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Department of Electronic & Electrical Engineering, Unit Catalogue 2009/10


EE40054: Digital image processing

Click here for further information Credits: 6
Click here for further information Level: Masters
Click here for further information Period: Semester 1
Click here for further information Assessment: CW 25%, EX 75%
Click here for further informationSupplementary Assessment: Like-for-like reassessment (where allowed by programme regulations)
Click here for further information Requisites:
Description: Aims:
The aim of this unit is to introduce the theory and practice of digital image processing.

Learning Outcomes:
After completing this unit students should be able to:
* Explain the elements of human vision system including monochrome and colour vision and perception.
* Describe the components of a digital image processing system and the digital representation of monochrome and colour images.
* Understand and apply a range of image enhancement techniques, including linear, non-linear and temporal filters.
* Implement both first and second order edge detection algorithms and explain their relative merits.
* Describe the operation of a variety of featured extraction techniques.
* Understand the main properties of various image transforms and explain transform domain filtering.
* Explain the role of relaxation labelling in image interpretation.

Skills:
Application of the techniques introduced in the lectures to practical image processing problems: taught, facilitated and tested.

Content:
The human vision system: monochrome and colour vision, perception. Digital imaging systems: system model, sampling and quantisation. Image enhancement: point operators and neighbourhood operators, linear and non-linear filters, spatio-temporal filtering. Image interpretation: edge detection, feature extraction and classification. Transforms: transform properties and uses, specific transforms including the two-dimensional Fourier and cosine, Karhunen-Loève, Walsh and Wavelet transforms. Colour: colour models, pseudo- and full-colour image processing. Scene labelling: discrete and probabilistic relaxation.
NB. Programmes and units are subject to change at any time, in accordance with normal University procedures.