Postgraduate Courses in the
Faculty of Computing Sciences & Engineering
MSc Digital Signal and Image Processing
Introduction
This course is designed to supply the necessary training for graduates to enter industry with software engineering expertise for image processing.
Typically, graduates of this course will find employment as Software Engineers, Technical Advisers or Analyst/Programmers in manufacturing, industry and commerce. Alternatively, their new skills may facilitate their development in previously professional careers.
Who is The Masters Degree For?
The course is a conversion course for graduates from a non-computing subject area but with a numerate academic back-ground. The course can either be taken full-time (one academic year) or part-time over a period of two years.
It is concerned with training students in the art of professional software engineering for building and executing individual image processing modules (forming part of a developing software library) or integrated image processing systems designed specifically for a well defined problem.
No former computing background is required, but the course does assume a basic literacy in graduate mathematics.
Course Structure
The course is organised into two parts; the first part is taught and is based on eight modules delivered over two Semesters. The third Semester is devoted to a research thesis on an industrial project.
In addition to formal lectures, students are invited to attend a series of seminars run by the Department of Mathematical Sciences, in which personnel from both academic and industrial organizations present research papers and information on software products and their applications to image processing and analysis.
| Semester
Module Title |
|
| Semester 1
Programming And Software Engineering Computaional Methods Signal Analysis Digital Signal Processing |
|
| Semester 2
Digital Image Processing Artificial Intelligence Image Understanding Interactive Real-Time Displays |
|
| Summer Period
Project |
Course Syllabus
Semester One
A programming approach to software engineering, covering modular programming in FORTRAN-77 and C, the definition planning and development phases of programming software testing techniques, reliability and maintenance, object oriented programming (in C++).
This module covers numerical methods of solution to the varying types of linear equations which occur in the analysis of discrete systems, in particular those that arise in the design of digital filters. Numerical solutions to the linear eigenvalue problem are also discussed.
Covers the mathematical methods used for describing signals and images and designing algorithms to process them. A large proportion of this course is devoted to Fourier theory which is concerned with the properties of the Fourier transform and its applications. Instruction is also given on different types of integral equations which play an important role in signal processing.
This modules covers a selection of subjects which focus attention on methods of processing digital signals obtained from a variety of systems. Instruction is given on the design, coding and testing of various DSP algorithms to help students construct their own software library.
Semester Two
This module extends the material covered in the signal processing module and explores the software techniques available for restoring and reconstructing images from limited data sets, methods of image enhancement and segmentation techniques. In each case, real problems are considered and instruction given on the mathematical models that are used and the circumstances under which these models and the software derived from them can be employed. As in the signal processing module, students develop a library of functions for image processing which is assessed at the end of the course.
Develops skills in the specification and construction of techniques of artificial intelligence for pattern recognition. Emphasis is placed on the use of Artificial Neural Networks for this purpose. This module includes a taught component on programming in Prolog and the development of expert system shells for image processing.
Illustrates the underlying physical models which are common to most imaging systems. It is shown how an understanding of the 'physics' of an imaging system can provide a mathematical model for data which leads to an (inversion) algorithm for processing an image.
Aims to introduce students to the programming techniques required in the development of interfaces using X-windows development systems such as X-designer, MS Visual C++ (for MS Windows Applications) and J++ for the design of image processing systems.
Summer Period
The project is undertaken in association with an external organization in industry, commerce or the public sector. It is expected that employed part-time students will undertake projects within their places of work. The project provides the opportunity to develop, to demonstrate and to appraise skills acquired from the course in the solution of a real practical problem subject to typical commercial constraints.
Further Information
Assessment
All taught modules are assessed by a combination of examination, course and/or project work. All modules consist of practical programming in which students build up a software library covering many of the data generation and visualization techniques required in a modern signal and image processing system. This library is assessed at the end of the course.
For contact details, see foot of page.
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