ADVANCED SIGNAL AND IMAGE PROCESSING

EMS5ACI

2019

Credit points: 15

Subject outline

This subject will cover the fundamentals of discrete signal and systems, basic image processing techniques in spatial domain and transform domain, and advanced topics such as wavelet-based image processing and compression, and edge-aware filtering. After completing this subject students will have advanced and integrated understanding of these topics and skills in some state-of-art techniques. Students will be able to research or apply established theories to practical problems such as image enhancement and feature extraction.

School: School Engineering&Mathematical Sciences

Credit points: 15

Subject Co-ordinator: Dennis Deng

Available to Study Abroad Students: No

Subject year level: Year Level 5 - Masters

Exchange Students: No

Subject particulars

Subject rules

Prerequisites: Students must be admitted in one of the following courses: SMENE, SMENEB, SMELE, SMTNE or LMEM

Co-requisites: N/A

Incompatible subjects: N/A

Equivalent subjects: N/A

Special conditions: N/A

Learning resources

Readings

Resource Type	Title	Resource Requirement	Author and Year	Publisher
Readings	Digital Image Processing using MATLAB	Recommended	R. C. Gonzalez, R. E. Woods, S. L. Eddins, 2009	Pearson-Prentice-Hall
Readings	Computer Vision: Algorithms and Applications	Recommended	R. Szeliski, 2011	Springer
Readings	Introduction to digital image processing	Recommended	W.K. Pratt, 2013	CRC press
Readings	Digital signal processing A computer-based approach	Recommended	S. Mitra, 2006	McGraw Hill

Graduate capabilities & intended learning outcomes

01. Demonstrate deep understanding of the fundamental principles in digital signal processing

Activities:: Lecture, assignments

02. Demonstrate specialised and in-depth knowledge in image processing by applying knowledge to practical applications.

Activities:: Lecture, laboratory class

03. Produced specialised MATLAB functions for advanced image processing building on existing algorithms and further developing new algorithms

Activities:: Laboratory class

04. Critically analyse, evaluate and synthesise fundamental concepts and recent advances in image processing for application to complex problems

Activities:: Lecture and assignments

Bendigo, 2019, Semester 1, Day

Overview

Online enrolment: No

Maximum enrolment size: N/A

Enrolment information:

Subject Instance Co-ordinator: Dennis Deng

Class requirements

LectureWeek: 10 - 22
One 2.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Laboratory ClassWeek: 11 - 21
One 2.0 hours laboratory class per week on weekdays during the day from week 11 to week 21 and delivered via face-to-face.

TutorialWeek: 11 - 22
One 1.0 hours tutorial per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.

Assessments

Assessment element	Comments	%	ILO*
Four written assignments (250 words each - total 1000 words)		20	01, 04
Four 15-minute laboratory class tests (equivalent to 250 words each - total 1000 words)	Conducted at the conclusion of each laboratory task	20	02, 03
1-hour mid-semester test (equivalent to 1000 words)		20	01, 02
2-hour exam (equivalent to 2000 words)		40	01, 02

Melbourne, 2019, Semester 1, Day