2University of California, Irvine, Beckman Laser Institute and Medical Clinic, Irvine, California, United States
- [2026.04] 🎉🎉🎉 Congratulations! NeOTF has been accepted by Advanced Photonics.
- [2025.12] The code repo is released on Github.
- [2025.11] The preprint is available on arXiv.
NeOTF is a guidestar-free OTF retrieval method for imaging through dynamic scattering media. By optimizing a neural representation with only a few speckle images from unknown objects, NeOTF robustly retrieves the system's OTF without a guidestar.
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Clone repo
git clone https://github.com/Xia-Research-Lab/NeOTF.git cd NeOTF -
Install dependent packages
conda create -n NeOTF python=3.10 -y conda activate NeOTF pip install torch numpy pillow matplotlib tqdm pyyaml
For training and reconstructing images from default multi-frame speckles, simply run:
python NeOTF.py --config ./config.ymlRun all baseline methods (HIO+ER, MORE) alongside NeOTF:
bash run_main.sh --config config.yml --output_dir ./outputsMutliframe images are reconstructed from inverse filtering with the static OTF retrieved within NeOTF training. The NeOTF is visualized as below.
NeOTF.py: Main NeOTF training and reconstruction pipeline.MORE.py: MORE algorithm baseline.HIOER.py: HIO+ER algorithm baseline.SIREN.py: Neural network module.utils.py: Data loading and helper functions.config.yml: Default configuration file.run_main.sh: Benchmark bash script.
If our code helps your research or work, please consider citing our paper.
@article{sun2026neotf,
title={NeOTF: guidestar-free neural representation for broadband dynamic imaging through scattering},
author={Sun, Yunong and Xia, Fei},
journal={Advanced Photonics},
volume={8},
number={3},
pages={036007--036007},
year={2026},
publisher={Society of Photo-Optical Instrumentation Engineers}
}
