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Fiches de cours
Image processing II
MICRO-512
Enseignant(s) :
Liebling Michael Stefan DanielSage Daniel
Unser Michaël
Van De Ville Dimitri Nestor Alice
Langue:
English
Summary
Study of advanced image processing; mathematical imaging. Development of image-processing software and prototyping in JAVA; application to real-world examples in industrial vision and biomedical imaging.Content
- Review of fundamental notions. Multi-dimensional Fourier transform. Convolution. z-transform. Digital filters.
- Continuous representation of discrete data. Splines. Interpolation. Geometric transformations. Multi-scale decomposition (pyramids and wavelets).
- Image transforms. Karhunen-Loève transform (KLT). Discrete cosine transform (DCT). JPEG coding. Image pyramids. Wavelet decomposition.
- Reconstruction from projections. X-ray scanners. Radon transform. Central slice theorem. Filtered backprojection. Iterative methods.
- Deconvolution. Inverse and Wiener filtering. Matrix formulations. Iterative techniques (ART).
- Statistical pattern classification. Decision making. Bayesian classification. Parameter estimation. Supervised learning. Clustering.
- Image analysis. Pixel classification. Contour extraction and representation. Shape. Texture. Snakes and active contours.
Learning Prerequisites
Required courses
Image Processing I
Recommended courses
Signals and Systems I & II, linear algebra, analysis
Important concepts to start the course
Basic image processing and related analytical tools (Fourier transform, z-tranform, etc.)
Learning Outcomes
By the end of the course, the student must be able to:- Construct interpolation models and continuous-discrete representations
- Analyze image transforms
- Design image-reconstruction algorithms
- Formalize multiresolution representations using wavelets
- Design deconvolution algorithms
- Perform image analysis and feature extraction
- Design image-processing software (plugins)
- Synthesize steerable filters
Transversal skills
- Plan and carry out activities in a way which makes optimal use of available time and other resources.
- Manage priorities.
- Access and evaluate appropriate sources of information.
- Use both general and domain specific IT resources and tools
Dans les plans d'études
- SemestrePrintemps
- Forme de l'examenEcrit
- Crédits
3 - Matière examinée
Image processing II - Cours
3 Heure(s) hebdo x 14 semaines
- Semestre
- SemestrePrintemps
- Forme de l'examenEcrit
- Crédits
3 - Matière examinée
Image processing II - Cours
3 Heure(s) hebdo x 14 semaines
- Semestre
Semaine de référence
Lu | Ma | Me | Je | Ve | |
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8-9 | |||||
9-10 | |||||
10-11 | CM011 CO260 CO4 CO5 CO6 ELD020 | ||||
11-12 | |||||
12-13 | |||||
13-14 | |||||
14-15 | |||||
15-16 | |||||
16-17 | |||||
17-18 | |||||
18-19 | |||||
19-20 | |||||
20-21 | |||||
21-22 |
Cours
Exercice, TP
Projet, autre
légende
- Semestre d'automne
- Session d'hiver
- Semestre de printemps
- Session d'été
- Cours en français
- Cours en anglais
- Cours en allemand