ADVANCED SIGNAL AND IMAGE PROCESSING
EMS5ACI
Not currently offered
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: Engineering and Mathematical Sciences (Pre 2022)
Credit points: 15
Subject Co-ordinator: Guang Deng
Available to Study Abroad/Exchange Students: No
Subject year level: Year Level 5 - Masters
Available as Elective: No
Learning Activities: N/A
Capstone subject: 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
Quota Management Strategy: N/A
Quota-conditions or rules: N/A
Special conditions: N/A
Minimum credit point requirement: N/A
Assumed knowledge: N/A
Learning resources
Digital signal processing A computer-based approach
Resource Type: Book
Resource Requirement: Recommended
Author: S. Mitra
Year: 2006
Edition/Volume: N/A
Publisher: McGraw Hill
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Introduction to digital image processing
Resource Type: Book
Resource Requirement: Recommended
Author: W.K. Pratt
Year: 2013
Edition/Volume: N/A
Publisher: CRC press
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Digital Image Processing using MATLAB
Resource Type: Book
Resource Requirement: Recommended
Author: R. C. Gonzalez, R. E. Woods, S. L. Eddins
Year: 2009
Edition/Volume: N/A
Publisher: Pearson-Prentice-Hall
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Computer Vision: Algorithms and Applications
Resource Type: Book
Resource Requirement: Recommended
Author: R. Szeliski
Year: 2011
Edition/Volume: N/A
Publisher: Springer
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Career Ready
Career-focused: No
Work-based learning: No
Self sourced or Uni sourced: N/A
Entire subject or partial subject: N/A
Total hours/days required: N/A
Location of WBL activity (region): N/A
WBL addtional requirements: N/A