Module Information

Module Identifier
Module Title
Image Processing
Academic Year
Semester 1
CS10510 or CS20410 or mathematical equivalent
Other Staff

Course Delivery

Delivery Type Delivery length / details
Lecture 15 Hours .
Other 3 x 1 hour workshops
Other At least 4 x 1 hour demonstration sessions


Assessment Type Assessment length / details Proportion
Semester Assessment Comparison scientific paper (8 pages in LNCS format) based on a set of selected image processing topics.  60%
Semester Assessment Demonstration based on the above paper to be delivered to the peer group.  40%
Supplementary Assessment Scientific paper.  100%

Learning Outcomes

On successful completion of this module students should be able to:

express a consolidated and extended understanding and knowledge of various image processing topics and techniques: colour space, image formation, image compression, image enhancement, image features, texture, and classification.

compare, critically evaluate and discuss alternative techniques.

describe a method and design experiments to evaluate techniques.


The module is intended to introduce basic image processing topics and techniques. The manipulation of image data can be seen as fundamental to a number of advanced computer vision, visualization, and game aspects. In addition, the development of digital imaging in main-stream life makes this unit stands on its own as well.

Brief description

The module will form a generic introduction to image processing. It will start with the image formation and compression process. Subsequently several image filtering techniques will be discussed in order to enhance images. The use of these techniques with regard to image features, texture, and classification will be covered. It will make clear links between programming and image processing. In the workshops, how to do experimental study of some selected image processing topics from data collection, algorithm development and analysis, programming and implementation, result analysis, and how to write a scientific paper will be discussed.


Introduction to Image Processing (1 lecture)

Mathematical Techniques (2 lectures)

Colour Space (1 lecture)

Image Formation (1 lecture)

Image Compression (2 lectures)

Image Enhancement (2 lectures)

Image Features (2 lectures)

Texture (2 lectures)

Classification (2 lectures)

Module Skills

Skills Type Skills details
Communication Covered by demonstration of selected image processing topics.
Personal Development and Career planning Peer assessment. The assessment mimics a scientific conference.
Problem solving Analysis and evaluation of image processing techniques
Research skills Covered by directed reading and scientific review paper

Reading List

Essential Reading
Nick Efford (2000) Digital Image Processing: a practical introduction using Java Pearson Education Limited Primo search Rafael C. Gonzalez, Richard E. Woods (2002) Digital Image Processing, Second edition Prentice-Hall, Inc. Primo search


This module is at CQFW Level 5