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基于感知的计算机生成全息显示的损失函数。

Perceptually motivated loss functions for computer generated holographic displays.

机构信息

Centre of Molecular Materials, Photonics and Electronics, University of Cambridge, Cambridge, UK.

Research Division, VividQ Ltd., Cambridge, UK.

出版信息

Sci Rep. 2022 May 11;12(1):7709. doi: 10.1038/s41598-022-11373-8.

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.

摘要

理解和提高重建图像的感知质量是开发用于高逼真度全息显示的计算机生成全息算法的关键。然而,当前的算法通常使用均方误差进行优化,该方法因与感知质量相关性差而受到广泛批评。在我们的工作中,我们全面分析了在全息图优化过程中使用当代图像质量指标(IQM)作为损失函数的情况。对实验重建图像的广泛客观和主观评估揭示了 IQM 损失在全息图优化中的相对性能。我们的结果表明,当使用适当的 IQM 损失函数时,感知图像质量会有显著提高,这突出了为全息图优化开发基于感知的损失函数的价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0428/9095705/7469b1c01b70/41598_2022_11373_Fig1_HTML.jpg

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