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Image Systems Engineering

Image Systems Engineering
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Description

In this introduction to digital imaging technologies, learn how software simulation is used to model image systems components and the human visual system. Gain insight into how imaging technologies handle the requirements of complex biological and psychological processes. Explore the basic tools used in digital imaging and image quality measurement and the value of image systems simulations in neuroscience and industrial vision applications. This course will include a project component.

Non-degree option students are required to take this course for 3 units.

Prerequisites

EE261 or equivalent. Some background in mathematics (linear algebra) and programming (Matlab) is valuable.

Topics include

  • Image processing principles
  • Image sensors
  • Basic principles of optics (Snell's Law, diffraction, adaptive optics, light fields)
  • Color science, metrics and calibration
  • Human vision (space, depth, motion)
  • Displays
  • Computational methods

Course Availability

The course schedule is displayed for planning purposes – courses can be modified, changed, or cancelled. Course availability will be considered finalized on the first day of open enrollment. For quarterly enrollment dates, please refer to our graduate education section.

Course Archived
School
Stanford School of Humanities and Sciences
Language
English