Image and video processing
Summary
This course covers fundamental notions in image and video processing, as well as covers most popular tools used, such as edge detection, motion estimation, segmentation, and compression. It is composed of lectures, laboratory sessions, and mini-projects.
Content
Introduction, acquisition, restitution
Two-dimensionnal signals and systems, Elementary signals, Properties of two-dimentional Fourier transform, Discretization (spatial and spatio-temporal artefacts), Two-dimensional digital filters, Two-dimensional z-transform, Transfer function. Captors, monitors, printers, half-toning, color spaces.
Multi-dimensional filtres
Design of Infinite Impulse Response and Finite Impulse Response filters, Implementation of multi-dimensional filters, Directional decomposition and directional filters, M-D Sub-band filters, M-D Wavelets.
Visual perception
Neural system, Eye, Retina, Visual cortex, Model of visual system, Special effects, Mach phenomena and lateral inhibition, Color, Temporal vision.
Contour and feature extraction, segmentation
Local methods, Region based methods, Global methods, Canny, Mathematical morphology. Segmentation, Motion estimation
Visual information coding
Overview of the information theory and basics of rate-distortion, Conventional techniques : predictive coding, transform coding, subband coding, vector quantization, Advanced methods : multiresolution coding, perception based coding, region based coding, directional coding, fractals, Video coding : motion compensation, digital TV, High definition TV. Standards: JPEG, MPEG, H.261, H.263
Keywords
Contour detection, motion estimation, segmentation, human visual system, image compression, video compression
Learning Prerequisites
Required courses
Fundamental notions of signal processing
Recommended courses
Signal processing for communication
Important concepts to start the course
Sampling, quantization, transforms, programming, algorithms, systems
Learning Outcomes
By the end of the course, the student must be able to:
- Create simple image processing systems
- Create simple video processing systems
- Compare image processing tools
- Compare video processing tools
- Select appropriately optimal image and video processing tools
Transversal skills
- Make an oral presentation.
- Write a scientific or technical report.
Teaching methods
Ex cathedra, laboratory sessions, mini-projects
Expected student activities
Written report of laboratory sessions, oral presentation of mini-projects, comprehension of various notions presented during the course, resolve simple problems of image and video processing.
Assessment methods
Laboratories, mini-project, oral exam
Supervision
| Others | Students are encouraged to ask for appoitment with the professor any time outside of teaching hours |
Resources
Bibliography
handouts of image and video processing course
Fundamentals of Digital Image Processing, A. K. Jain
Ressources en bibliothèque
Prerequisite for
Semester projects , master thesis projects, doctoral thesis
In the programs
- Semester: Fall
- Exam form: Oral (winter session)
- Subject examined: Image and video processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Semester: Fall
- Exam form: Oral (winter session)
- Subject examined: Image and video processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Semester: Fall
- Exam form: Oral (winter session)
- Subject examined: Image and video processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Semester: Fall
- Exam form: Oral (winter session)
- Subject examined: Image and video processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
Reference week
| Mo | Tu | We | Th | Fr | |
| 8-9 | |||||
| 9-10 | |||||
| 10-11 | |||||
| 11-12 | |||||
| 12-13 | |||||
| 13-14 | |||||
| 14-15 | |||||
| 15-16 | |||||
| 16-17 | |||||
| 17-18 | |||||
| 18-19 | |||||
| 19-20 | |||||
| 20-21 | |||||
| 21-22 |
Légendes:
Lecture
Exercise, TP
Project, other