Module overview
Signal processing is an essential part of human life and of modern industrial systems. As humans we see and hear and process signals. This is the same in electronic systems: we sense and then process signals. We need to be able to understand these signals, sometimes to interpret them, sometimes to filter them and sometimes to develop systems to process them automatically. That is what this module is about, and we shall apply the processes to images and to music in continuous and discrete
systems.
Linked modules
Pre-requisite: ELEC2220 or ELEC2226
Aims and Objectives
Learning Outcomes
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- Apply signal and image processing in research and industrial environments
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Apply signal processing techniques to understand and analyse 1-dimensional and 2-dimensional signals
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Demonstrate knowledge and understanding of frequency domain analysis and synthesis. Be able to use basic techniques to process 1-dimensional signals. Be able to implement standard approaches to process 2-dimensional images
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- Understand the basic approaches in a technology fundamental to perception of signals
Syllabus
- Statistical signal processing [rm1]
- Human audiovisual system
- Continuous Fourier analysis, Fourier transform (FT). Amplitude and power spectrums for
- periodic and non-periodic signals. Power spectral analysis and cosine transform (CT)
- Convolution, correlation and Fourier Transform
- Analogue filter design
- Sampling and aliasing
- Discrete signal analysis and z transforms
- Discrete FT (Fast FT – FFT; Discrete CT - DCT)
Digital filters and their design (FIR and IIR)
- Random signals
- Adaptive filtering
- 2D FTs (difference between 2D and 1D, 2D DCT)
- Mpeg (music) and jpeg (image) coding
- Point and group image operators (and convolution)
- Edge detection in images
- Image shape extraction (Template matching, HT and correlation)
- Shape extraction by evolution
- Image filtering
- Image restoration
Learning and Teaching
| Type | Hours |
|---|---|
| Wider reading or practice | 65 |
| Completion of assessment task | 3 |
| Revision | 10 |
| Follow-up work | 18 |
| Preparation for scheduled sessions | 18 |
| Lecture | 36 |
| Total study time | 150 |
Resources & Reading list
Textbooks
Haykin (2003). Signals and Systems.
Mandal and Asif (2007). Continuous and Discrete Time Signals and Systems.
Nixon and Aguado (2012). Feature Extraction & Image Processing for Computer Vision,.
(2013). Schaum's Outline of Signals and Systems. Schaum's Outline Series.
Oppenheim and Schafer (2013). Discrete-Time Signal Processing.
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Examination | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Examination | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Examination | 100% |
Repeat Information
Repeat type: Internal & External