COURSE UNIT STUDY GUIDE
Course unit : IMAGE PROCESSING; Course code: SPH425
Year 2014/2015: Second semester
Course lecturer: Mr. D. L. Omucheni; Email omucheni@uonbi.ac.ke
Introduction to the course unit
We are in the age multimedia revolution. Due to proliferation of digital cameras, we are not only
consumers but also producers of images. As a result, image processing skills are finding wide
applications in scientific and industrial world. These include areas such as in remote sensing,
microscopy, medical imaging (eg x-ray, and MRI), industrial automation, security systems,
development of intelligent systems, etc.
Aims
This unit aims to introduce students to fundamental concepts of image processing that are
important in understanding image processing technology, literature and their application in
solving practical problems involving images.
Objectives: At the end of the course, students should be able to:
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Demonstrate a basic understanding of the human visual system and its relation to image
processing
Demonstrate a basic understanding of various imaging modalities and image formation
Demonstrate a basic understanding of theory and algorithms commonly used in image
processing
Demonstrate hands-on ability to apply image processing tools using a computer.
Program of lectures and computer lessons
Lectures for this course are held on Tuesdays 2.00-3.00 pm in R222 and on Wednesday 4.006.00pm in R226.
Course Unit content
Week 1: Fundamentals of imaging
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Sampling & Quantization
visual perception
sensing
acquisition,
Week 2: Sources of imaging
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gamma rays
X-rays
UV, Vis,IR
microwaves
radio
acoustic
Electronic
Synthetic
Week 3 & 4: Image Enhancement
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Enhancement in spatial domain
Enhancement in frequency domain
Week 5 & 6: Image Restoration
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noise models
filtering– spatial, frequency domain
estimation of degradation function
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Wiener filter
Week 7: Colour image processing
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colour models
transformations
segmentation noise
Week 8 & 9: Image compression
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Image compression fundamentals and models
loss free and lossless compression
Compression standards
Week 10: Morphological image processing
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Dilation
Erosion
Opening
Closing
Segmentation
Week 11: Object Recognition
Assessment
Two Continuous Assessment Tests (CATs) constitute 30% and final examination 70%
(Total=100%)
Recommended reading
1. Digital Image Processing by Rafael C. Gonzalez & Richard E. Woods
2. Fundamentals of Digital Image Processing- a practical approach with examples in Matlab
by Chris Solomon & Toby Breckon
3. Two-Dimensional Signal and Image Processing by Jae S. Lim
4. Image Processing Principles and Applications by Tinku Acharya & Ajoy K. Ray