COURSE DESCRIPTION

Cp Eng 345 – Digital Image Processing

(Offered Every Spring Semesters)

Required or Elective Course: Elective

Catalog Description:

[Lec. 3.0] Fundamentals of human perception, sampling and quantization, image transforms, enhancement, restoration, image and video compression and coding. Prerequisites: El Eng 267 Linear Systems II.

Prerequisites by topic:Linear algebra and matrix operations, linear time-invariant systems, Fourier transform analysis and filtering

Textbooks and other required material:R.C. Gonzalez and R.E. Woods, Digital Image Processing, 2nd ed., (Prentice Hall 2002).

Course learning outcomes/expected performance criteria:

1.Understand image formation and the role human visual system plays in perception of gray and color image data.

2.Get broad exposure to and understanding of various applications of image processing in industry, medicine, and defense.

3.Learn the signal processing algorithms and techniques in image enhancement and image restoration.

4.Acquire an appreciation for the image processing issues and techniques and be able to apply these techniques to real world problems.

5.Be able to conduct independent study and analysis of image processing problems and techniques.

Topics covered:

  1. Introduction Digital Image Processing (1 week)
  2. Image Fundamentals and Human Visual Perception (1 week)
  3. Image Enhancement in Spatial Domain (2 weeks)
  4. Image Transforms (1 week)
  5. Image Enhancement in Frequency Domain (1.5 week)
  6. Image Restoration (2 week)
  7. Image Morphology – Introductory (1 week)
  8. Color Image Processing – Introductory (1 week)
  9. Image Compression and Coding (2.5 week)
  10. Wavelet Transforms – Introductory (1 week)
  11. Student Presentations, Reviews, Examinations, and Final (3 weeks)

Class/laboratory schedule:

Three 50-minute lectures per week are typical. A host of image processing algorithms are demonstrated using available mathematical tools (particularly MATLAB)during the class and students are expected to use these tools to learn and apply these tools for computer assignment and exercises.

Contribution of course to meeting the professional component:

Digital image processing builds upon the tools and techniques learned by students in linear systems and probability courses. The course provides a mathematical basis for further study and research in image and video processing, computer vision, and image understanding. The students are required to use available mathematical tools (particularly MATLAB) and implement various image processing algorithms and evaluate their results. The homework is designed to reinforce fundamental theory and techniques. Class projects are aimed at providing practical insight into the implementation and constraints of real world image processing problems. The students are asked to write/present a survey technical paper on a subject of their choice related to image processing. Students present selected survey papers to the class as a short seminar in the last week of the class. The students are also required to do an individual term project on a topic of their interest related to image processing.

Relationship of course learning outcomes to ECE program outcomes:

ECE
Outcome / Course Outcomes / Comments
1 / 2 / 3 / 4 / 5
a / S / S / S / A balanced approach is taken in introducing mathematical tools and concepts and engineering intuition is stressed.
b / M / S
c / W / M / S
d / S / M / Students are introduced to multidisciplinary applications of image processing techniques particularly in industrial automation, medicine and defense.
e / W / M / M / S / S / Students are encouraged towards life-long learning and scholarship through self-guided research for survey paper and term project.
f / M / Requirement of the course to write survey paper and term project foster ethical and professional judgment in students.
g / S / Selected students are encouraged to present their project to class. All students are required to write a project report.
h
i / M / S / M / M / M
j / M / M / M
k / W / W / S / W / S / Use of available computer tools (particularly MATLAB) is promoted in learning the subject matter
l / M / M / M / M
S – strong connection; M – medium connection; W – weak connection

Prepared by: Sanjeev AgarwalDate:February 1, 2008