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A Bottom-Up Saliency-Based Segmentation for High-Resolution Satellite Images

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Proceedings of 2nd International Conference on Computer Vision & Image Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 704))

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Abstract

High-resolution satellite images, especially of urban areas, are complex in nature. Presence of multiple objects renders analysis of such images challenging. As human mind is best in dealing with complex images and ambiguous problems, such urban area satellite images can be best interpreted by development of such systems that can emulate human mind. Therefore, the presented work separates the high-resolution satellite images into foreground and background on the basis of saliency for simulating human-like segmentation. This work exploits the existing saliency methods available along with segmentation algorithm. Results have been analyzed on the basis of the robustness of ‘shape’ which is a key factor for object recognition. Presented work also propose a measure to assess the goodness of the segmented images which is based on similar segmentation of terrestrial images in a separate work.

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Authors and Affiliations

  1. Civil Engineering Department, Indian Institute of Technology, Roorkee, 247667, India

    Ashu Sharma & Jayanta Kumar Ghosh

Authors
  1. Ashu Sharma
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  2. Jayanta Kumar Ghosh
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Correspondence to Ashu Sharma .

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Editors and Affiliations

  1. Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata, India

    Bidyut B. Chaudhuri

  2. School of Computing, National University of Singapore, Singapore, Singapore

    Mohan S. Kankanhalli

  3. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Balasubramanian Raman

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Sharma, A., Ghosh, J.K. (2018). A Bottom-Up Saliency-Based Segmentation for High-Resolution Satellite Images. In: Chaudhuri, B., Kankanhalli, M., Raman, B. (eds) Proceedings of 2nd International Conference on Computer Vision & Image Processing . Advances in Intelligent Systems and Computing, vol 704. Springer, Singapore. https://doi.org/10.1007/978-981-10-7898-9_14

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  • DOI: https://doi.org/10.1007/978-981-10-7898-9_14

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