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https://listes.telecom-paristech.fr/mailman/listinfo/mvaisat

Location: Courses shall take place every Thursday morning (9 to 12:30) from January 17th until march 28th at Télécom ParisTech, 46 rue Barrault, 75013 Paris.

Building access: In order to ensure your admission to the building, please bring your ID card + student’s card (mentioning Université Paris-Saclay).

Network & Server access: For the practical work (TPs) we recommend that you:

  • bring your own laptop if you have one and configure it to connect to connect to the eduroam WiFi network (desktop PCs are also available if you do not have your own laptop).
  • open a student account at Telecom ParisTech via https://moncompte.telecom-paristech.fr/master_upsay/ you may need it to access the TP workstations and servers.

Abstract

If there is one source of big data today, it is the continuous stream of high-resolution images from Earth observation satellites. The combined bandwidth of all commercial satellites is of several Terabytes per hour. A good understanding of these systems and instruments allows to fully take advantage of this source of information. This course is a well balanced mix of mathematical modeling of these systems and practical works handling remote sensing images retrieved either from space agencies or private providers to solve real-scale imaging problems.

The following issues are addressed during the course: (1) modeling of optical and SAR (Synthetic Aperture Radar) acquisition systems and radiometric and geometric corrections; (2) recovering 3D information from optical and SAR sensors (stereo-vision and multi-stereo, point matching, sub-pixel accuracy, interferometry), (3) time series creation and analysis (change detection, multi-temporal change analysis, either on single modality or combining heterogeneous sensors). The required mathematical tools are introduced along the way. Namely, variational calculus, discrete and continuous optimization, approximation theory and spectral analysis, mathematical morphology, statistical modeling and inference.

The courses will be closely linked to practical work sessions (during the course or to do on your own) giving you a straightforward expertise to handle these data. Usage of a personal laptop is encouraged for practical sessions.

Evaluation is done through practical works and a project done all along the period. The projects are dedicated to current issues raised by the newly launched or upcoming sensors and rely on machine learning and/or image processing methods.

Teaching staff

Andrés Almansa,
Carlo de Franchis,
Gabriele Facciolo,
Enric Meinhardt,
Jean-Marie Nicolas,
Florence Tupin

Syllabus

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Bibliography

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Where & When

Telecom ParisTech (Ecole Nationale Supérieure des Télécommunications)
46 rue Barrault
75013 Paris
access map to Telecom ParisTech’s rue Barrault site.
Find a classroom.

Courses shall take place Thursdays from 9:00 to 12:30, from January to March 2019.

Schedule

[…]

DateRoomTopic
Jan 17Amphi Opale1) What can be seen from space ?
Jan 24G6-12) Modeling an optical instrument
Jan 31Amphi Opale3) Modeling a Synthetic Aperture Radar instrument
Feb 07C474) How to recover 3D information with optic sensors ?
Feb 14Amphi Opale5) How to recover 3D information with SAR sensors ?
Feb 21Amphi Opale6) Processing and exploitation of SAR data
Feb 28C477) Sub-pixel accuracy in stereo matching with low baseline
Mar 07G6-18) Generation and exploitation of 3D data
Mar 14G6-19) Optic & SAR Time series analysis
Mar 21C47Project work
Mar 28G6-1Project Presentations

Previous versions of the course

This course changed significantly from previous year’s course. The course description as of 2012-2017 is still available in this archive site.