SGN-31007 Advanced Image Processing, 5 cr

Additional information

Suitable for postgraduate studies.

Person responsible

Karen Eguiazarian


Implementation Period Person responsible Requirements
SGN-31007 2019-01 4 Karen Eguiazarian
Sheyda Ghanbaralizadeh Bahnemiri
Peter Kocsis
Final mark is computed based on the units as follows:
- Lecture attendance,
- Project work,
- Classroom exercises,
All units must be passed otherwise final mark is not given

Learning Outcomes

Students get in-depth view of selected advanced topics of image processing and perform practical tasks in image processing laboratory.


Content Core content Complementary knowledge Specialist knowledge
1. Transform-based image representation: unitary (Fourier, DCT, wavelets), redundant (pyramids, wavelet packets)     
2. Image data compression (lossless, near-lossless, lossy)     
3. image restoration (denoising, deblurring, demosaicing, inpainting, etc.)     
4. study of selected topics in image processing: projects     

Instructions for students on how to achieve the learning outcomes

Course grade is computed based on four units as follows: Lectures attendance: mandatory, Classroom exercises: 50% of the mark. Project work: 50 % of the mark. All units must be passed otherwise final mark is not given. There is no exam.

Assessment scale:

Numerical evaluation scale (0-5)

Study material

Type Name Author ISBN URL Additional information Examination material
Book   Digital Image Processing   R. Gonzalez and R. Woods         No   
Book   Local Approximations in Signal and Image Processing   V.Katkovnik, K.Egiazarian, and J.Astola         No   
Lecture slides     K. Egiazarian         No   


Course Mandatory/Advisable Description
SGN-11007 Introduction to Signal Processing Mandatory   1
SGN-12007 Introduction to Image and Video Processing Mandatory   2
SGN-11000 Signaalinkäsittelyn perusteet Mandatory    

1 . Either SGN-11006 or SGN-11007

2 . Either SGN-12006 or SGN-12007 or SGN-12000

Correspondence of content

Course Corresponds course  Description 
SGN-31007 Advanced Image Processing, 5 cr SGN-31006 Image and Video Processing Techniques, 6 cr Muutettu takaisin uusi vastaa vanhaa HOPSin käyttäytymisen vuoski 27.6.2018 jk  

Updated by: Kämäräinen Joni, 10.06.2019