ENEE 631: Digital Image Processing

Course Goals:

To introduce the student to theoretical foundations and modern applicatons in Digital Image Processing. Main topics to be covered are image digitization, image representation, image compression, restoration and reconstruction. The student will be exposed to concepts such as Markov Random Fields, simulated annealing, multi-resolution processing as well as image compression standards.

Course Prerequisite(s):

ENEE 620, 624 or Permission of the Instructor

Topics Prerequisite(s):

Random Processes, sampling, quantization, multi-rate signal processing, linear algebra.

Textbook(s)

A.K. Jain, Fundamentals of Digital Image Processing, Prentice Hall, 1988

Reference(s):

R. Chellappa, Collected papers in Digital Image Processing, IEEE Computer Society Press, 1992.

M. Tekalp, Digital Video Processing, Prentice-Hall, 1996

Core Topics:

• Image sampling and quantization
• Image Transforms and models
• Image enhancement and restoration
• Still and video compression and compression standards
• Image Reconstruction

Optional Topics:

• Non-linear PDE's and anisotropic diffusion processes for image processing>
• Digital Image and Video Libraries >
• Biometric Image Processing>

Course Structure:

Grading Method: