SGN-12007 Introduction to Image and Video Processing, 5 cr
Additional information
This course is equivalent to SGN-12001
Person responsible
Sari Peltonen, Jenni Raitoharju, Moncef Gabbouj
Lessons
| Implementation | Period | Person responsible | Requirements |
| SGN-12007 2019-01 | 2 |
Moncef Gabbouj Anton Muravev Sari Peltonen Jenni Raitoharju |
Accepted exercises, assignment and exam. |
Learning Outcomes
After completing the course, the student is able to - explain the basics of human visual system, brightness adaptation and discrimination, image formation, image sampling and quantization, - present verbally or with mathematical formulas the spatial and frequency domain enhancement and restoration methods considered on the course for digital gray-scale images, - calculate outputs of the methods for simple images using the calculator, - explain the basics of color vision and pseudocolor images and the color models considered on the course, - explain the basic concepts of video processing, - implement covered operations independently for images using Matlab software.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Definition and representation of digital image, basics of the human visual system, brightness adaptation and discrimination, image formation, two-dimensional sampling and quantization | History of digital image processing, application areas and basic relationships between pixels | |
| 2. | Image enhancement and restoration both in spatial and frequency domains, two-dimensional discrete Fourier transform and classes of spatial and frequency domain filters | Continuous two-dimensional Fourier transform, properties of the two-dimensional discrete Fourier transform, other transforms and mathematical representation of individual filters | Mathematical derivation of the properties of the two-dimensional discrete Fourier transform |
| 3. | The basics of color vision, color models and pseudocolor images | Color transformations between color models, color image smoothing and sharpening | |
| 4. | The basics of video processing, video file formats, resolutions and bit rates | Video enhancement | |
| 5. | Motion analysis and estimation, motion compensated filtering, deinterlacing and sampling rate conversion | MPEG standards | |
| 6. | Topics of the possible visiting lecture | Details of the possible visiting lecture |
Instructions for students on how to achieve the learning outcomes
The grade is determined by the exam (max 30 p.), exercises bonus (max 2 p.) and assignment bonus (max 2 p.). To pass the course the students has to have 8 out of 12 exercises accepted, assignment accepted and at to get least half of the exam maximum points. Exercises bonus (max 2 p.) and assignment bonus (max 2 p.) are valid only for the 3 exams of this implementation of the course. For the grade 3 the student should master the core content well. To obtain grade 4 student should also master some of the complementary knowledge. Student has the possibility to obtain grade 5 if he/she master well the complementary knowledge. If the students has minor lack of knowledge in core content he/she has possibility to obtain grade 1 or 2 depending on the amount of lacking knowledge. If there is serious lack of knowledge in core content, the student will not pass the course.
Assessment scale:
Numerical evaluation scale (0-5)
Partial passing:
Study material
| Type | Name | Author | ISBN | URL | Additional information | Examination material |
| Book | Digital Image Processing | Gonzalez, Woods | 9780131687288 | 3rd edition, Prentice-Hall, New Jersey, 2008 | No | |
| Book | Practical Image and Video Processing Using MATLAB | Marques | 9781118093467 | No | ||
| Book | Video Processing and Communications | Wang, Ostermann, Zhang | 130175471 | No | ||
| Lecture slides | Moncef Gabbouj | Lecture notes shall be supplemented by materials from Chapters 1-6 of Digital Image Processing book. | Yes |
Prerequisites
| Course | Mandatory/Advisable | Description |
| SGN-11007 Introduction to Signal Processing | Mandatory |
Additional information about prerequisites
Either SGN-11007 or equivalent knowledge of the basics of digital signal processing is required.
Correspondence of content
| Course | Corresponds course | Description |
| SGN-12007 Introduction to Image and Video Processing, 5 cr | SGN-12006 Basic Course in Image and Video Processing, 5 cr | |
| SGN-12007 Introduction to Image and Video Processing, 5 cr | SGN-12001 Introduction to Image and Video Processing, 5 cr |