyu Zhou, Anyang Normal Univ. (China)
Xu Song, Anyang Normal Univ. (China)
Guoying Liu, Anyang Normal Univ. (China)


Published in SPIE Proceedings Vol. 10611:
MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Nong Sang; Jie Ma; Zhong Chen, Editor(s)

© SPIE. Terms of Use
Back to Top