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Mathematical Problems in Engineering
Volume 2017, Article ID 4728425, 8 pages
Research Article

Hierarchical Sea-Land Segmentation for Panchromatic Remote Sensing Imagery

1Beijing Key Laboratory of Embedded Real-Time Information Processing Technology, Beijing Institute of Technology, Beijing 100081, China
2Department of Software Engineering, Mehran University of Engineering and Technology, SZAB Campus, Khairpur 66020, Pakistan
3Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China

Correspondence should be addressed to Liang Chen; nc.ude.tib@lnehc

Received 15 November 2016; Accepted 31 January 2017; Published 12 March 2017

Academic Editor: Ram Avtar

Copyright © 2017 Long Ma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Automatic sea-land segmentation is an essential and challenging field for the practical use of panchromatic satellite imagery. Owing to the temporal variations as well as the complex and inconsistent intensity contrast in both land and sea areas, it is difficult to generate an accurate segmentation result by using the conventional thresholding methods. Additionally, the freely available digital elevation model (DEM) also difficultly meets the requirements of high-resolution data for practical usage, because of the low precision and high memory storage costs for the processing systems. In this case, we proposed a fully automatic sea-land segmentation approach for practical use with a hierarchical coarse-to-fine procedure. We compared our method with other state-of-the-art methods with real images under complex backgrounds and conducted quantitative comparisons. The experimental results show that our method outperforms all other methods and proved being computationally efficient.