Mathematics for Technical Visualization (MATLD0131), 5 op

Perustiedot

Esitietovaatimukset

Engineering Mathematics and Mathematics for Multimedia

Sisältö (ydinaines ja -osaaminen)

Applied statistics in image processing: distributions, conditional probabilities, central limit theorem. Basics of information theory, redundancy, compression ratio. Mathematics of colour, colour spaces and colour processing. Fourier analysis of signals esp. digital images: frequency domain processing; sampling principles; amplitude and phase spectrum of a signal. Filtering in frequency domain; image enhancement in frequency domain: e.g. removing noise from a digital image.

Sisältö (täydentävä ja erityisosaaminen)

Boosting masks; Laplacian of a signal in edge enhancement. Bayer filter pattern of a colour image. Basics of data compression methods: reducing redundancy of data.

Tiedolliset oppimistulokset (ydinaines ja -osaaminen)

After completing the course the student will know different ways to represent the results of technical activity visually. Will be able to tell data and information apart. Will understand basic concepts in statistics, information theory and in colour processing. Will know what kind of information is related to a signal in frequency domain. Will know some principles how to extract information from data.

Taidolliset oppimistulokset (ydinaines ja -osaaminen)

After completing the course the student will be able to enhance images in frequency domain by a computer. Will be able to carry out colour image processing by a computer.

Kirjallisuus ja muu materiaali

Opetusmenetelmät

Opiskelijan kuormittavuus

Luennot - 28
Itsenäinen työskentely ja kirjallisuuteen tutustuminen - 60
Tentti - 5
Projekti - 20
Laboratoriotyöt - 42

Arvioinnin perusteet

Two examinations with approval (at least 40% of the maximum), laboratory exercises and a final project.

Koulutusohjelmakohtaiset kompetenssit