ACS321 Digital Signal Processing

Module Description

This module aims to introduce students to digital processing techniques, including sampling and analysis of digital signals, design of digital filers, and the introduction of digital image processing. Discrete signals and systems are studied, with an emphasis on the frequency-domain theory necessary for the analysis of discrete signals and design of digital filters. The concepts associated with digital images and some basic digital image processing operations are also covered.

Credits: 10 (Spring semester)

Module Leader

Rob HarrisonProfessor Zi-Qiang Lang

If you have any questions about the module please talk to me during the lectures or the labs in the first instance. It is likely that other students will learn from any questions you ask as well, so don’t be afraid to ask.

Outside of lectures please contact me via email, or drop in to see me.

Learning Outcomes

Learning Outcomes

By the end of the module students will be able to:

Explain and apply the key ideas of sampling continuous-time signals. [SM1p, SM2p]
Analyse discrete-time sequences using the tools of discrete Fourier analysis and relate results to their continuous-time counterparts. [SM1p, SM2p]
Explain and analyse the effects of windowing continuous-time signals and make informed choices according to their characteristics. [SM1p, SM2p]
Design finite impulse response and and infinite impulse response digital filters and apply them to practical signal processing problems. [EA1p, EA2p, EA3p]
Define and describe the basic concepts associated with digital images and apply some basic digital image processing algorithms. [SM2p, EA1p, EA3p]

This module satisfies the AHEP3 (Accreditation of Higher Education Programmes, Third Edition) Learning Outcomes that are listed in brackets after each learning outcome above. For further details on AHEP3 Learning Outcomes, see the downloads section of our accreditation webpage.

Syllabus

Syllabus

  • Discrete signals, sampling theorem, discrete Fourier transform, Fast Fourier transform. Goertzel algorithm, commonly used window functions.
  • Discrete time systems and the system frequency response.
  • Discrete filter design: Analogue filter design, IIR discrete filter design. The implementation of digital filters.
  • Pixel, Gray scale, and bits of gray levels of digital images; Histogram and Histogram equalization; Point operations and linear filtering on digital images.
  • Basic concepts and applications of image segmentation.
Teaching Methods

Learning and Teaching Methods

Lectures: 20 hours
Tutorials: 4 hours
Lab Exercises/Classes: 9 hours
Independent Study: 67 hours

Teaching Materials

Learning and Teaching Materials

All teaching materials will be available via MOLE.

Assessment

Assessment

2 hour examination 85%
Lab exercise assignment 15%

No resit examination is available for this module.

Feedback

Feedback

Students will receive feedback via the in-class exercises and lab sessions / coursework.

Student Evaluation

Student Evaluation

Students are encouraged to provide feedback during the module direct to the lecturer. Students will also have the opportunity to provide formal feedback via the Faculty of Engineering Student Evaluation Survey at the end of the module.

Recommended Reading

Recommended Reading

  • Banks, SP, Signal Processing, Image processing, and Pattern Recognition, Prentice Hall, 1990,
  • Gonzalez, RC & Wood, RC, Digital Image Processing, Prentice Hall, 2008, [Available in Information Commons, 621.3670288 (G)]
  • Porat, B, A Course in Digital Signal Processing, John Wiley & Sons, Inc, 1997,
  • Cavicchi, TJ, Digital Signal Processing, John Wiley & Sons, Inc, 2000,
  • Zelniker, G & Taylor,FJ, Advanced Digital Signal Processing, Marcel Dekker, Inc, 1994,