Open Source Software

We share our codeWe are committed to making all our software available for free in all not-for-profit applications. We also go the extra mile and provide examples that facilitate the dissemination of our work. We do our best to respond to inquiries about our code in a timely manner. However, our team does not have the ability to provide assistance with general matlab / python inquiries.
We kindly ask that you cite the related publications. https://github.com/UNC-optics.

GitHub - UNC-optics/DeepCGH: A Python/TensorFlow implementation of DeepCGH, a framework for unsupervised deep learning-based computer-generated holography.A Python/TensorFlow implementation of DeepCGH, a framework for unsupervised deep learning-based computer-generated holography. - GitHub - UNC-optics/DeepCGH: A Python/TensorFlow implementation of D...

DeepCGH (Python)

DeepCGH is an unsupervised, non-iterative algorithm for computer-generated holography.

Related publication

M. Hossein Eybposh, Nicholas W. Caira, Mathew Atisa, Praneeth Chakravarthula, and Nicolas C. Pégard, "DeepCGH: 3D computer-generated holography using deep learning," Opt. Express 28, 26636-26650 (2020)
https://doi.org/10.1364/OE.399624 (OPEN ACCESS)

Additional relevant references

M. Hossein Eybposh, Vincent R. Curtis, Jose Rodriguez-Romaguera, Nicolas C. Pégard, "Advances in computer-generated holography for targeted neuronal modulation," Neurophoton. 9(4) 041409 (16 June 2022) https://doi.org/10.1117/1.NPh.9.4.041409

GitHub - UNC-optics/NOVO-CGHContribute to UNC-optics/NOVO-CGH development by creating an account on GitHub.

NoVo-CGH (Matlab)

Non-convex Volumetric CDG is an algorithm for computer-generated holography that relies on nonlinear optimization with gradient descent .

Related publication

Jingzhao Zhang, Nicolas Pégard, Jingshan Zhong, Hillel Adesnik, and Laura Waller, "3D computer-generated holography by non-convex optimization," Optica 4, 1306-1313 (2017)
https://doi.org/10.1364/OPTICA.4.001306 (OPEN ACCESS)

GitHub - UNC-optics/DCGHContribute to UNC-optics/DCGH development by creating an account on GitHub.

Dynamic CGH (Matlab)

A toolbox of functions to implement DCGH, a new light sculpting technique that renders speckle-free 3D images by rapidly displaying a superposition of jointly optimized coherent waves.

Related publication

V. R. Curtis, N. W. Caira, J. Xu, A. G. Sata and N. C. Pégard, "DCGH: Dynamic Computer Generated Holography for Speckle-Free, High Fidelity 3D Displays," 2021 IEEE Virtual Reality and 3D User Interfaces 2021, pp. 1-9
https://doi.org/10.1109/VR50410.2021.00097 (OPEN ACCESS)

Additional relevant references

Roadmap on wavefront shaping and deep imaging in complex media, Sylvain Gigan et al. Journal of Physics: Photonics, Volume 4, Number 4 (2022)

M. H. Eybposh, V. R. Curtis, A. Moossavi, and N. C. Pégard, "Dynamic Computer Generated Holography for Virtual Reality Displays," in Frontiers in Optics + Laser Science 2021 (Optica Publishing Group, 2021), paper FM3B.3.

V. R. Curtis, J. Xu, N. W. Caira, A. G. Sata, and N. C. Pégard, "High Fidelity 3D Image Synthesis with Dynamic Computer Generated Holography (DCGH)," in Conference on Lasers and Electro-Optics, OSA Technical Digest (Optica Publishing Group, 2021), paper STh2D.2