Master Course Description

No: EE440

Title: INTRODUCTION TO DIGITAL IMAGING SYSTEMS

Credits: 4

UW Course Catalog Description

Coordinator: Ming-Ting Sun, Professor of Electrical Engineering

 

Goals: To provide students with an introduction of the basic theory of image processing and key aspects in image computing and digital video systems, including various standards.

 

Learning Objectives: At the end of this course, students will be able to:

  1. Explain various image representations, human visual perception, color space, and standards.
  2. Write computer programs to perform image filtering, enhancement, restoration, and transform.
  3. Perform various image and video compression using various techniques.
  4. Implement algorithms to solve real-world image and video processing problems.

Textbook: Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, 3rd Edition, Prentice Hall, 2002.

 

Prerequisites by Topic:

  1. Discrete time signal analysis
  2. Discrete time Linear Time-Invariant Systems
  3. Impulse response and Convolution
  4. Correlation
  5. Z-transform
  6. Discrete Fourier Transform
  7. Digital filters

Topics:

  1. Image Representations (1 week)
  2. Visual Perception and Color Spaces (0.5 week)
  3. Image Enhancement (1.5 week)
  4. Image Filtering (1 week)
  5. Image Enhancement in the Frequency Domain (1 week)
  6. Image Restoration (0.5 week)
  7. Edge Detection, Segmentation, and Mathematical Morphology (1 week)
  8. Image Transform (1 week)
  9. Image Compression (1 weeks)
  10. Video Compression (1 week)

Course Structure: The class meets for two lectures a week and also has weekly lab assignments. The students use the computer resources to perform lab assignments with the help from the TA and the instructor.

 

Computer Resources: This course uses MATLAB and image processing and video compression software to perform various kinds of image/video processing/manipulation.

 

Outcome Coverage:
(a) An ability to apply knowledge of mathematics, science, and engineering. The majority of the lectures and lab assignments deal with the application of math, science, and engineering knowledge to enhance, restore, or compress the image/video signals. Mathematical formulations are commonplace throughout the course. (M)

(b) An ability to design and conduct experiments, as well as to analyze and interpret data. In the lab assignments, the students need to design and conduct experiments to solve many real-world image-processing problems. (M)

(e) An ability to identify, formulate, and solve engineering problems.  Students are required to identify the sources of corruption that degrade the image quality, and to formulate and solve a number of problems on image enhancement and restoration, in the lab assignments and exams. (M)

(j) Knowledge of contemporary issues, Students search the Internet, media, and technical journals to understand topics related to image/video technologies, describe the issue and give comments. (H)

(k) An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.  The students use various capturing devices to capture digital image and video files. They use commercially available image processing software to perform various kinds of image processing, and use Matlab to implement image-processing algorithms. They also use video encoders and decoders to compress and decompress video sequences. (M)

 

Prepared By: Ming-Ting Sun

Last revised: 10/08/2012