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Change Detection in Multitemporal Images Through Single- and Multi-scale Approaches

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Mathematical Models for Remote Sensing Image Processing

Part of the book series: Signals and Communication Technology ((SCT))

Abstract

This chapter presents an analysis of the current status and the challenges in change detection techniques for the analysis of multitemporal SAR images. Algorithms and methods based on validated statistical models for SAR data are investigated, which adopt advanced information-theoretic and multi-scale signal-processing methodologies. After a brief review of the recent literature on general change detection methods, the chapter investigates the specific problem of change detection in SAR images. The main properties of the change detection problem in SAR images are explored and discussed. Then, recent change detection techniques for high-resolution (HR) and very high-resolution (VHR) SAR data are presented and critically analyzed from the theoretical viewpoint. Finally, examples of application of these techniques to real problems are presented by using simulated image pairs and Enhanced Spotlight COSMO-SkyMed images.

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Author information

Authors and Affiliations

  1. Institute of Applied Physics “Nello Carrara”, National Research Council, Via Madonna del Piano 10, 50019, Sesto Fiorentino, Firenze, Italy

    Bruno Aiazzi

  2. Fondazione Bruno Kessler, via Sommarive 18, 38123, Povo, Trento, Italy

    Francesca Bovolo & Davide Pirrone

  3. Department of Information Engineering and Computer Science, University of Trento, via Sommarive 9, 38123, Povo, Trento, Italy

    Lorenzo Bruzzone

  4. Department of Information Engineering and Mathematics, University of Siena, via Roma 56, 53100, Siena, Italy

    Andrea Garzelli & Claudia Zoppetti

Authors
  1. Bruno Aiazzi
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  2. Francesca Bovolo
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  3. Lorenzo Bruzzone
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  4. Andrea Garzelli
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  5. Davide Pirrone
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  6. Claudia Zoppetti
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Corresponding author

Correspondence to Andrea Garzelli .

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Editors and Affiliations

  1. University of Genoa, Genoa, Italy

    Gabriele Moser

  2. Université Côte d’Azur, Inria, Sophia Antipolis Cedex, France

    Josiane Zerubia

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Aiazzi, B., Bovolo, F., Bruzzone, L., Garzelli, A., Pirrone, D., Zoppetti, C. (2018). Change Detection in Multitemporal Images Through Single- and Multi-scale Approaches. In: Moser, G., Zerubia, J. (eds) Mathematical Models for Remote Sensing Image Processing. Signals and Communication Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-66330-2_8

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  • DOI: https://doi.org/10.1007/978-3-319-66330-2_8

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  • Online ISBN: 978-3-319-66330-2

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