CATALOG DESCRIPTION: Fundamentals of image processing. Image compression, enhancement, and restoration. Image reconstruction from projections and partial information.

REQUIRED TEXT: Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing (3rd Edition), Prentice Hall.

REFERENCE TEXTS: None

COURSE DIRECTOR: Aggelos Katsaggelos

COURSE GOALS: To study the application of digital signal processing to problems in image processing. Topics covered will range from the fundamentals of 2-D signals and systems, to image enhancement, restoration and compression. A brief coverage of video processing (compression) will also be given.

PREREQUISITES BY COURSES: EECS 359 or equivalent

PREREQUISITES BY TOPIC: Introduction to digital signal processing.

DETAILED COURSE TOPICS:

  • 2-D Signals and Systems
Description and Properties of 2-D signals and systems
2-D Fourier Transform
2-D DFT and FFT
Rectangular sampling
Arbitrary sampling
  • Enhancement and Restoration
Contrast and dynamic range modification
Edge detection
Degradation models
Noise filtering
Deterministic restoration filters
  • Stochastic restoration filters

Image Compression
Quantization
Lossless coding
Predictive coding
Transform coding
Standards (JPEG)
Fractal coding

  • Video Compression
Motion estimation
Transform coding
Standards (MPEG, H.261, H.263)

COMPUTER USAGE: None.

LABORATORY PROJECTS: None.

GRADES:

Homeworks – 30%
Midterm Exam – 30%
Final Exam – 40%

COURSE OBJECTIVES: When a student completes this course, s/he should be able to:

• Understand the fundamental concepts of 2D signals and systems;

• Perform image enhancement and restoration;

• Perform image compression and decompression;

• Perform video compression and decompression.