Module Handbook

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COURSE DESCRIPTION The course consists of theoretical material introducing the mathematics of images and imaging. Topics include representation of two-dimensional data, time and frequency domain representations, filtering and enhancement, the Fourier transform, convolution, interpolation, color images. The student will become familiar with Image Enhancement, Image Restoration, Wavelets and Multi-resolution Processing, Image Compression, Morphological Image Processing, Image Segmentation, Representation and Description, and Object Recognition. More specific: ? Digital Image Fundamentals. ? Image Enhancement in the Spatial Domain. ? Image Enhancement in the Frequency Domain. ? Image Restoration. ? Color Image Processing. ? Wavelets and Multi-resolution Processing. ? Image Compression. ? Morphological Image Processing. ? Image Segmentation. ? Representation and Description. ? Object Recognition. 


On successful completion of this course students will be able to:

·                Demonstrate a knowledge of a broad range of fundamental image processing and image analysis techniques and concepts (linear and non-linear filtering, denoising, deblurring, edge detection, line finding, detection, morphological operators, compression, shape metrics and feature based recognition)

·                   Identify, Demonstrate and apply their knowledge by analyzing image processing problems and recognizing and employing (or proposing) effective solutions

·             Design and create practical solutions to a range of common image processing problems and to critically assess the results of their solutions, including shortcomings