Text: Anil K. Jain, Fundamentals of Digital Image Processing, Prentice-Hall, 1989.
Prerequisite: EEE 407 Digital Signal Processing, or equivalent.
This course is concerned with understanding the fundamentals of digital image perception, representation, processing, and compression.
Outline
I. Two-Dimensional Digital Signal Processing Basics
A. Representation of 2-D Signals, Special 2-D SignalsII. Vision and Perception
B. Two-D Linear Shift-Invariant Systems
C. Two-D Sampling
A. Modeling the Human Visual SystemIII. Quantization and Quantizer Design
B. Luminance, Brightness, Contrast Masking
C. Color Models
D. Image Fidelity Criteria
A. Entropy CodingIV. Image Transforms
B. Rate-Distortion Theory
C. Optimal Quantizer Designs: scalar and vector quantizers
D. VQ with Structural Constraints or Memory
A. Matrix Representation of Images and TransformsV. Image and Video Compression
B. Vector Representation versus Matrix Representation
C. Separable and Unitary Transforms
D. Special Transforms: 2-D DFT, DCT, DST, Discrete Hadamard, Optimal Karhunen-Loeve
A. Predictive, Transform, and Subband Coding DVI. Image Enhancement and Restoration
B. Entropy Coding and Run-Length Coding
C. Motion Estimation and Compensation
D. JPEG and MPEG Compression Standards
A. Image Enhancement TechniquesCourse Coordinator: Lina Karam
B. Image Restoration Techniques