Edinburgh International Conference Centre
Edinburgh, United Kingdom
21 - 24 September 2020
Conference RS107
Image and Signal Processing for Remote Sensing
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Abstract Due:
13 May 2020
Submit your abstract now. Post-deadline submissions are encouraged.

Author Notification:
5 July 2020

Manuscript Due Date:
26 August 2020

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Conference Chair
Conference Co-Chairs
Program Committee
Program Committee continued...
  • Peijun Du, Nanjing Univ. (China)
  • Andrea Garzelli, Univ. degli Studi di Siena (Italy)
  • Jordi Inglada, Ctr. d'Etudes Spatiales de la Biosphère (France)
  • Jun Li, Sun Yat-Sen Univ. (China)
  • Sicong Liu, Tongji Univ. (China)
  • Allan A. Nielsen, Technical Univ. of Denmark (Denmark)
  • Claudia Paris, Univ. degli Studi di Trento (Italy)
  • David Small, Univ. Zürich (Switzerland)
  • Florence Tupin, Télécom ParisTech (France)
  • Benoit Vozel, Univ. de Rennes 1 (France)
  • Josiane B. Zerubia, INRIA Sophia Antipolis - Méditerranée (France)

Call for
The main goal of this conference is to address advanced topics related to signal processing, image analysis, pattern recognition, machine learning and data fusion methodologies in the field of remote sensing.

Papers describing recent and original work in the following and related research topics are welcome:

  • calibration and registration
  • image enhancement and restoration
  • edge detection and segmentation
  • target detection and object recognition
  • automatic classification
  • estimation of geo- bio-physical parameters
  • machine learning and deep learning
  • analysis of big data
  • change detection and analysis of image time series
  • analysis of multispectral and hyperspectral images
  • analysis of SAR and LIDAR signals
  • multisensor and multisource data fusion
  • data mining techniques
  • image coding and data compression
  • remote sensing applications
  • satellite, airborne and UAV remote sensing.

  • Note: To assure a high quality conference, all abstracts will be reviewed by the conference scientific committee and co-chairs for technical merit and content.

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