Deep Optics: Learning Cameras and Optical Computing Systems

Gordon Wetzstein, Hayato Ikoma, Christopher Metzler, Yifan Peng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


Neural networks and other advanced image processing algorithms excel in a wide variety of computer vision and imaging applications, but their high performance also comes at a high computational cost and their success is sometimes limited. Here, we review recent hybrid optical-digital strategies to computational imaging that outsource parts of the algorithm into the optical domain. Using such a co-design of optics and image processing, we can facilitate application-domain-specific cameras or compute parts of a convolutional neural network in optics. Optical computing happens at the speed of light and without any memory or power requirements, thereby opening new directions for intelligent imaging systems.
Original languageEnglish (US)
Title of host publication2020 54th Asilomar Conference on Signals, Systems, and Computers
Number of pages3
ISBN (Print)9780738131269
StatePublished - Jun 3 2021
Externally publishedYes


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