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Perceptually motivated loss functions for computer generated holographic displays.
Yang, Fan; Kadis, Andrew; Mouthaan, Ralf; Wetherfield, Benjamin; Kaczorowski, Andrzej; Wilkinson, Timothy D.
Afiliación
  • Yang F; Centre of Molecular Materials, Photonics and Electronics, University of Cambridge, Cambridge, UK.
  • Kadis A; Research Division, VividQ Ltd., Cambridge, UK.
  • Mouthaan R; Centre of Molecular Materials, Photonics and Electronics, University of Cambridge, Cambridge, UK.
  • Wetherfield B; Centre of Molecular Materials, Photonics and Electronics, University of Cambridge, Cambridge, UK.
  • Kaczorowski A; Centre of Molecular Materials, Photonics and Electronics, University of Cambridge, Cambridge, UK.
  • Wilkinson TD; Research Division, VividQ Ltd., Cambridge, UK.
Sci Rep ; 12(1): 7709, 2022 05 11.
Article en En | MEDLINE | ID: mdl-35546601
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Holografía Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Holografía Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido