EEC206 - Digital Image Processing

4 units - Winter Quarter

Lecture: 3 hours

Laboratory: 3 hours (completion of 3 lab-oriented projects)

Prerequisite: Course 150B

Grading: Letter; based on midterm exam, project, and final exam

Course Description

Two-dimensional systems theory, image perception, sampling and quantization, transform theory and applications, enhancement, filtering and restoration, image analysis, and image processing systems.

Expanded Course Description

  1. Two-Dimensional Systems
    1. Linear systems and shift invariance
    2. Convolution summation
    3. Fourier transforms
  2. Image Perception
    1. Perception of brightness
    2. Perception of spatial information
    3. Color perception
    4. Temporal properties of vision
  3. Image Sampling and Quantization
    1. Image scanning and television
    2. Two-dimensional sampling theory
    3. Practical limitations in sampling and reconstruction
    4. Image quantization
    5. Visual quantization
  4. Image Transforms
    1. Two-dimensional orthogonal and unitary transforms
    2. Discrete Fourier transform (DFT)
    3. Discrete cosine transform (DFT)
    4. Other transforms
  5. Image Enhancement
    1. Point operations
    2. Histogram modeling
    3. Spatial operations
    4. Transform operations
    5. Color image enhancement
  6. Image Filtering and Restoration
    1. Image observation models
    2. Inverse and Wiener filtering
    3. Generalized inverse methods
    4. Coordinate transformation and geometric correction
  7. Image Analysis
    1. Spatial feature extraction
    2. Edge detection, boundary extraction and representation
    3. Structure
    4. Texture
    5. Scene matching and detection
    6. Segmentation
  8. Image Processing Systems
    1. Image processing hardware
    2. Image processing software

Laboratory Experiments:

In the laboratory, students will learn to use an image processing hardware and software system to perform a set of experiments, chosen from:

Image sampling and quantization
Fast Fourier transform
Nonlinear point operations
Histogram equalization
Spatial filtering
Edge detection
Shape analysis
Texture analysis

Textbook: A. K. Jain, Fundamentals of Digital Image Processing, Prentice-Hall, 1989.

Engineering Design Statement:

The laboratory projects examine design at both the level of individual functions (e.g., the design of 2-D filters) and the system level. In addition to design methodology, criteria for the selection of algorithms appropriate to a given application are stressed. Designs are implemented in software, via a visual programming language which emphasizes a modular approach to problem solving. Projects do not have unique solutions, and students are encouraged to explore alternative approaches. Lectures emphasize the design aspects of image processing, particularly with respect to evaluation of methods for specific applications (e.g., image quality metrics for image enhancement and compression techniques).

ABET Category Content:

Engineering Science: 2 credits
Engineering Design: 2 credits

Instructor: Ford, Levy, Reed

THIS COURSE DOES NOT DUPLICATE ANY EXISTING COURSE.

Last revised: 2/93