Differentiable Imaging

Differentiable imaging represents a foundational paradigm in computational imaging. Leveraging differentiable programming, it effectively bridges the gaps among core system components, enabling authentic co-design to move from concept to practical implementation.

Publications:

  1. Ni Chen, Liangcai Cao, T.-C. Poon, Byoungho Lee, Edmund Y. Lam, “Differentiable Imaging: a new tool for computational optical imaging,” Advanced Physics Research 2(3), 2023.
  2. Ni Chen, David J. Brady, Edmund Y. Lam, “Differentiable Imaging: Progress, Challenges, and Outlook,” Advanced Devices & Instrumentation, 2025.
  3. Ni Chen, Edmund Y. Lam, “Differentiable pixel super resolution lensless imaging,” Optics Letters 50(5), 2025.
  4. Ni Chen, Congli Wang, Wolfgang Heidrich, “∂H: Differentiable Holography,” Laser & Photonics Reviews 17(9), 2023.
  5. Yang Wu, Jun Wang, Sigurdur Thoroddsen, Ni Chen, “Single-Shot High-Density Volumetric Particle Imaging Enabled by Differentiable Holography,” IEEE Transactions on Industrial Informatics 20(12), 2024.
  6. Congli Wang, Ni Chen, and Wolfgang Heidrich. “dO: A differentiable engine for deep lens design of computational imaging systems”. IEEE Transactions on Computational Imaging, 8(1), 2022.