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

Civil Engineering

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