ECE 457/ ECE 557 Digital Image Procesing

Fall 2010

Instructor:: Dr. Elisa H. Barney Smith; Office: MEC 202C; Phone: 426-2214; E-mail: EBarneySmith@boisestate.edu

Class Meeting Times:: MWF 8:40-9:40am; MEC 309; http://coen.boisestate.edu/EBarneySmith/Image_proc

Office Hours:: Monday & Wednesday 9:40-10:30; I will also be available in my office at many other times. Stop by if you have questions.

Syllabus:

Syllabus ECE 457

Syllabus ECE 557

Text:: “Digital Image Processing,” Rafael C. Gonzalez and Richard E. Woods, Prentice Hall, second edition, 2002, ISBN 0-201-18075-8.; - or -; “Digital Image Processing,” Rafael C. Gonzalez and Richard E. Woods, Prentice Hall, third edition, 2008, ISBN 0-13-168728-8.; (but not first edition)

References:: “Digital Image Processing,” Rafael C. Gonzalez and Richard E. Woods, Prentice Hall, First edition, 1992.; “Fundamentals of Digital Image Processing,” Anil K. Jain, Prentice Hall, 1989.; MATLAB software package will be used in some homeworks. It is installed on the computers in ET239, MEC117, MEC103, and MEC 408. Student versions of Matlab are available from Mathworks (www.mathworks.com) if you would like to use a home PC instead, but some of the functionality of the Image Processing Toolbox will be needed.; Writing Guidelines

Grading:

Undergraduates:

Homeworks	55%
Projects	45%

Graduate Students:

Homeworks*	45%
Projects*	45%
Literature Survey	10%

* The homeworks and projects will be greater in number and larger in scope for graduate students than for undergraduate students.

Projects will require writing multiple pages of code to implement an algorithm.
Homeworks will focus on using existing Matlab functions to see the effect of an algorithm.

Course description:

The course will cover many of the following topics:

Pictures and their computer representation.
Image digitization, transformation, and prediction methods.
Image coding and image data compression.
Digital enhancement techniques, histogram equalization, differencing, smoothing and geometric corrections.
Restoration and filtering.
Edge detection and picture segmentation
Color models and transformations
Use of wavelets in image processing
Morphological Algorithms

Academic Honesty:: Please read the university policy on academic honesty in the undergraduate catalog (p17: 2010-2010). I strongly encourage students to work together and to discuss homeworks, BUT copying solutions is NOT permitted and can result in a grade of 0 for that assignment. In the written reports, all material included is expected to be your own creation. Material from the web or books or colleagues should be sparse and referenced with the appropriate citation.

Homeworks:

Homework #1- Isopreference Curves, due Monday 13 September 2010

Homework #2- Morpholocial Processing, due Monday 29 November 2010

Data for use in Homework #2: Problem 9.5 ‘U’; Problem 9.6; Problem 9.36 ‘Particles’

Homework #3- Multiresolution Analysis and Wavelets, due Wednesday 1 December 2010

Homework #4- Color Science, due Thursday 16 December 2010

colorscience_files.zip

Projects:

Project #1- connected components, due Friday 17 September 2010

Data for use in Project #1: ISRI image; Skull image

Project #2- Point Operations, due Wednesday 29 September 2010

Project #3- Filtering, due Wednesday 20 October 2010

Project #4- Image restoration filtering, due Monday 9 November 2010Data for use in Project #4 (choose either one, you may choose to filter just a part of the image. Do not downsample. Convert to gray scale before processing.)

Expo2010 image option 1

Expo2010 image option 2