|ERR041 - Image processing
3,0 Credits (ECTS 4,5)
|Grading: TH - Five, Four, Three, Not passed
Department: 75 - EARTH AND SPACE SCIENCES
Teaching language: English
Minimum participants: 5
Maximum participants: 60
20 Oct 2005 pm V,
11 Jan 2006 pm V
TTFYA ENGINEERING PHYSICS, Year 4 (elective)
TITEA SOFTWARE ENGINEERING, Year 3 (elective)
TDATA COMPUTER SCIENCE AND ENGINEERING, Year 3 (elective)
TDATA COMPUTER SCIENCE AND ENGINEERING - Other elective courses, Year 4 (elective)
TKBIA BIOENGINEERING, Year 4 (elective)
TAUTA AUTOMATION AND MECHATRONICS ENGENEERING, Year 4 (elective)
TELTA ELECTRICAL ENGINEERING, Year 4 (elective)
Professor John Conway
Eligibility:For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.
Digital image processing is a rapidly evolving field with applications to many areas of technology and science. Image processing techniques include image compression for transmission and storage on the Internet (JPEG, FAX, and moving image compression), restoration of image distortions (motion blurring etc), reconstruction of images from indirectly sampled data (synthetic aperture radar, radio interferometry, and medical tomography), and image enhancement for human interpretation of images. These image processing techniques have many applications in business, medicine, remote sensing, geophysics, astronomy and space research, radar and sonar imaging.
The course will enable engineers or scientists to use image processing systems as a tool. It also acts as an introductory course for those designing image processing systems and conducting research in new and emerging topics. The course concentrates on mature subjects with in image processing which have a wide range of applications; however short introductions to more advanced topics such as wavelet analysis are included. The course also seeks to balance teaching of these basics with real-life applications.
A companion course "Image Analysis" (Bildanalys) deals with the automatic recognition of features within images, automatic characterization and classification of images etc.
Students are expected to have had prior exposure to one-dimensional digital signal processing topics such as the sampling theorem, Fourier transform, linear systems and basic matrix algebra.
The course lectures cover the following areas:
Introduction - 2D Fourier Transform - The Human
Vision System - Image Enhancement - Image Transforms - Image restoration/reconstruction
- Image Compression - Image Wavelet Analysis.
The companion course 'Image Analysis' (ERR060)
in Lp 2 deals with the automatic recognition and characterisation of features
Detailed content of course:
Introduction: digital image representation, discrete 2D data quantisation etc
Imaging: direct and indirect imaging devices
The human vision system: relevance to image compression and enhancement
Image transforms: Fourier and other separable unitary transforms (hotelling, Hadamard etc)
Image enhancement: histogram modification, smoothing, sharpening
Image restoration: removal of image distortions, processing of indirect image data (interferometry etc)
Image compression: lossless and lossy coding of continuous and binary images
(JPEG, FAX, etc)
Wavelet analysis: applications to image compression etc.
The course consists of 14 lectures - 5 problem
classes and 2 student seminars. All classes are
given in a studio environment and include a wide
range of image display and real time interaction
with images. Student exercises using MATLAB or
JAVA applets are incorporated into the lectures.
All students must do a short project and present
the results at the end of laasperiod seminars.
The course textbook is 'Digital Image Processing'
by R.C. Gonzalez and R.Woods, 2nd Edition, 2001, Publ
There is a final written exam which consists
of 5 questions. In addition in order to pass
the course students must submit a written
report on their project work. This project counts
for 7% of the final grade.