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 2018-01 2 Moncef Gabbouj
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:

Completion parts must belong to the same implementation

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 (alternatively 4th edition)   Yes   
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  

Updated by: Ketola Susanna, 09.03.2018