ELEC4245: Digital Image Processing

The University of Hong Kong, Second Semester, 2018–19


  • The first class will be on January 15, 2019.

Calendar entry of ELEC4245 (subject to change as needed):

This course aims to help students gain a firm understanding in digital image processing and master its methods and techniques. It intends to build upon the knowledge students acquire in Signals and Linear Systems (ELEC3241) and extends it.

The course in general begins with the basics in 2D signals and systems, visual perception, image sensing and acquisition. It then proceeds to study various intensity transformations, histogram processing techniques, filters in both spatial and frequency domains, and how they can be used to enhance the quality of digital images. Next, it considers reconstruction and restoration of images due to degradations, how image quality is measured and color image processing. It then moves onto Image compression, which plays a pivotal role today’s Internet and multimedia applications. A core area of this course is to learn how to segment features/patterns from images. This includes using various methods to extract point, line, edge and regions. The course concludes by considering some typical image processing applications.

Specifically, it covers the areas of image acquisition and imaging systems, 2D continuous‐time and discrete‐time signals and systems, time and frequency representations, sampling and quantization issues, image filtering, convolution and enhancement, image reconstruction and restoration, color image processing, image quality evaluation, image transform and compression, applications and computer implementations.

  • Pre-requisite: ELEC3241 Signal and linear systems

  • Mutually exclusive with: ELEC3505, ELEC3225

  • Assessment: 40% continuous assessment, 60% examination

Grading and Standards of Assessment
  • A: Exceptionally good performance demonstrating a superior understanding of the subject matter, a foundation of extensive knowledge, a skillful use of concepts and/or materials, and ability to analyze and evaluate problems.

  • B: Good performance demonstrating capacity to use the appropriate concepts, a good understanding of the subject matter, and an ability to handle the problems and materials encountered in the course.

  • C: Adequate performance demonstrating an adequate understanding of the subject matter, an ability to handle relatively simple problems, and adequate preparation for moving on to more advanced work in the field.

  • D: Minimally acceptable performance demonstrating at least partial familiarity with the subject matter and some capacity to deal with relatively simple problems, but also demonstrating deficiencies serious enough to make it inadvisable to proceed further in the field without additional work.

  • F: Unacceptable performance demonstrating unfamiliarity with the subject matter, and lack of capacity to deal with relatively simple problems, and also demonstrating deficiencies serious enough to make it advisable to retake the course.

Course Learning Outcomes
  • Understand the need of digital image processing and the confluence of different fields, as well as the emerging problems in this area.

  • Understand the fundamental digital image processing techniques such as intensity transformation, filtering, enhancement, restoration, and compression.

  • Understand the basic design of image processing algorithms for specific applications.