MIPI 2022 Challenge on Quad-Bayer Re-mosaic: Dataset and Report

Qingyu Yang; Guang Yang; Jun Jiang; Chongyi Li; Ruicheng Feng; Shangchen Zhou; Wenxiu Sun; Qingpeng Zhu; Chen Change Loy; Jinwei Gu; Zhen Wang; Daoyu Li; Yuzhe Zhang; Lintao Peng; Xuyang Chang; Yinuo Zhang; Yaqi Wu; Xun Wu; Zhihao Fan; Chengjie Xia; Feng Zhang; Haijin Zeng; Kai Feng; Yongqiang Zhao; Hiep Quang Luong; Jan Aelterman; Anh Minh Truong; Wilfried Philips; Xiaohong Liu; Jun Jia; Hanchi Sun; Guangtao Zhai; Longan Xiao; Qihang Xu; Ting Jiang; Qi Wu; Chengzhi Jiang; Mingyan Han; Xinpeng Li; Wenjie Lin; Youwei Li; Haoqiang Fan; Shuaicheng Liu; Rongyuan Wu; Lingchen Sun; Qiaosi Yi

doi:10.1007/978-3-031-25072-9_2

MIPI 2022 Challenge on Quad-Bayer Re-mosaic: Dataset and Report

Qingyu Yang, Guang Yang, Jun Jiang, Chongyi Li, Ruicheng Feng, Shangchen Zhou, Wenxiu Sun, Qingpeng Zhu, Chen Change Loy, Jinwei Gu, Zhen Wang, Daoyu Li, Yuzhe Zhang, Lintao Peng, Xuyang Chang, Yinuo Zhang, Yaqi Wu, Xun Wu, Zhihao Fan, Chengjie XiaFeng Zhang, Haijin Zeng, Kai Feng, Yongqiang Zhao, Hiep Quang Luong, Jan Aelterman, Anh Minh Truong, Wilfried Philips, Xiaohong Liu, Jun Jia, Hanchi Sun, Guangtao Zhai, Longan Xiao, Qihang Xu, Ting Jiang, Qi Wu, Chengzhi Jiang, Mingyan Han, Xinpeng Li, Wenjie Lin, Youwei Li, Haoqiang Fan, Shuaicheng Liu, Rongyuan Wu, Lingchen Sun, Qiaosi Yi

School of Automation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). To bridge the gap, we introduce the first MIPI challenge including five tracks focusing on novel image sensors and imaging algorithms. In this paper, Quad Joint Remosaic and Denoise, one of the five tracks, working on the interpolation of Quad CFA to Bayer at full-resolution is introduced. The participants were provided with a new dataset including 70 (training) and 15 (validation) scenes of high-quality Quad and Bayer pair. In addition, for each scene, Quad of different noise level were provided at 0 dB, 24 dB and 42 dB. All the data were captured using a Quad sensor in both outdoor and indoor conditions. The final results are evaluated using objective metrics including PSNR, SSIM [6], LPIPS [10] and KLD. A detailed description of all models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found in https://github.com/mipi-challenge/MIPI2022.

Original language	English
Title of host publication	Computer Vision – ECCV 2022 Workshops, Proceedings
Editors	Leonid Karlinsky, Tomer Michaeli, Ko Nishino
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	21-35
Number of pages	15
ISBN (Print)	9783031250712
DOIs	https://doi.org/10.1007/978-3-031-25072-9_2
State	Published - 2023
Event	17th European Conference on Computer Vision, ECCV 2022 - Tel Aviv, Israel Duration: 23 Oct 2022 → 27 Oct 2022

Publication series

Name	Lecture Notes in Computer Science
Volume	13805 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th European Conference on Computer Vision, ECCV 2022
Country/Territory	Israel
City	Tel Aviv
Period	23/10/22 → 27/10/22

Keywords

Bayer
Denoise
MIPI challenge
Quad
Remosaic

Access to Document

10.1007/978-3-031-25072-9_2

Cite this

Yang, Q., Yang, G., Jiang, J., Li, C., Feng, R., Zhou, S., Sun, W., Zhu, Q., Loy, C. C., Gu, J., Wang, Z., Li, D., Zhang, Y., Peng, L., Chang, X., Zhang, Y., Wu, Y., Wu, X., Fan, Z., ... Yi, Q. (2023). MIPI 2022 Challenge on Quad-Bayer Re-mosaic: Dataset and Report. In L. Karlinsky, T. Michaeli, & K. Nishino (Eds.), Computer Vision – ECCV 2022 Workshops, Proceedings (pp. 21-35). (Lecture Notes in Computer Science; Vol. 13805 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-25072-9_2

@inproceedings{51aa51b0e87a479f980126e432fb21b4,

title = "MIPI 2022 Challenge on Quad-Bayer Re-mosaic: Dataset and Report",

abstract = "Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). To bridge the gap, we introduce the first MIPI challenge including five tracks focusing on novel image sensors and imaging algorithms. In this paper, Quad Joint Remosaic and Denoise, one of the five tracks, working on the interpolation of Quad CFA to Bayer at full-resolution is introduced. The participants were provided with a new dataset including 70 (training) and 15 (validation) scenes of high-quality Quad and Bayer pair. In addition, for each scene, Quad of different noise level were provided at 0 dB, 24 dB and 42 dB. All the data were captured using a Quad sensor in both outdoor and indoor conditions. The final results are evaluated using objective metrics including PSNR, SSIM [6], LPIPS [10] and KLD. A detailed description of all models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found in https://github.com/mipi-challenge/MIPI2022.",

keywords = "Bayer, Denoise, MIPI challenge, Quad, Remosaic",

author = "Qingyu Yang and Guang Yang and Jun Jiang and Chongyi Li and Ruicheng Feng and Shangchen Zhou and Wenxiu Sun and Qingpeng Zhu and Loy, {Chen Change} and Jinwei Gu and Zhen Wang and Daoyu Li and Yuzhe Zhang and Lintao Peng and Xuyang Chang and Yinuo Zhang and Yaqi Wu and Xun Wu and Zhihao Fan and Chengjie Xia and Feng Zhang and Haijin Zeng and Kai Feng and Yongqiang Zhao and Luong, {Hiep Quang} and Jan Aelterman and Truong, {Anh Minh} and Wilfried Philips and Xiaohong Liu and Jun Jia and Hanchi Sun and Guangtao Zhai and Longan Xiao and Qihang Xu and Ting Jiang and Qi Wu and Chengzhi Jiang and Mingyan Han and Xinpeng Li and Wenjie Lin and Youwei Li and Haoqiang Fan and Shuaicheng Liu and Rongyuan Wu and Lingchen Sun and Qiaosi Yi",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 17th European Conference on Computer Vision, ECCV 2022 ; Conference date: 23-10-2022 Through 27-10-2022",

year = "2023",

doi = "10.1007/978-3-031-25072-9_2",

language = "英语",

isbn = "9783031250712",

series = "Lecture Notes in Computer Science",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "21--35",

editor = "Leonid Karlinsky and Tomer Michaeli and Ko Nishino",

booktitle = "Computer Vision – ECCV 2022 Workshops, Proceedings",

}

Yang, Q, Yang, G, Jiang, J, Li, C, Feng, R, Zhou, S, Sun, W, Zhu, Q, Loy, CC, Gu, J, Wang, Z, Li, D, Zhang, Y, Peng, L, Chang, X, Zhang, Y, Wu, Y, Wu, X, Fan, Z, Xia, C, Zhang, F, Zeng, H, Feng, K, Zhao, Y, Luong, HQ, Aelterman, J, Truong, AM, Philips, W, Liu, X, Jia, J, Sun, H, Zhai, G, Xiao, L, Xu, Q, Jiang, T, Wu, Q, Jiang, C, Han, M, Li, X, Lin, W, Li, Y, Fan, H, Liu, S, Wu, R, Sun, L & Yi, Q 2023, MIPI 2022 Challenge on Quad-Bayer Re-mosaic: Dataset and Report. in L Karlinsky, T Michaeli & K Nishino (eds), Computer Vision – ECCV 2022 Workshops, Proceedings. Lecture Notes in Computer Science, vol. 13805 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 21-35, 17th European Conference on Computer Vision, ECCV 2022, Tel Aviv, Israel, 23/10/22. https://doi.org/10.1007/978-3-031-25072-9_2

MIPI 2022 Challenge on Quad-Bayer Re-mosaic: Dataset and Report. / Yang, Qingyu; Yang, Guang; Jiang, Jun et al.
Computer Vision – ECCV 2022 Workshops, Proceedings. ed. / Leonid Karlinsky; Tomer Michaeli; Ko Nishino. Springer Science and Business Media Deutschland GmbH, 2023. p. 21-35 (Lecture Notes in Computer Science; Vol. 13805 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - MIPI 2022 Challenge on Quad-Bayer Re-mosaic

T2 - 17th European Conference on Computer Vision, ECCV 2022

AU - Yang, Qingyu

AU - Yang, Guang

AU - Jiang, Jun

AU - Li, Chongyi

AU - Feng, Ruicheng

AU - Zhou, Shangchen

AU - Sun, Wenxiu

AU - Zhu, Qingpeng

AU - Loy, Chen Change

AU - Gu, Jinwei

AU - Wang, Zhen

AU - Li, Daoyu

AU - Zhang, Yuzhe

AU - Peng, Lintao

AU - Chang, Xuyang

AU - Zhang, Yinuo

AU - Wu, Yaqi

AU - Wu, Xun

AU - Fan, Zhihao

AU - Xia, Chengjie

AU - Zhang, Feng

AU - Zeng, Haijin

AU - Feng, Kai

AU - Zhao, Yongqiang

AU - Luong, Hiep Quang

AU - Aelterman, Jan

AU - Truong, Anh Minh

AU - Philips, Wilfried

AU - Liu, Xiaohong

AU - Jia, Jun

AU - Sun, Hanchi

AU - Zhai, Guangtao

AU - Xiao, Longan

AU - Xu, Qihang

AU - Jiang, Ting

AU - Wu, Qi

AU - Jiang, Chengzhi

AU - Han, Mingyan

AU - Li, Xinpeng

AU - Lin, Wenjie

AU - Li, Youwei

AU - Fan, Haoqiang

AU - Liu, Shuaicheng

AU - Wu, Rongyuan

AU - Sun, Lingchen

AU - Yi, Qiaosi

PY - 2023

Y1 - 2023

N2 - Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). To bridge the gap, we introduce the first MIPI challenge including five tracks focusing on novel image sensors and imaging algorithms. In this paper, Quad Joint Remosaic and Denoise, one of the five tracks, working on the interpolation of Quad CFA to Bayer at full-resolution is introduced. The participants were provided with a new dataset including 70 (training) and 15 (validation) scenes of high-quality Quad and Bayer pair. In addition, for each scene, Quad of different noise level were provided at 0 dB, 24 dB and 42 dB. All the data were captured using a Quad sensor in both outdoor and indoor conditions. The final results are evaluated using objective metrics including PSNR, SSIM [6], LPIPS [10] and KLD. A detailed description of all models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found in https://github.com/mipi-challenge/MIPI2022.

AB - Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). To bridge the gap, we introduce the first MIPI challenge including five tracks focusing on novel image sensors and imaging algorithms. In this paper, Quad Joint Remosaic and Denoise, one of the five tracks, working on the interpolation of Quad CFA to Bayer at full-resolution is introduced. The participants were provided with a new dataset including 70 (training) and 15 (validation) scenes of high-quality Quad and Bayer pair. In addition, for each scene, Quad of different noise level were provided at 0 dB, 24 dB and 42 dB. All the data were captured using a Quad sensor in both outdoor and indoor conditions. The final results are evaluated using objective metrics including PSNR, SSIM [6], LPIPS [10] and KLD. A detailed description of all models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found in https://github.com/mipi-challenge/MIPI2022.

KW - Bayer

KW - Denoise

KW - MIPI challenge

KW - Quad

KW - Remosaic

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