Awesome
Towards General Low-Light Raw Noise Synthesis and Modeling (ICCV 2023)
Technical Report: <a href='https://openaccess.thecvf.com/content/ICCV2023/html/Zhang_Towards_General_Low-Light_Raw_Noise_Synthesis_and_Modeling_ICCV_2023_paper.html'><img src='https://img.shields.io/badge/paper-PDF-green'></a>
<img width="900" alt="image" src='./asset/results.png'>LRD is a general framework for low-light raw noise synthesis and modeling. Specifically, we synthesize the signal-dependent and signal-independent noise in a physics- and learning-based manner, respectively. In this way, our method can be considered as a general model, that is, it can simultaneously learn different noise characteristics for different ISO levels and generalize to various sensors.
:snake:Synthesis Pipeline
<img width="900" alt="image" src='./asset/framework.png'>:open_file_folder:LRD Dataset
The LRD dataset is available for download at Baidudisk (vj53) or Dropbox or One Drive
<img width="900" alt="image" src='./asset/datasets.png'>:heavy_check_mark:Pretrained Models
The pretrained models for raw denoise is available at Baidudisk (ujzm) or Google Drive.
Due to the business license, pre-trained models for noise synthesis are not available now.
:bookmark_tabs:Intallation
Download the ELD dataset and SID dataset at the following links:
ELD (official project): download (11.46 GB)
SID (official project): download (25 GB)
- Install the conda environment
conda create -n lrd python=3.8
conda activate lrd
- Install Pytorch
conda install pytorch==1.9 torchvision cudatoolkit=10.2 -c pytorch
- Install Packages for Raw Image
pip install ExifRead
pip install h5py
Note that the rawpy version is using ELD's customized rawpy, which can be downloaded from GoogleDrive or Baidudisk (0lby).
To build rawpy from source, please first compile and install the LibRaw library following the official instructions, then type pip install -e .
in the customized rawpy directory.
- Install other packages
pip install tqdm
pip install lmdb
pip install glob
pip install imageio
pip install PyYAML
pip install timm
pip install patchify
conda install -c conda-forge scipy
pip install opencv-python
pip install tensorboardx
pip install scikit-image
pip install colour
pip install pylab-sdk
pip install pillow
:car:Run
- Quick start to raw denoising tests for SID dataset
python test_denoise_SID.py
- Quick start to raw denoising tests for ELD dataset
python test_denoise_ELD.py
- Quick start to raw denoising tests for LRD dataset
python test_denoise_LRD.py
Due to the business license, the source code for noise synthesis is not available now.
:book: Citation
If you find our LRD model useful for you, please consider citing :mega:
@InProceedings{Zhang_2023_ICCV,
author = {Zhang, Feng and Xu, Bin and Li, Zhiqiang and Liu, Xinran and Lu, Qingbo and Gao, Changxin and Sang, Nong},
title = {Towards General Low-Light Raw Noise Synthesis and Modeling},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2023},
pages = {10820-10830}
}
:email:Contact
If you have any question, feel free to email fengzhangaia@hust.edu.cn.