POISTETTU: Digitaalinen kuvankäsittelyLaajuus (5 op)

Osaamistavoitteet

Upon completion of the course the student: - understands the basic theory of digital image processing and knows its main applications, - is able to apply spatial and frequency domain methods in image enhancement, restoration, compression, morphological processing and segmentation.

Sisältö

- Introduction - Fundamentals of digital image - Intensity transformations and spatial filtering - Image processing in frequency domain - Restoration - Color image processing - Compression - Morphological image processing - Segmentation

Esitietovaatimukset

Recommended prior courses: 521141P Elementary Programming or equivalent Python programming skills, 031080A Signal Analysis or basic knowledge on signal processing, and basic engineering mathematics.

Arviointikriteerit, tyydyttävä (1)

The grading is based on the points collected from exams and the homework assignments. More specific criteria are published in Moodle.

Oppimateriaalit

Lecture and exercise material, online lecture videos, Jupyter notebook guides and tutorials.

Lisätiedot

The course is organized in the spring semesters 2024 and 2025 (period 4) and in the autumn semester 2025 (period 2).

Toteutustavat

Lectures 20 h, exercises 14 h and homework assignments 30 h. The rest is independent work. Mode of delivery: blended teaching.

Suoritustavat

The course is completed by collecting enough points from exams (in-class quizzes or a final exam) and homework assignments.