Advanced Image Processing (P00803)

? Credit Points : 10 ? SCQF Level : 11 ? Acronym : GEO-P-RSAIP

This course extends and builds on the material in the semester 1 courses “Theory of Image Processing” and “Applied image processing”. Techniques applicable to optical, thermal and microwave methods are covered but greatest emphasis is given to optical techniques. Emphasis is placed on gaining a practical understanding of the principles behind each technique and a consideration of their appropriateness in different applications. Practical experience in the utilization of remotely sensed data and in image processing techniques will be gained through a series of unsupervised practical projects designed to complement lecture material. Students are required to implement some of the techniques themselves in a programming language: this leads to deeper understanding of the basic principles involved. Emphasis will also be placed on the importance of image interpretation.

Entry Requirements

? Pre-requisites : Available only to postgraduate students 'Applied Image Processing' and 'Theory of Image Processing' for non-Remote Sensing and Image Processing MSc students

Subject Areas

Home subject area

Postgraduate Courses (School of GeoSciences), (School of GeoSciences, Schedule N)

Delivery Information

? Normal year taken : Postgraduate

? Delivery Period : Block 3 only

? Contact Teaching Time : 4 hour(s) per week for 5 weeks

First Class Information

Date	Start	End	Room	Area	Additional Information
08/01/2008	14:00	17:00	Room 301, Crew Building	KB

All of the following classes

Type	Day	Start	End	Area
Lecture	Tuesday	14:00	18:00	KB

Summary of Intended Learning Outcomes

The course builds on the theory of image processing introduced in semester 1 by
Discussing the treatment of geometrical correction of common distortions
Covering ways of classifying different areas and textures in images
Introducing the student to recent developments in the practical application of image processing techniques

Assessment Information

The Course is assessed on 4 items
A classification exercise (20%)
A principal component analysis exercise (10%)
An exercise in image registration (30%)
A student seminar (40%)