Spectral Residual Model for Rural Residential Region Extraction from GF-1 Satellite Images

Abstract

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.