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Digital Signal and Image Processing

Semester 2

This course reviews the basics of DSP – building on the fundamentals taught in ELET2460 – before moving to more advanced concepts of signal processing. In the first part of the course the students will be taken through the processes required for digital filter design, starting with the basic methods and moving on to more sophisticated techniques. Digital imaging processing will be covered in the second module. The tools and techniques employed in basic image processing (compression and de-noising) will be addressed; this will provide the student with the capacity to grasp the more complex concepts and techniques employed in modern image processing applications.

Given that DSP is essentially about the manipulation of real-world signals, the tools, techniques and approaches to problem-solving taught in this course can be applied in disparate fields, from telecommunications to medical imaging, video and audio processing for law enforcement, to investment banking.


Overview of a Digital Signal Processor. Transfer Functions of Filters. FIR vs. IIR. Linear phase FIR. All Pass filters. Implementing FIR filters. Window approach. Linear phase types 1-4. Optimal fit Algorithms. Implementing IIR filters. Bi-linear and Impulse Invariant Transforms. Direct Form 1 & 2 Structures.  Effects of Finite Number Operations. Use of second order sections. Noise and instability. Generating signals with DSPs. Structure use of Adaptive Filters. Implementing of FFT on a Digital Signal processing platform.


One 2-hour final exam                                      60%

One 1-hour in-course tests                                            20%

Five Take home assignments (equal weighting)  20%

Learning Objectives: 


  • Review of areas covered at Level 2 Signal and Systems:
    • Overview A/D and D/A Conversion, Sampling, Quantizing and Encoding, I/O devices, DSP hardware, Fixed and floating point devices; Frequency Domain analysis; DSP Fundamentals
  •  Digital Filter Design:
    •  FIR and IIR filters. Linear phase FIR filters; All Pass filters. Implementing FIR Filters; Window approach; Linear phase types 1-4; Optimal fit Algorithms. Implementing IIR filters; Bi-linear and Impulse Invariant Transforms
  • DSP Structures:
    • Direct Form 1 & 2 Structures. Effects of Signal Digitisation; Signal Sampling and Reconstruction; Effects of Finite Number Operations; Use of second order sections; Noise and instability. Structure and use of Adaptive Filters; Least-squares error requirement for adaptive filter design


  • Introduction to Digital Image Processing:
    •  Image Acquisition; Representing Digital Images; Pixel Relationships
  • Basic Image Operations:
    • Histogram Equalisation; Histogram Matching; Image Subtraction; Image Averaging
  • Frequency Domain Image Enhancement:
    • Use of the Fourier Transform in Image Enhancement; Fourier Transform-based Smoothing ; Fourier Transform-based Sharpening
  • Image Compression:
    • Error-free Compression; Lossy Compression; Image Compression Standards
  • Image Segmentation:
  • Point Detection; Line Detection; Edge Detection

Text Book:

  • Oppenheim, A. V. &  Schafer, R.W. (2010) Discrete Time Signal Processing. Pearson Publication. ISBN 978-0132-06709-6
  • Gonzalez, R. C. & Woods, R. E. (2007) Digital Image Processing (3rd Edition). Prentice Hall. ISBN 978-0131-68728-8

Supplemental Reading :

  • Blanchet, G. & Charbit, M. (2009) Digital Image Processing Using MATLAB, 2nd ed. Gatesmark Publishing. ISBN 978-0982-08540-0
  • Engelberg, S. (2010) Digital Signal Processing: An Experimental Approach (Signals and Communication Technology). Springer. ISBN 978-1849-96730-3

Internet Resources:

1.      DSP lectures by IIT Professor Dutta Roy:

2.      Image Processing Tutorials:

3.      Online text - The Scientist and Engineer's Guide to Digital Signal Processing

4.      Matlab Online tutorial

Course Code: 
3 Credits
Level 3
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