Spectral Residual Model for Rural Residential Region Extraction from GF-1 Satellite Images
Joint Authors
Tang, Hong
Li, Shaodan
Yang, Xin
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-03-17
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Visual attention is an attractive technique to derive important and prominent information from a scene in natural pictures.
As a visual attention approach, spectral residual (SR) model is adapted to extract the residential regions from GF-1 satellite images in this paper.
Specifically, we analyzed the impact of both different combinations of GF-1 satellite image bands and threshold algorithms on rural residential region detection.
In addition, the adapted approach is compared with related visual attention methods in terms of both quantitative and qualitative detection effectiveness.
Experimental results showed that the SR model coupled with red, green, and blue bands in GF-1 images and Otsu threshold algorithm achieved the best results and is suitable to quickly extract rural residential regions from GF-1 images.
American Psychological Association (APA)
Li, Shaodan& Tang, Hong& Yang, Xin. 2016. Spectral Residual Model for Rural Residential Region Extraction from GF-1 Satellite Images. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1112008
Modern Language Association (MLA)
Li, Shaodan…[et al.]. Spectral Residual Model for Rural Residential Region Extraction from GF-1 Satellite Images. Mathematical Problems in Engineering No. 2016 (2016), pp.1-13.
https://search.emarefa.net/detail/BIM-1112008
American Medical Association (AMA)
Li, Shaodan& Tang, Hong& Yang, Xin. Spectral Residual Model for Rural Residential Region Extraction from GF-1 Satellite Images. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1112008
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112008