Prè-requis
Basics of Fourier analysis and differential calculus.
Objectif du cours
Explore ways (and applications) of linking continuous and discrete image models: How to translate a continuous image processing model into a discrete numerical algorithm? Conversely, how to extract geometric informations from a discrete array of pixels?
Presentation : here
Organisation des séances
Half of course sessions, half of exercise/computer practice sessions
Mode de validation
Project or exam.
Références
- L. Moisan, Modeling and Image Processing (available on the course web page)
- L. Moisan, « Periodic plus smooth image decomposition », Journal of Mathematical Imaging and Vision, vol 39:2, pp. 161-179, 2011 (available on the course web page)
Thèmes abordés
- The image formation process: geometry, diffraction, sampling
- FFT- and Spline-based interpolations, lossless geometric transforms
- Image reduction and the aliasing/ringing/blur trade-off
- Implementation of differential operators, image iterative filtering
- Sub-pixel image geometry
- Phase spectrum and applications: sharpness metrics, texture synthesis
Les intervenants
Lionel MOISAN
(Université Paris Cité)
