ISDM

Imaging through scattering media via generative diffusion model

Paper: Imaging through scattering media via generative diffusion model

Authors: Z. Chen, B. Lin, S. Gao, W. Wan*, Q. Liu*

Applied Physics Letters (Vol.124, Issue 5)
https://pubs.aip.org/aip/apl/article/124/5/051101/3176612/Imaging-through-scattering-media-via-generative

Date : Jan-29-2024
Version : 1.0
The code and the algorithm are for non-comercial use only.
Copyright 2024, Department of Electronic Information Engineering, Nanchang University.

Checkpoints

ISDM : We provide pretrained checkpoints. You can download pretrained models from [Baidu cloud] (https://pan.baidu.com/s/1CX7xCh1uJl-h5ZojO5SkNQ?pwd=hdtp) Extract the code (hdtp)

Dataset

The dataset used to train the model in this experiment is MNIST dataset.

place the dataset in the train file under the church folder.

Train:

python main.py --config=configs/ve/church_ncsnpp_continuous.py --workdir=exp_train_church_max1_N1000 --mode=train --eval_folder=result

Test:

python ISDM_reconstruction.py

Structure diagram of imaging through scattering media

Training and reconstruction flow chart of ISDM

The scattering imaging system

Recovery results of measured scatter data by different methods

(a) USAF resolution targets, (b) speckles, (c) LR, (d) HIO, (e) TC, and (f) ISDM method. From top to bottom, G1E2: element 2 of group 1, G1E6: element 6 of group 1, G2E5: element 5 of group 2, and G3E2: element 2 of group 3.

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yqx7150/ISDM