EE E4830: Digital Image Processing, Spring 2005


COURSE BENEFITS:

PROFESSOR  Shih-Fu Chang:


APPLICABLE DEGREE PROGRAMS:


Lecturer/Manager: Professor Shih-Fu Chang
Office Hours: Mondays 4-5:30pm, CEPSR 709
Office Phone: (212) 854-6894
Email Address: [email protected]
Day & Time Class 
Meets on Campus:
Mondays & Wednesdays, 2:40-3:55 PM
Location: Mudd 1024
Class Homepage: http://www.ee.columbia.edu/~sfchang/course/dip/
Credits for Course: 3
Class Type: Lecture
Prerequisites:

Signals and Systems or equivalent required

Familiarity with Probability and Linear Algebra

Intended for Seniors, Juniors, or beginning graduate students.

Description:

Introduction to theories, algorithms, and practical solutions of digital image/video perception, acquisition, color representation, quantization, transform, enhancement, filtering, multi-spectral processing, restoration, analysis, feature extraction, segmentation, morphological transform, and compression.

Students will gain understanding of algorithm design, mathematical tools, and practical implementations of various digital image applications.  Considerations of practical system requirements (e.g., medical, satellite, consumer) will be discussed. Related standards such as JPEG and MPEG will be reviewed.

Required Text(s):


Gonzalez and Woods, Digital Image Processing, 2nd edition, Prentice Hall, 2001.


Reference Text(s):
  • Anil K. Jain, Fundamentals of Digital Image Processing, Prentice Hall, 1989.
  • William K. Pratt, Digital Image Processing, 3rd Edition, John Wiley, 2001.
  • Kenneth R. Castleman, Digital Image Processing, Prentice Hall, 1996.
  • Arun N. Netravali, Barry G. Haskell, Digital Pictures, Plenum, 2e, 1995.
Homework(s): 6 homework's including analytical questions and mini programming in language of your choice. Use of Matlab is suggested.
Project(s): None
Paper(s): None
Midterm Exam(s): One, open book
Final Exam: One, open book
Grading: Homework (40%), midterm (30%), final (30%)
Hardware 
requirements:
PC or notebook computer with access to Columbia’s systems
Software 
requirements:

Matlab is the recommended tool for the class. Software examples will be shown in class. To help students get familiar with Matlab, we will prepare a simple tutorial for Matlab at the beginning of the semester.

Matlab and Image Processing toolbox will be installed in the computer lab located in Mudd Rm. 251. Most students also find it convenient to purchase a student edition of Matlab for their own computers. However, students may choose any language of his/her choice for homework submission.

All sample program and test data will be distributed on the course web site. There will be an online discussion place on courseworks.columbia.edu to exchange information and discuss common issues. Students need to have Columbia account in order to access the site.


 
Schedule for EE E4830: Digital Image Processing, Spring 2005
Class

Date

Class

No.

Topics/Chapters Covered
Homework

Assigned

Due
  1

Introduction, Image Representation

   
  2

Color Space, Image Sampling

   
  3 Quantization, Image Quality Measurement    
  4 Image Quality Enhancement, Discrete Fourier Transform    
  5 Frewuency-Domain Filtering, Image Transform    
  6 Discrete Cosine Transform, KL Transform    
  7 Image Restoration    
  8 Image Feature Extraction and Representation: Edge and Line    
  9 Region Segmentation and Representation    
  10 Morphological Image Processing    
  11 Image and Video Compression    
  12 Object Recognition