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Image Processing (ELEN90076)
Graduate courseworkPoints: 12.5Not available in 2023
To learn more, visit 2023 Course and subject delivery.
Overview
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Images and visual information are integral parts of our daily lives. Image processing plays an important role in various practical applications among them: television, medical imaging modalities such as X-ray or ultrasound, photography, security, astronomy and remote sensing. This subject will introduce the fundamentals of image and video processing and manipulation. While image applications will be used for illustrations, the subject emphasizes on general principles of image processing rather than specific applications.
This subject will cover the following topics:
introduction to image processing, image acquisition and display, image perception, colour representations, image sampling, quantization and image quality measurement, point operations, linear image filtering and correlation, image transforms and sub-band decompositions, contrast and colour enhancement, eigenimages, image segmentation, image restoration, image compression, patch image analysis, video coding and analysis.
Intended learning outcomes
Intended Learning Outcomes (ILOs)
Upon completing this subject, the student is expected to:
- Describe the principles of image formation, acquisition and perception
- Describe the basic theory and algorithms that are widely used in image processing
- Demonstrate a general knowledge on current technologies and issues that are specific to image processing systems
- Describe the basic theory and algorithms used in video coding and processing
- Develop hands-on experience in using computers to process images
- Define image operations and use the MATLAB Image Processing Toolbox to execute these image operations
- Demonstrate critical thinking about shortcomings of the state of the art in image and video processing
Generic skills
Upon completion of this subject, students will have developed the following skills:
- Ability to apply knowledge of science and engineering principles to image and video related problems;
- Ability to undertake image and video problem identification and formulate solutions;
- Capacity for independent critical thought, rational inquiry and self-directed learning;
- Develop work collaboration and communication skills.
Last updated: 30 January 2024
Eligibility and requirements
Prerequisites
Students must meet one of the following prerequisite options:
Option 1
Admission into or selection of one of the following:
- MC-ELECENG Master of Electrical Engineering
- Electrical specialisation (formal) in the MC-ENG Master of Engineering
- Electrical with Business specialisation (formal) in the MC-ENG Master of Engineering
AND
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
ELEN30012 | Signals and Systems |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
ELEN90054 | Probability and Random Models | Semester 1 (On Campus - Parkville) |
12.5 |
Option 2
Admission into a research higher degree (MPhil or PhD) in Engineering (subject to approval from the Subject Coordinator).
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 30 January 2024
Assessment
Semester 2
Description | Timing | Percentage |
---|---|---|
Applied research project will be carried out from week 3 to 10. The students will be divided in groups of two and each research project will require a written assignment per group, a Matlab demonstration and a presentation to the class. (Approximately 35-40 hours of work per student). ILOs 1-7 are addressed in these projects.
| Week 11 | 30% |
A three-hour written examination. ILOs 1-7 are addressed in this exam.
| During the examination period | 70% |
Last updated: 30 January 2024
Dates & times
Not available in 2023
Time commitment details
200 hours
Last updated: 30 January 2024
Further information
- Texts
Prescribed texts
None
- Related Handbook entries
This subject contributes to the following:
Type Name Course Ph.D.- Engineering Course Doctor of Philosophy - Engineering Course Master of Philosophy - Engineering - Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 30 January 2024