PCB593 Digital Image Processing
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| Unit code: | PCB593 |
|---|---|
| Credit points: | 12 |
| Timetable | Details in HiQ, if available |
| Availabilities |
|
| CSP student contribution | $1,118 |
| Domestic tuition unit fee | $4,104 |
| International unit fee | $4,488 |
Unit Outline: Semester 1 2024, Gardens Point, Internal
| Unit code: | PCB593 |
|---|---|
| Credit points: | 12 |
| Coordinator: | Joel Alroe | j.alroe@qut.edu.au |
Overview
This unit provides students in the Astrophysics minor with an opportunity to learn how to use image processing techniques. An understanding of digital image processing enables information to be extracted from images that is not otherwise accessible. This unit delivers an understanding of digital images and the skills required to manipulate images in order to enhance features and extract quantitative information. Specific areas of study include the structure of digital images; image display techniques; grey scale palettes and look-up tables; colour perception, colour models, image formats, Fourier transforms; convolutions; image processing hardware; image analysis, enhancement and restoration; spatial filtering; Fourier space filtering; methods of image reconstruction; 3D volume and surface rendering; applications of image processing in medicine, astronomy and remote sensing.
Learning Outcomes
On successful completion of this unit you will be able to:
- Develop and demonstrate a basic knowledge and understanding of digital images
- Understand and apply various methods of generating, storing, transmitting and manipulating digital images.
Content
1. Introduction to digital image processing - applications in medicine, agriculture, astrophysics, etc.
2. Digital image basics - pixels, bits and bytes, color vision and colour images, look up tables, image formats.
3. Digital imaging hardware and software - CCDs, solid state x-ray detectors, scanners, digital cameras, image displays, networks, image file formats.
4. Image manipulation using histogram equalization and contrast stretching.
5. Spatial domain image filtering using low and high-pass convolution filters, edge detection.
6. Frequency domain image filtering and reconstruction (using the FFT and inverse FFT).
7. Image compression using lossless/lossy compression algorithms.
8. Measurings distances, angles, area and volumes on images.
9. Image arithmetic operations for enhancement, compression and selective masking.
Learning Approaches
Students apply theory explored in the lectures to laboratory practical exercises and are encouraged to think about the utility of digital imaging processing in a wide variety of fields.
Lectures: 2 hours / week
Practicals: 2 hours / week
Feedback on Learning and Assessment
Laboratory exercises are handed back with comments about a week after submission.
Assessment
Overview
Assessment includes a series of laboratory-based activities demonstrating image processing techniques, followed by a final written examination to assess conceptual theoretical knowledge. All work is individually assessed.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Portfolio of practical work
Weekly laboratories will provide experience in applying digital image processing techniques for a range of applications. Worksheets are submitted within a week of each laboratory and written feedback is provided after each task.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Written examination
Short answer written examination including both conceptual questions and worked problems.
Academic Integrity
Students are expected to engage in learning and assessment at QUT with honesty, transparency and fairness. Maintaining academic integrity means upholding these principles and demonstrating valuable professional capabilities based on ethical foundations.
Failure to maintain academic integrity can take many forms. It includes cheating in examinations, plagiarism, self-plagiarism, collusion, and submitting an assessment item completed by another person (e.g. contract cheating). It can also include providing your assessment to another entity, such as to a person or website.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Further details of QUT’s approach to academic integrity are outlined in the Academic integrity policy and the Student Code of Conduct. Breaching QUT’s Academic integrity policy is regarded as student misconduct and can lead to the imposition of penalties ranging from a grade reduction to exclusion from QUT.
Resources
There is no required text for this unit.
Resource Materials
Recommended text(s)
Burger, W., & Burge, M. (2016). Digital image processing : an algorithmic introduction using Java (Second edition.). Springer. https://doi.org/10.1007/978-1-4471-6684-9
Gonzalez, R. C., & Woods, R. E. (Richard E. (2018). Digital image processing (Fourth edition, Global edition.). Pearson.
Hessman, F. V., & Modrow, E. (2008). An Introduction to Astronomical Image Processing with ImageJ. Georg-August-Universität Göttingen. https://www.astro.physik.uni-goettingen.de/~hessman/ImageJ/Book/
Bourne, R. (2010). Fundamentals of Digital Imaging in Medicine (1st ed. 2010.). Springer London. https://doi.org/10.1007/978-1-84882-087-6
Risk Assessment Statement
There are no out of the ordinary risks associated with this unit.