ECE: Electrical & Computer Engineering
Accredited by ABET
Undergraduate Programs

ECE 4580 Digital Image Processing

Spring 2016 textbook list

The Spring 2016 ECE textbook list is available online for students.

Current Prerequisites & Course Offering

For current prerequisites for a particular course, and to view course offerings for a particular semester, see the Virginia Tech Course Timetables.

Return to course list

ECE 4580 Digital Image Processing (3C)

This course provides an introduction to basic concepts, methodologies and algorithms of digital image processing focusing on the following two major problems concerned with digital images: (1) image enhancement and restoration for easier interpretation of images, and (2) image analysis and object recognition. Some advanced image processing techniques (e.g., wavelet and multiresolution processing) will also be studied in this course. The primary goal of this course is to lay a solid foundation for students to study advanced image analysis topics such as computer vision systems, biomedical image analysis, and multimedia processing & retrieval.

What is the reason for this course?

For the last few decades, image processing has emerged as an important technology to extract useful information for scene understanding. To develop next-generation image processing systems, it is essential to equip our students with a deep understanding of the challenges in image understanding, and with advanced skills to develop image processing techniques by integrating approaches from information processing and pattern recognition. This course will provide both basic and in-depth coverage of image processing techniques for students to develop information processing systems. In particular, this coruse will help students understand many image processing approaches for scene analysis and understanding; to acquire working knowledge of many image processing systems; to have a hands-on experience on analyzing a variety of images for image understanding.

Typically offered: Spring. Program Area: Computers.

Department Syllabus Information:

Major Measurable Learning Objectives:
  • describe and explain basic principles of digital image processing;
  • design and implement algorithms that perform basic image processing (e.g., noise removal and image enhancement);
  • design and implement algorithms for advanced image analysis (e.g., image compression, image segmentation & image representation);
  • assess the performance of image processing algorithms and systems.

Course Topics
Topic Percentage
1. Image processing fundamentals and human vision system 10%
2. Digital image enhancement techniques: point processing; spatial filtering 10%
3. Digital image enhancement in the frequency domain 10%
4. Digital image restoration: inverse filtering; Wiener filtering 15%
5. Color image processing 10%
6. Digital image compression techniques and standards: source coding; entropy coding, transform and predictive coding; JPEG; MPEG 10%
7. Image Segmentation: edge detection; threshoding; region segmentation 20%
8. Advanced topics: Morphology and recognition 10%
9. Advanced topics: Wavelets and multi-resolution processing 5%

Return to course list