Perceptually guided computer-generated holography

Perceptually guided computer-generated holography
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感知引导计算机生成全息术

DOI:
10.1117/12.2610251
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发表时间:
2022
期刊:
--
影响因子:
--
通讯作者:
Aksit K
Aksit K
中科院分区:
--
文献类型:
--
作者:
Aksit K

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计算机生成全息(CGH)承诺在任何深度提供真实的高质量视觉效果。我们认为,结合计算全息和感知引导图形可以很快导致实际的全息显示系统,提供感知逼真的图像。我们提出了一种新的计算全息方法,称为同色异谱变焦全息图。我们的CGH方法仅在用户的焦平面上生成图像,而显示的图像在统计上是正确的,并且与周边视觉(条件等色)上的实际目标无法区分。因此,观察我们的全息图的用户被设置为在他们的注视位置处感知高质量的视觉。同时,图像的完整性在其余外围部分中遵循统计上正确的趋势。我们在现代GPU上展示了我们可区分的CGH优化管道,并通过显示原型支持我们的发现。我们的方法将为摆脱经典CGH问题(如斑点噪声或视觉质量差)的逼真视觉效果铺平道路。
Computer-Generated Holography (CGH) promises to deliver genuine, high-quality visuals at any depth. We argue that combining CGH and perceptually guided graphics can soon lead to practical holographic display systems that deliver perceptually realistic images. We propose a new CGH method called metameric varifocal holograms. Our CGH method generates images only at a user’s focus plane while displayed images are statistically correct and indistinguishable from actual targets across peripheral vision (metamers). Thus, a user observing our holograms is set to perceive a high quality visual at their gaze location. At the same time, the integrity of the image follows a statistically correct trend in the remaining peripheral parts. We demonstrate our differentiable CGH optimization pipeline on modern GPUs, and we support our findings with a display prototype. Our method will pave the way towards realistic visuals free from classical CGH problems, such as speckle noise or poor visual quality.
同色异谱变焦全息术
DOI: --
发表时间: 2021
期刊: arXiv.org
影响因子: --
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发表时间: 2021
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发表时间: 2021-12-01
影响因子: 3.4
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通讯作者: Urey, Hakan