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

Graduate capabilities & intended learning outcomes

Graduate Capabilities

Intended Learning Outcomes

01. Demonstrate deep understanding of the fundamental principles in digital signal processing
02. Demonstrate specialised and in-depth knowledge in image processing by applying knowledge to practical applications.
03. Produced specialised MATLAB functions for advanced image processing building on existing algorithms and further developing new algorithms
04. Critically analyse, evaluate and synthesise fundamental concepts and recent advances in image processing for application to complex problems
Subject not currently offered - Subject options not available.