Course information
ECS605U/ECS776P - Image
Processing
Aims
The main purpose of this course is to provide an introduction to the knowledge and methodologies for digital image processing.
Prerequisites
Some mathematical background, such as calculus, complex arithmetic, statistics, linear algebra, basic understanding of signal processing (Fourier transform), some programming experience.
Objectives
- Be able to implement low level image processing algorithms.
- Understand image file formats
- Implement contrast enhancement by histogram manipulation
- Know frequency domain transform methods
- Use filtering algorithms for image smoothing and sharpening
- Ability to undertake independent advanced scholarship
- Ability to interpret/ conceptualise/ independently evaluate techniques and applications of techniques in this field of study
- An awareness of the wider context and critical issues surrounding this field of study
Description
This course gives students an introduction to digital image processing and uses a programming language Java to implement simple applications in low level image processing. Areas covered include image representation, image sampling and display, and image transforms and image enhancement using point and spatial operations. Also considered are image processing methods such as convolution, frequency filtering and image restoration, compression and segmentation.
Assessment
One 2 hour examination for 80% and assessed coursework for 20%
Reading
Textbook:
Digital
Image Processing
(Global Edition, 4th Edition), by Rafael C. Gonzalez, and Richard E. Woods,
1024 pages, Pearson, 2017, ISBN13: 9781292223049, ISBN10: 1292223049.
Reference book:
Digital Image Processing Using MATLAB, by Rafael C. Gonzalez, Richard E.
Woods, Steven L. Eddins, 827 pages, Gatesmark Publishing; 2nd edition (2009), ISBN-10:
0982085400, ISBN-13: 978-0982085400.
Reference journals:
IEEE Trans. Image Processing
IEEE Trans. Signal Processing
IEEE Trans. Medical Imaging
Computer Vision and Image Understanding (CVIU)
Graphical Modeling and Image Processing
Computer Vision, Graphics and Image Processing (CVGIP)
Reference conference proceedings:
British Machine Vision Conference (BMVC)
International Conference on Image Processing (ICIP)
IEEE International Conference on Computer Vision (ICCV)
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)
Webpages and Mailing Lists
The Course
- : http://www.eecs.qmul.ac.uk/~phao/IP/
The Course - QM+ : http://qmplus.qmul.ac.uk/course/view.php?id=3252
The Course - Image Processing labs: http://www.eecs.qmul.ac.uk/~phao/IP/Labs/
The Course
- Lecture notes (image processing): http://www.eecs.qmul.ac.uk/~phao/IP/Notes/
The Course
- Coursework: http://www.eecs.qmul.ac.uk/~phao/IP/Labs/cwk/
The Course
- Mailing lists: ECS605U@lists.eecs.qmul.ac.uk;
ECS776P@lists.eecs.qmul.ac.uk
Test images (RAW, BMP, and TIF formats): http://www.eecs.qmul.ac.uk/~phao/IP/Images
The text
book website: http://www.imageprocessingplace.com/
Past exam papers are available on QM+.
Teaching
Image processing: Pengwei Hao (p.hao@qmul.ac.uk)
Labs and exercises: Bingqing Guo (b.guo@qmul.ac.uk), Xindi Zhang (xindi.zhang@qmul.ac.uk) .
Schedule (tentative)
|
Teaching |
Lectures |
DIP Reading Sections |
Lab Session |
|
Week 1 |
Introduction |
Chapter 1 |
No Lab Session |
|
Week 2 |
Image representation, sampling and quantization |
Chapter 2 |
Session 1 |
|
Week 3 |
Point processing for image enhancement |
Chapter 3 |
Session 2 |
|
Week 4 |
image histogram |
Chapter 3 |
Session 3 |
|
Week 5 |
Image filtering/convolution, smoothing and sharpening |
Chapter 3 |
Session 4 |
|
Week 6 |
Fourier transform |
Chapter 4 |
Session 5 |
|
Week 7 |
Review and Feedback Week |
Session 6 |
|
|
Week 8 |
Image enhancement in frequency domain |
Chapter 4 |
Session 7 |
|
Week 9 |
Image restoration: degradation models, |
Chapter 5 |
Session 8 |
|
Week 10 |
Image segmentation: edge detection, thresholding |
Chapter 10 |
Session 9 |
|
Week 11 |
Image compression: information theory, Huffman coding, run-length coding, lossy compression, compression standards |
Chapter 8 |
Coursework Assessment |
|
Week 12 |
Revision (exercises) |
--- |
Coursework Assessment |