Module Summary
Module code: EBU723U
Module Title: Image and Video Processing
Semester: 7
Exam marks: 85
Coursework marks: 15
Teaching Hours 40
Lab Hours 6
Tutorial Hours 12
Class tests once every two teaching weeks
Prerequisite BUPT4502 Digital Signal Processing
Module Summary This course provides fundamental knowledge about well-established techniques for digital image and video processing. It covers mathematical models used to analyze still images, technology and standards for image and video compression and the basic methods used to design and develop a wide range of imaging solutions. Such solutions relate to the fields of machine vision, imaging graphics, pattern recognition, medical imaging, image and video coding.
Teaching Schedule
Week 1 Lectures: Introduction (aims, objectives, syllabus, coursework, what you see is what you get). Digital image representation, Sampling, Quantization, Sub-sampling, Pixel interpolation. Histograms: definition, properties, colour histograms, thresholding, segmentation, equalization. Using Matlab for the coursework.
Open office hours: An opportunity for students to ask questions individually.
Week 2 Lectures: Algebraic transformations, Geometric transformations Algebraic transformations, Noise, PSNR, Convolution, Image smoothing and Noise reduction, Colour spaces, Colour images, PGM/PPM images.
Tutorial: A one hour session on material covered so far and example exam questions.
Open office hours: An opportunity for students to ask questions individually.
Coursework: Students are given an in-class MCQ coursework test.
Week 3 Lectures: Edge detection – Gradient, Gaussianfilters, Laplacianfilters, Unsharpmasking, Canny edge detector. Interest points – Definition, Moravecoperator, Evaluation of interest points. Other filters – Min, max, median. JPEG, JPEG2000, JPEG vs. JPEG2000. 2D wavelet decomposition, Tier, Layer, Region of interest (ROI).
Tutorial: A one hour session on material covered so far and example exam questions.
Open office hours: An opportunity for students to ask questions individually.
Week 4 Lectures: Introduction to colour image processing, Pseudo colour image processing, Full-colour image processing basics, Transforming colours, Smoothing and sharpening, Noise in colour images. Motion pictures, Motion field and optical flow, Motion models, Motion estimation, Stereo vision. Redundancy, Video coding standards, Predictive coding, H.261, MPEG-1/2/4/AVC/HEVC. Revsion.
Tutorial: A one hour session on material covered so far and example exam questions.
Open office hours: An opportunity for students to ask questions individually.
Coursework: Students are given an in-class written coursework test.
Coursework description Two in class MCQs, Two laboratory sessions on image processing using Matlab evalauted in-lab and by a report and software
Book The main text recommended is:
GONZALES, R.C. and WOODS, R.E. Digital Image Processing (Prentice Hall 2008) ISBN 978-0135052679