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Visual attention model based mining area recognition on massive high-resolution remote sensing images

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Abstract

With the development of remote sensing technology, satellite images with the characteristics of multi-scale, multi-band, and multi-date make it tend to be big data. So how to raise the extraction speed, precision and automatic degree of salient objects from high-resolution remote sensing images become urgent problems. Based on the analysis using an Itti visual attention model for natural image processing, we achieved improvements in two aspects: (1) the selection of salient regions based on elevation data, and (2) the segmentation of salient regions using the Snake model for precise object contour extraction. Tests on the extraction of 2.5 m high-resolution remote sensing image data in the rare earth mining area in Dingnan County, Jiangxi Province showed a false alarm rate of 14.8 % and a missing alarm rate of 8.4 % in the extraction of mine quantity data. The proposed method could be useful for improving the speed, precision and automatic extraction of salient objects from high-resolution remote sensing images as well as the boundary information of salient objects that are based on a visual attention model.

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Acknowledgments

This work was supported by the grant from the National Natural Science Foundation of China (60972142), the ten-year investigation special ecological environment (STSN-10-03), the National High Technology Research and Development Program of China (2012BAH27B05), 135 Strategy Planning of Institute of Remote Sensing and Digital Earth, CAS.

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Authors and Affiliations

  1. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100094, China

    Xiaolu Song, Guojin He, Zhaoming Zhang, Tengfei Long, Yan Peng & Zhihua Wang

  2. University of Chinese Academy of Sciences, Beijing, 100039, China

    Xiaolu Song

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  1. Xiaolu Song
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  2. Guojin He
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  3. Zhaoming Zhang
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  4. Tengfei Long
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  5. Yan Peng
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  6. Zhihua Wang
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Correspondence to Guojin He.

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Song, X., He, G., Zhang, Z. et al. Visual attention model based mining area recognition on massive high-resolution remote sensing images. Cluster Comput 18, 541–548 (2015). https://doi.org/10.1007/s10586-015-0438-8

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