Authorised by Academic Registrar, April 1996
Objectives On successfully completing this subject a student should have a working knowledge of digital image processing and the representation of digital data; be able to implement image processing operations to improve the quality of an image; understand the discrete convolution process and spatial filtering; be familiar with methods of representing data in the Fourier domain through the DFT; understand the processes of image segmentation, in particular texture segmentation; be able to apply image processing to selected areas of science, technology and medicine.
Synopsis Point operations: the gray scale histogram (GSH), thresholding, contrast operations, GSH equalisation, LUTs, pseudo-colouring. One-dimensional and two-dimensional spatial operations: discrete convolutions and spatial filtering. One-dimensional and two-dimensional Fourier transforms: the DFT and FFT. The discrete cosine transform. Introduction to other transforms. Image segmentation, feature extraction and pattern recognition. Texture analysis: Laws masks and texture segmentation, statistical models of texture analysis, co-occurrence matrices. Exact and approximate data coding and compression techniques.
Assessment Examination (2 hours): 50% + Laboratory work: 50%