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Location: Courses shall take place every Monday from 9:00 to 12:00, from January 10th until March 21st 2021 at ENS Paris-Saclay, 4 Avenue des Sciences, 91190 Gif-sur-Yvette, France.

Network & Server access: For the practical work (TPs) you must bring your own laptop and configure it to connect to the eduroam WiFi network.

Access the TPs here (password will be provided during the lecture)

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

Emanuele Dalsasso,
Carlo de Franchis,
Gabriele Facciolo,
Enric Meinhardt,
Florence Tupin

Evaluation

  • Practical works (to be delivered on the same day as the TPs): 25% of the grade
  • Group project (20h): 75% of the grade

Syllabus

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Bibliography

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Where & When

École normale supérieure Paris-Saclay,
4 Avenue des Sciences, 91190 Gif-sur-Yvette, France.

Courses shall take place Mondays from 9:00 to 12:00, from January to March.

Schedule 2022

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DateRoomTopic
Jan 101N821) What can be seen from space ?
Jan 171N822) Geometric modeling of optical satellites and application to 3D reconstruction
Jan 241Z713) Modeling a Synthetic Aperture Radar instrument
Jan 311Z714) How to recover 3D information with optical sensors ?
Feb 71Z715) Sub-pixel matching and super-resolution
Feb 14*1N82*6) How to recover 3D information with SAR sensors ?
Feb 21 1Z717) Generation and exploitation of 3D data
Feb 28Project Work
Mar 71Z718) Processing and exploitation of SAR data
Mar 141Z719) Optical & SAR time series analysis
Mar 211Z71Project Presentations