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Stanford University

EE368: Digital Image Processing

About This Course

Image sampling and quantization color, point operations, segmentation, morphological image processing, linear image filtering and correlation, image transforms, eigenimages, multiresolution image processing, noise reduction and restoration, feature extraction and recognition tasks, image registration. Emphasis is on the general principles of image processing. Students learn to apply material by implementing and investigating image processing algorithms in Matlab and optionally on Android mobile devices. Term project. In the fall and spring quarter, a sequence of interactive web/video modules substitutes the classroom lectures. In the winter quarter, the course is taught conventionally; both versions of the course are equivalent.

Recommended Prerequisites

EE261, EE278B, or equivalent.

Course Staff

Bernd Girod

Senior Associate Dean and Professor in School of Enginering

David Chen

Doctoral Student in School of Engineering

Matt Yu

Doctoral Student in School of Engineering

  1. Course Number

  2. Classes Start

    Sep 22, 2013
  3. Classes End

    Dec 13, 2013