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Citation

DeepLens Hyperspectral Imaging is an application example built on the DeepLens framework. If you use this code or these ideas in your research, please cite the DeepLens framework paper:

X. Yang, M. Souza, K. Wang, P. Chakravarthula, Q. Fu, and W. Heidrich, "End-to-End Hybrid Refractive-Diffractive Lens Design with Differentiable Ray-Wave Model," in SIGGRAPH Asia 2024 Conference Papers, 2024. doi:10.1145/3680528.3687640

@inproceedings{Yang_2024,
  title     = {End-to-End Hybrid Refractive-Diffractive Lens Design with Differentiable Ray-Wave Model},
  author    = {Yang, Xinge and Souza, Matheus and Wang, Kunyi and Chakravarthula, Praneeth and Fu, Qiang and Heidrich, Wolfgang},
  booktitle = {SIGGRAPH Asia 2024 Conference Papers},
  series    = {SA '24},
  pages     = {1--11},
  year      = {2024},
  month     = dec,
  publisher = {ACM},
  doi       = {10.1145/3680528.3687640},
  url       = {https://doi.org/10.1145/3680528.3687640}
}

Methods

The diffractive encoders implemented here are based on:

  • DiffractedRotation — D. S. Jeon, S.-H. Baek, S. Yi, Q. Fu, X. Dun, W. Heidrich, and M. H. Kim, "Compact Snapshot Hyperspectral Imaging with Diffracted Rotation," ACM Transactions on Graphics (SIGGRAPH), 2019.
  • RotationallySymmetric — X. Dun, H. Ikoma, G. Wetzstein, Z. Wang, X. Cheng, and Y. Peng, "Learned rotationally symmetric diffractive achromat for full-spectrum computational imaging," Optica, 2020.

For an analysis of how the optical encoder limits data-driven spectral reconstruction, see "Limitations of Data-Driven Spectral Reconstruction: An Optics-Aware Analysis" (code).

Acknowledgement

The freeform DOE height map (planar_doe.npy) was provided by Jingyue Ma.

License

DeepLens Hyperspectral Imaging is released under the Apache License 2.0.