COURSE UNIT TITLE

: ADVANCED TOPICS IN DIGITAL IMAGE PROCESSING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EEE 5114 ADVANCED TOPICS IN DIGITAL IMAGE PROCESSING ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR MUSTAFA ALPER SELVER

Offered to

ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)
ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)
ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)

Course Objective

The aim of the course is to teach principles and applications of advanced digital image processing techniques for image filtering, segmentation, compression, and registration.

Learning Outcomes of the Course Unit

1   Understanding the role of partial differential equations in image filtering
2   Understanding the role of partial differential equations in image segmentation
3   Understanding advanced techniques and appplications of image registration
4   Understanding digitial image compression standards and techniques
5   Having advanced knowledge and hands on experience on image processing techniques and applications

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Partial Differential Equations for Filtering (Edge Stopping, Directional, Isotropic and Anisotropic Diffusion Filters)
2 Model based segmentation (Active Contours)
3 Explicit (Lagrangian) Geometric Curve and Surface Evaluation: Snakes, Applications and Limitations
4 Implicit (Eulerian) Geometric Curve and Surface Evaluation: Level Sets, Applications and Limitations
5 Variational Level Set Methods (Fast Marching)
6 Geodesic Curves and Minimal Surfaces (Minimal path and centerline extraction techniques)
7 Statistical Shape Modeling of Image and Volume Data (Shape representation, Shape Model Construction, Appearance models, Shape correspondence, Applications)
8 Image Reconstruction from projections: Radon Transform, (Filtered) Backprojection, Iterative Reconstructions
9 Texture extraction (Co-occurence matrices, sum and different histograms, wavelets, curvelets, contourlets, brushlets)
10 Image Registration Techniques
11 Image Compression Techniques (Parameters of image compression, drawbacks of various methods, advantages of wavelet-based compression techniques, standard and new image formats, strength of new compression techniques
12 Hyper-spectral and Multi-spectral imaging
13 Multi-dimensional Processing (Multi Planar Reconstruction, Curved and Oblique Sectioning, Volume Rendering, Surface Rendering, Maximum Intensity Projection)
14 Image Mining and Content Based Image Retrieval

Recomended or Required Reading

1. Geometric Partial Differential Equations and Image Analysis, AUTHOR: Guillermo Sapirodate PUBLISHED: February 2006, Cambridge Press ISBN: 9780521685078
2. Image Processing: Principles and Applications AUTHORS: Tinku Acharya, Ajoy K. Ray
PUBLISHED: October 2005, Wiley ISBN: 978-0-471-71998-4
3. Image Processing: Dealing With Texture Maria AUTHORS: Petrou, Pedro Garcia Sevilla
PUBLISHED: January 2006, Wiley ISBN: 978-0-470-02628-1

Planned Learning Activities and Teaching Methods

Students understanding in theoretical course outcomes will be evaluated by 10 homeworks. Their ability to use the information and capture the concepts in applications will be evaluated in 5 different projects that consist of simulating theoretical information using computer based studies for which they have to prepare technical reports.
10 Homeworks will consist 50% (i.e. 50% each), and 5 projects will consists 50% (i.e. 50% each) of the final grade.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 PRS PRESENTATION
3 FCG FINAL COURSE GRADE ASG * 0.50 + PRS * 0.50


Further Notes About Assessment Methods

None

Assessment Criteria

Homeworks and Projects

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

alper.selver@deu.edu.tr
+902323017685

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 11 154
TOTAL WORKLOAD (hours) 196

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.154435212221421
LO.254445323122521
LO.354555453334542
LO.454435222222421
LO.534412411542211

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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