Suggestions [Computational Light Laboratory]

[kaanaksit]

Thank you for adding our group's website to your list. There are some works from our side that you may find relevant for your README.md.

Data-driven (Learning-based) Methods

• Learned Holographic Light Transport (Kavaklı et al. 2022) describes an algorithmic approach to learning the light transport kernel (aka beam propagation) from actual photographs. For code visit here.

Iterative Methods

• Realistic Defocus Blur for Multiplane Computer-Generated Holography (Kavaklı et al. 2022) introduces several algorithmic approaches. This work includes a new targeting scheme inspired by Depth-of-Field rendering in Computer Graphics, a novel loss function for evaluating focus and defocused parts in a reconstructed image and an optimiser that adopts double phase constrain. This work helps mitigate typical artefacts that degrade visual quality in holographic displays, such as edge fringes and inaccurate defocus blur. For code visit here.

Perception-driven Methods

• Metameric Varifocal Holograms (Walton et al. 2022) A gaze-contingent foveated varifocal image generation routine for holographic displays. For code visit here.

All of our work is dependent on our in-house baked library named Odak. We are also active on Social media, and our website can be reached from here.

[bchao1]

Hi Professor Akşit, thank you for your suggestions. These papers are indeed very relevant. I'll make sure I read them and add them to the list.

On a side note, I have also worked on a research project about synthesizing realistic defocus blur (but for computational light field displays). However, that proof-of-concept work naively disregards diffraction, which might cause problems in real-world settings. Hence, I think that directly leveraging diffraction (CGH) to synthesize realistic defocus blur is a fascinating and fruitful direction.

[kaanaksit]

Hi Brian, I am planning on referring to your repository in my next lecture in August. Please keep this one growing, it can help newcomers and even experts in the field.

[kaanaksit]

Holographic Display Architectures and Optics

There are also also two works from our side that uses Holographic Optical Elements (HOEs) for near-eye display optics and architectures.

• Varifocal Augmented Reality Near-Eye Displays to my knowledge this is the first paper that introduces varifocal augmented reality near-eye displays using HOEs.
• Foveated Augmented Reality Near-Eye Displays This specific paper introduces a foveated near-eye display hardware using HOEs.

Beside our work, you may want to make sure to have some seminal books listed for your audience. You already have Goodman's book. There is also this one:

• Max Born and Emil Wolf. 2013. Principles of optics: electromagnetic theory of propagation, interference and diffraction of light. Elsevier.

And many people in the past, started their first CGH simulations by reading this book:

• Schmidt, Jason Daniel. "Numerical simulation of optical wave propagation: With examples in MATLAB." SPIE, 2010.

One more addition for your hardware section could also be this one:

• Cakmakci, Ozan, Yi Qin, Peter Bosel, and Gordon Wetzstein. "Holographic pancake optics for thin and lightweight optical see-through augmented reality." Optics Express 29, no. 22 (2021): 35206-35215.

[bchao1]

Thank you for providing these great resources!!! Hopefully this list continues to grow.

[kaanaksit]

These could also be a meaningful addition for your list:

• Kavaklı, Koray, Liang Shi, Hakan Urey, Wojciech Matusik, and Kaan Akşit. "Multi-color Holograms Improve Brightness in Holographic Displays." In SIGGRAPH Asia 2023 Conference Papers, pp. 1-11. 2023.

• Markley, Eric, Nathan Matsuda, Florian Schiffers, Oliver Cossairt, and Grace Kuo. "Simultaneous Color Computer Generated Holography." In SIGGRAPH Asia 2023 Conference Papers, pp. 1-11. 2023.

These two papers both explores illuminating a phase-only hologram with multiple light sources to reconstruct a full color scene in 3D. The one from my group has a project website here. In addition, the optimization process in our work could further be simplified by predicting the required light dosages for each scene before optimizing a hologram:

• Zhan, Yicheng, Koray Kavaklı, Hakan Ürey, Qi Sun, and Kaan Akşit. "AutoColor: learned light power control for multi-color holograms." In Optical Architectures for Displays and Sensing in Augmented, Virtual, and Mixed Reality (AR, VR, MR) V, vol. 12913, pp. 96-102. SPIE, 2024.

This project has its project website here. The interesting side bit about this work is the usage of a large language model and a generative model to build a hologram dataset.