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Repository Details
Real-world Noisy Image Denoising: A New Benchmark
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The dataset in this package provides the real-world noisy images
as described in the following paper:
Jun Xu, Hui Li, Zhetong Liang, David Zhang, and Lei Zhang
Real-world Noisy Image Denoising: A New Benchmark
https://arxiv.org/abs/1804.02603, 2018.
Please cite the paper if you are using this dataset in your research.
Please see the file License.txt for the license governing this code.
Version: 1.1 (02/05/2019), see ChangeLog.txt
Contact: Jun Xu <[email protected]/[email protected]>
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Note
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For more shots of training and test real-world noisy images, please refer to
1. (Multiple Folders) https://pan.baidu.com/s/1539s_gNN8zvDYxG-DbiDuA (code: gy9b).
2. (One Zip File) https://pan.baidu.com/s/1uK8XTFdD8xReMa5cs_NPLg.
3. (Google Drive) https://drive.google.com/file/d/1tzNY-WTk3HRI8MiixDp1-Es1k55VgRKS/view?usp=sharing
Overview
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This dataset contains 40 different scenes captured by 5 cameras from the 3 leading brands of cameras:
1) Canon EOS (5D Mark II, 80D, 600D);
2) Nikon (D800);
3) Sony (A7 II).
We crop 100 regions of 512X512 from these 40 scenes:
The *Real.JPG are noisy images;
The *mean.JPG are "ground truth" images.
Dataset Details
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Camera 1: Canon EOS 5D Mark II
Image Name Size Aperture Shutter Speed ISO Value
Canon5D2_bag 2784 x 1856 f/5 1/200s 6400
Canon5D2_bicyc 2784 x 1856 f/5 1/160s 6400
Canon5D2_chair 2784 x 1856 f/5 1/160s 3200
Canon5D2_circu 2784 x 1856 f/5 1/160s 6400
Canon5D2_desk 2784 x 1856 f/5 1/160s 6400
Canon5D2_fruit 2784 x 1856 f/5 1/200s 3200
Canon5D2_mouse 2784 x 1856 f/5 1/160s 3200
Canon5D2_plug 2784 x 1856 f/5 1/160s 3200
Canon5D2_recie 2784 x 1856 f/5 1/160s 6400
Canon5D2_robot 2784 x 1856 f/5 1/160s 3200
Canon5D2_toy 2784 x 1856 f/5 1/200s 3200
Camera 2: Canon EOS 80D
Image Name Size Aperture Shutter Speed ISO Value
Canon80D_ball 2976 x 1680 f/8 1/8s 3200
Canon80D_compr 2976 x 1680 f/8 1/8s 6400
Canon80D_corne 2976 x 1680 f/8 1/8s 1600
Canon80D_GO 2976 x 1680 f/8 1/8s 800
Canon80D_print 2976 x 1680 f/8 1/8s 12800
Camera 3: Canon EOS 600D
Image Name Size Aperture Shutter Speed ISO Value
Canon600_book 5184 x 3456 f/4.5 1/125s 1600
Canon600_toy 5184 x 3456 f/4.5 1/125s 1600
Canon600_water 5184 x 3456 f/3.5 1/125s 1600
Camera 4: NIKON D800
Image Name Size Aperture Shutter Speed ISO Value
Nikon800_bulle 3680 x 2456 f/8 1/100s 6400
Nikon800_carbi 3680 x 2456 f/8 1/125s 4000
Nikon800_class 3680 x 2456 f/4.5 1/160s 1600
Nikon800_desch 3680 x 2456 f/11 1/160s 3200
Nikon800_desk 3680 x 2456 f/4.5 1/160s 3200
Nikon800_door 3680 x 2456 f/5.6 1/160s 6400
Nikon800_flowe 3680 x 2456 f/5 1/100s 4000
Nikon800_map 3680 x 2456 f/5 1/100s 4000
Nikon800_photo 3680 x 2456 f/8 1/125s 6400
Nikon800_plant 3680 x 2456 f/6.3 1/125s 5000
Nikon800_plaso 3680 x 2456 f/10 1/100s 6400
Nikon800_stair 3680 x 2456 f/5 1/125s 6400
Nikon800_wall 3680 x 2456 f/5 1/100s 6400
Camera 5: SonyA7II ILCE-7M2
Image Name Size Aperture Shutter Speed ISO Value
SonyA7II_book 3008 x 1688 f/4.5 1/125s 1600
SonyA7II_class 3008 x 1688 f/3.5 1/200s 1600
SonyA7II_compu 3008 x 1688 f/3.5 1/500s 3200
SonyA7II_door 3008 x 1688 f/4 1/200s 3200
SonyA7II_plant 3008 x 1688 f/4.5 1/125s 3200
SonyA7II_stair 3008 x 1688 f/10 1/10s 1600
SonyA7II_toy 3008 x 1688 f/4.5 1/125s 1600
SonyA7II_water 3008 x 1688 f/4.5 1/125s 6400
Other Datasets
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CC [1]: 15 cropped real-world noisy images from CC dataset.
This dataset can be found at http://snam.ml/research/ccnoise
The smaller 15 cropped images can be found on in the directory
''Real_ccnoise_denoised_part'' of
https://github.com/csjunxu/MCWNNM_ICCV2017
The *real.png are noisy images;
The *mean.png are "ground truth" images;
The *ours.png are images denoised by CC.
DND [2]: 1000 cropped real-world noisy images from DND dataset.
Please download the dataset from https://noise.visinf.tu-darmstadt.de/
and put the files in "DND_2017" directory accordingly.
SID [3]: http://cchen156.web.engr.illinois.edu/SID.html
SIDD [4]: Smartphone Image Denoising Dataset
https://www.eecs.yorku.ca/~kamel/sidd/index.php
[1] Seonghyeon Nam*, Youngbae Hwang*, Yasuyuki Matsushita, Seon Joo Kim. A Holistic Approach to Cross-Channel Image Noise Modeling and its Application to Image Denoising. CVPR, 2016.
[2] Tobias Pl?tz and Stefan Roth. Benchmarking Denoising Algorithms with Real Photographs. CVPR, 2017.
[3] Chen Chen, Qifeng Chen, Jia Xu and Vladlen Koltun. Learning to See in the Dark. CVPR, 2018.
[4] Abdelrahman Abdelhamed, Lin S., Brown M. S. A High-Quality Denoising Dataset for Smartphone Cameras. CVPR, 2018.
Dependency
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This dataset does not depend on any external dataset.
Contact
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If you have questions, problems with the code, or find a bug, please let us know. Contact Jun Xu at [email protected] or [email protected]
