SYDE 574Image Processing
- Faculty
- Engineering
- Offered
- Winter
- Credit
- 0.5
- Last listed
- 1993–94
No longer offered. It’s in Waterloo’s scanned calendars from 1989–90 to 1993–94; the 1995–96 to 2023–24 calendars are on ucalendar.
Beginning with a discussion of quantitative models of imaging systems, this course moves on to apply methods of linear systems theory and signal processing to image processing. Simple spatial domain techniques as well as spatial frequency domain methods and digital filter design for image enhancement and restoration are discussed. Special topics in application areas of machine vision (segmentation and feature extraction), remote sensing, medical imaging and vision models are presented throughout the term. Ukrainian For courses in Ukrainian see Germanic and Slavic Languages and Literatures. Course Descriptions Ukrainian
As printed in the 1989–90 to 1993–94 calendars, read by OCR; the scanned page is the original.
Requirements, as last listed
Prereq: SY DE 252 or equivalent
Check it elsewhere
In the scanned calendars
How it read in each calendar from 1989–90 to 1993–94, newest first. The text is OCR of the scanned pages; years whose wording matches are shown once, from the clearest scan. Each year links to its page on uwloo and to that page of the scanned PDF.
1989–90 to 1993–94 5 calendars
Beginning with a discussion of quantitative models of imaging systems, this course moves on to apply methods of linear systems theory and signal processing to image processing. Simple spatial domain techniques as well as spatial frequency domain methods and digital filter design for image enhancement and restoration are discussed. Special topics in application areas of machine vision (segmentation and feature extraction), remote sensing, medical imaging and vision models are presented throughout the term.
Ukrainian
For courses in Ukrainian see Germanic and Slavic Languages and Literatures.
Course Descriptions Ukrainian
Prereq: SY DE 252 or equivalent
Offered Winter · 3 class, 1 tutorial hours a week · 0.5 credit