School of Computer Science

Module 06-28732 (2019)

Digital Image Processing and Analysis

Level 1/C

Ela Claridge Semester 2 20 credits
Co-ordinator: Ela Claridge
Reviewer: Hamid Dehghani

The Module Description is a strict subset of this Syllabus Page.


This course will cover the fundamentals and practical application of digital image processing. The topics include: * Image formation: from a physical scene to a digital image; * Colour images: human colour perception and digital representations; * Improving image quality: de-noising, de-blurring, contrast enhancement; * Image segmentation: partitioning the scene into meaningful objects; * Detection, counting and localising: what and where of image objects; * Image registration: how to align or stitch images together; * Beyond colour: multispectral images; * Applications (e.g. medicine, biology, remote sensing, astronomy, food, forensics) * Overview of advanced topics

Learning Outcomes

On successful completion of this module, the student should be able to:

  • Describe the basic concepts of image processing and image analysis.
  • Discuss the advantages and drawbacks of different methods.
  • Make informed choices about what methods to apply to solve specific image processing problems.

Teaching methods

Lectures, to introduce topics and their underpinning scientific background. Demonstrations, to introduce practical image processing tools (ImageJ / Fiji). Work-based learning through weekly (unassessed) exercises and recommended reading.


Assessments: Three MCQ tests (15% each), 1.5hr examination (55%). Reassessment: 1.5hr Examination (55%) with MCQ marks (45%) carried forward.