Note: This is an archived Handbook entry from 2015.
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2015:Semester 2, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: 36 hours of lectures and tutorials |
Total Time Commitment:
Enrolment in a research higher degree (Masters or PhD) in Engineering
|Recommended Background Knowledge:|| |
Students will be expected to be familiar with statistics and probability.
|Non Allowed Subjects:|| |
|Core Participation Requirements:||
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.
It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability
CoordinatorDr Karim Seghouane
Melbourne School of Engineering
Ground Floor, Old Engineering (Building 173)
Phone: 13MELB (13 6352)
+61 3 9035 5511
Images and visual information are integral parts of our daily lives. Digital 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 processing and manipulation. While image applications will be used for illustrations, the subject emphasizes general principles of image processing rather than specific applications. It is expected to cover the following topics: introduction to digital 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 and image compression.
Upon completing this subject, the student is expected to:
1- describe the principles of image formation, acquisition and perception
2- describe the theory and algorithms that are widely used in digital image processing
3- demonstrate a general knowledge on current technologies and issues that are specific to image processing systems
4- develop hands-on experience in using computers to process images
5- define image operations and use the MATLAB Image Processing Toolbox to execute these image operations
6- demonstrate critical thinking about shortcomings of the state of the art in image processing
|Breadth Options:|| |
This subject is not available as a breadth subject.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
Ability to apply knowledge of science and engineering principles to image and video related problems
Master of Philosophy - Engineering |
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