Perceptually Motivated Loss Functions for Computer Generated Holographic Displays

Authors
Kadis, Andrew 
Yang, Fan 
Mouthaan, Ralf 
Wetherfield, Benjamin 

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Article
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Abstract

Understanding and improving the perceived quality of reconstructed images is key to developing computer-generated holography algorithms for high-fidelity holographic displays. However, current algorithms are typically optimized using mean squared error, which is widely criticized for its poor correlation with perceptual quality. In our work, we present a comprehensive analysis of employing contemporary image quality metrics (IQM) as loss-functions in the hologram optimization process. Extensive objective and subjective assessment of experimentally reconstructed images reveal the relative performance of IQM losses for hologram optimization. Our results reveal that the perceived image quality improves considerably when the appropriate IQM loss function is used, highlighting the value of developing perceptually-motivated loss functions for hologram optimization.

Publication Date
2022-05-11
Online Publication Date
2022-05-11
Acceptance Date
2022-04-13
Keywords
Journal Title
Scientific Reports
Journal ISSN
2045-2322
2045-2322
Volume Title
Publisher
Nature Publishing Group
Sponsorship
EPSRC (EP/T008369/1)
EPSRC (2108797)
Engineering and Physical Sciences Research Council (EP/P030181/1) The Cambridge Trust as well as The China Scholarship Council Department of Engineering, University of Cambridge (Richard Norman Scholarship)