THE KING'S UNIVERSITY
Processing and Embedded Images
||Dr. Michael Janzen
AND WEEKLY TIME DISTRIBUTION:
||credits 3(hrs lect 3 - hrs sem 0 - hrs lab 3)
||This course introduces the topic of image processing,
including a mathematical approach to understanding the technical aspect
of how an image can be created, viewed and modified. Utilizing an image
processing toolbox various images will be analyzed using standard
algorithms, noisy or degraded images restored and enhanced for improved
intelligibility, shapes and textures will be analyzed, and features of
images will be embedded or extracted.
Prerequisites: CMPT 305
- Gonzalez, Rafael C; Woods Richard E.; Eddins (2007), Digital Image Processing 3rd ed., Pearson.
following may be useful. If desired these books can be put on
reserve in the King’s library.
- Sonka, Milan; Hlavac, Vaclav; Boyle, Roger (2008), Image processing, analysis and
machine vision, Thompson Learning.
- Gonzalez, Rafael C; Woods Richard E.; Eddins,
Steven L. (2009), Digital
image processing using MATLAB, Gatesmark Publishing.
- Russ, John C. (2011) The image processing handbook
6 th ed., CRC Press.
- Also see the paper reading list for discussion group
DISTRIBUTION IN PERCENT:
||This course is intended to introduce students to image
processing. By the end of this course a student should be
- Understand what makes an image and how an image is
- Process an image using several techniques including
grey scaling an image, convolutions, operations on black and white
images, and some image classification techniques
- Have introductory GPGPU skills
- Discuss issues concerning image processing in society
- What is an Image?
- Greyscale and Black & White operations
- GPGPU processing
- Image resizing
- Image formats and compression
- Background subtraction techniques
- Textures in Images
- Image Classification
- Additional topics as time allows
Required texts, assignments, and grade distributions
from one offering of this course to the next. Please consult
the course instructor for up to date details.