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Multi-Scale Blobs for Saliency Detection in Satellite Images

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Abstract

Saliency can be modeled as spatially localized and contrasted structures with higher blob density and higher blob evenness across scales in images. And it is likely to contain regions and objects of interest. So saliency detection is desired before further image processing and analysis. This paper presented an automatic and effective method for saliency detection in satellite images, based on multi-scale blob information. Firstly, multi-scale blob information were extracted from input images, to produce a blob map. Then, in the blob map, multi-level distance transform spread the blob information to the entire image, to generate a saliency map. Finally the saliency map was segmented to detect salient regions and to locate object centers. The experimental results illustrated its accuracy and stability for detecting salient regions (such as residential areas, parking lots and airplane docks) and for locating object centers in various satellite images.

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Acknowledgments

This work was supported in part by China Postdoctoral Science Foundation under Grant 2015M570138, in part by the National Natural Science Foundation of China under Grant 41301488 and 41301438, in part by the National High Technology Research and Development Program of China (863 Program) under Grant 2013AA12A401-2, in part by the National Major Program on High Resolution Earth Observation System under Grant 03-Y30B06-9001-13/15-01.

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The authors report no conflict of interest. The authors are responsible for the content and writing of the paper.

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Correspondence to Yanan Zhou.

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Zhou, Y., Luo, J., Hu, X. et al. Multi-Scale Blobs for Saliency Detection in Satellite Images. J Indian Soc Remote Sens 44, 159–166 (2016). https://doi.org/10.1007/s12524-015-0469-x

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  • DOI: https://doi.org/10.1007/s12524-015-0469-x

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