CS-635 Introduction to Image Processing (revision of existing course)
Revised by Brent Seales
Credits: 3
Course Description:
This course covers the fundamentals of digital image processing. The topics
of image formation and digitization provide the context for a complete
treatment of the core topics of image representation and transformation,
enhancement, reconstruction, segmentation and early processing (filtering,
edge detection, feature localization) for the purpose of solving a variety
of current image-based problems.
Prerequisites: CS335, MA114
Needed Skills:
Students should be capable of structured functional/object-oriented
programming and the basics of graphical user interface design. Math skills
should be at the level of familiarity with calculus, linear algebra, and
basic statistical methods.
Learning Outcomes:
Students will learn to handle digital images and to write programs which
manipulate them in terms of many of the basic image processing functions.
Students will understand the relationship of the digital image to the scene
it represents, and the effect of processing that image to extract or enhance
its information content. Students will use the theoretical and practical
knowledge of digital imagery to design and implement a solution to a
substantial problem requiring the manipulation of digital imagery.
Course Content:
* Introduction
Image formation, Image representations;
Software environment, Imaging systems
* Image transforms
Properties of the Fourier transform
The Sampling Theorem; the FFT
Other transforms; the Fourier slice theorem
* Color Images
* Image enhancement
Frequency domain methods
Spatial domain methods
* Image restoration
Restoration, warping and morphing
* Compression techniques
* Image segmentation
Edge detection
Edge detection, linking
Thresholding, Hough transform
Region-growing
Textbooks:
1. Digital Image Processing
Gonzales and Woods, Addison Wesley
2. Digital Image Processing
Castleman, Prentice Hall
3. Two Dimensional Imaging
Bracewell, Prentice Hall