期刊名称: |
Remote Sensing Letters |
全部作者: |
Zhenfeng Shao, Yingjie Tian, Xiaole Shen* |
出版年份: |
2014 |
卷 号: |
5 |
期 号: |
4 |
页 码: |
305-314 |
查看全本: |
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A built-up areas saliency index (BASI) to extract built-up areas is proposed in this article. The proposed method is designed to be especially effective for dealing with high-resolution remote sensing images and complex scenes. Due to the complexity of built-up areas in high-resolution images, visual attention model based on textural feature is applied for the calculation of BASI. To highlight built-up areas in complex scenes, we present an improved signal processing method to describe the textural feature of built-up areas, which is used as the low-layer feature of the visual attention model. Comparison studies and experimental results demonstrate the accuracy and robustness of BASI for discrimination between built-up and non-built-up areas from satellite and aerial high-resolution remote sensing data.