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Syllabus for

Academic year
ERR041 - Image processing
 
Owner: TELTA
3,0 Credits (ECTS 4,5)
Grading: TH - Five, Four, Three, Not passed
Level: A
Department: 0741 - Radio and space science


Teaching language: English
Minimum participants: 5
Maximum participants: 60

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 No Sp
0199 Examination 3,0 c Grading: TH   3,0 c    

In programs

TTFYA ENGINEERING PHYSICS, Year 4 (elective)
TDATA COMPUTER SCIENCE AND ENGINEERING - Cognition Technology and Multimedia, Year 4 (elective)
TDATA COMPUTER SCIENCE AND ENGINEERING, Year 3 (elective)
TELTA ELECTRICAL ENGINEERING, Year 4 (elective)
TAUTA AUTOMATION AND MECHATRONICS ENGENEERING, Year 4 (elective)

Examiner:




Eligibility:

For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.

Aim

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.

Content

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 lectures will be held in the new IT studio and will include a wide range of image display and real time interaction with images. Student exercises using MATLAB will be incorporated into the lectures. In these exercises, students can interactively process images illustrating topics such as the 2D Fourier transform and applications, image restoration, image enhancement and image compression.

Literature

R.C. Gonzalez and R. Woods: Digital Image Processing, Addison-Wesley Publishing Company, 1993.

Examination

A written exam occurs at the end of the course.


Page manager Published: Thu 03 Nov 2022.