Metameric Varifocal Holograms

Computer-Generated Holography (CGH) offers the potential for genuine, high-quality three-dimensional visuals. However, fulfilling this potential remains a practical challenge due to computational complexity and visual quality issues. We propose a new CGH method that exploits gaze-contingency and perceptual graphics to accelerate the development of practical holographic display systems. Firstly, our method infers the user's focal depth and generates images only at their focus plane without using any moving parts. Second, the images displayed are metamers; in the user's peripheral vision, they need only be statistically correct and blend with the fovea seamlessly. Unlike previous methods, our method prioritises and improves foveal visual quality without causing perceptually visible distortions at the periphery. To enable our method, we introduce a novel metameric loss function that robustly compares the statistics of two given images for a known gaze location. In parallel, we implement a model representing the relation between holograms and their image reconstructions. We couple our differentiable loss function and model to metameric varifocal holograms using a stochastic gradient descent solver. We evaluate our method with an actual proof-of-concept holographic display, and we show that our CGH method leads to practical and perceptually three-dimensional image reconstructions.

Automated summary

In the study of computer-generated holography, we propose a new method that utilizes gaze-contingency and perceptual graphics to accelerate the development of practical holographic display systems. By inferring the user's focal depth and generating images only at their focus plane, we are able to improve foveal visual quality and reduce distortions in peripheral vision. We also introduce a novel metameric loss function for comparing image statistics and implement a model representing the relation between holograms and image reconstructions.