EQ2330 Image and Video Processing 7.5 credits

Bild- och videobehandling

Please note

The information on this page is based on a course syllabus that is not yet valid.

This course introduces the principles of digital image and video processing, discusses current image and video processing technology, and provides hands-on experience with image/video processing and communication methods. The course includes topics on image filtering and restoration, image transform algorithms, multiresolution image processing, image matching and segmentation techniques, as well as image and video compression.

  • Education cycle

    Second cycle
  • Main field of study

    Electrical Engineering
  • Grading scale

    A, B, C, D, E, FX, F

Course offerings

Intended learning outcomes

After passing this course, participants should be able to

- describe and use the principles of digital image and video processing to develop image processing algorithms,

- develop image processing algorithms for image filtering and restoration, image transformation and multiresolution processing, image and video compression, as well as image matching and segmentation,

- implement (for example with MatLab) and assess the developed image processing algorithms, 

- explain algorithm design choices using the principles of digital image/video processing,

- develop image processing algorithms for a given practical image/video processing problem

- analyze given image/video processing problems, identify and explain the challenges, propose possible solutions, and explain the chosen algorithm design.

To achive higher grades, participants should also be able to

- solve more advanced problems in all areas mentioned above.

Course main content

This course introduces the principles of digital image and video processing, discusses current image and video processing technology, and provides hands-on experience with image/video processing and communication methods. The course includes topics on image filtering and restoration, image transform algorithms, multiresolution image processing, image matching and segmentation techniques, as well as image and video compression.

Eligibility

For single course students: 120 credits and documented proficiency in English B or equivalent.

Recommended prerequisites

EQ1220 Signal Theory or equivalent

Literature

See course homepage. Preliminary 

R.C. Gonzalez and R.E. Woods: Digital Image Processing, Prentice-Hall

Examination

  • INL1 - Assignment, 1.5, grading scale: P, F
  • TEN1 - Exam, 6.0, grading scale: A, B, C, D, E, FX, F

Requirements for final grade

Preparation assignments, course projects, written examination.

Preparation assignments 1.5 ECTS (P/F). Course Projects 3 ECTS (A-F), Exam 3 ECTS (A-F). The final grade is the average of course projects and exam.

Offered by

EECS/Intelligent Systems

Contact

Markus Flierl (mflierl@kth.se)

Examiner

Markus Flierl <mflierl@kth.se>

Add-on studies

EQ2845 Information Theory and Source Coding

EQ2442 Project Course on Multimedia Signal Processing

EQ2430 Project Course in Signal Processing and Digital Communication

Version

Course syllabus valid from: Spring 2019.
Examination information valid from: Spring 2019.