Computational Imagers, Sensors, and Displays

Computational imaging, sensing, and display systems have a wide range of applications in consumer electronics, scientific imaging, HCI, medical analysis, microscopy, and remote sensing. This is an interdisciplinary course that rides across domain interests in traditional electrical engineering, computer science, and human vision science.

This course discusses digital photography and basic image processing, convolutional neural networks for image processing, denoising, deconvolution, inverse problems in imaging, proximal gradient methods, introduction to wave optics, extended depth of field and high dynamic range imaging, end-to-end optimization of optics and imaging processing. We also discuss emerging computational display techniques, in particular light field and holographic solutions for 3D displays. Emphasis is on applied image processing and solving inverse problems using classic algorithms, formal optimization, and modern artificial intelligence techniques, for camera and display applications. Students learn to apply material by implementing and investigating image processing algorithms in Python.