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CS356

IMAGE AND OPTICAL PROCESSING

Credits
5
Year
4
Semester
1
Department
COMPUTER SCIENCE

Overview

Introduction to image processing; physical considerations (transfer functions, dynamic range, sampling, noise); two-dimensional transforms (e.g. the Fourier transform) and their properties; convolution; object recognition; deep learning convolutional neural networks for object recognition and segmentation; optical image processing; optical computing; three-dimensional image processing using digital holograms.

Learning Outcomes

  • Discuss applications of image processing in academia and industry
  • Explain the limits of image processing on poor quality data
  • Verify Fourier transform theorems using a high-level programming language
  • Design and implement a convolution filter for a given task
  • Design, implement, and train a convolutional neural network for an image processing task
  • Simulate optical image processing and optical computing architectures
  • Analyse the three-dimensional display limits of an arbitrary three-dimensional display
  • Implement various image processing tasks on three-dimensional objects encoded in digital holograms