NTIRE 2022 Spectral Demosaicing Challenge and Data Set

Boaz Arad; Radu Timofte; Rony Yahel; Nimrod Morag; Amir Bernat; Yaqi Wu; Xun Wu; Zhihao Fan; Chenjie Xia; Feng Zhang; Shuai Liu; Yongqiang Li; Chaoyu Feng; Lei Lei; Mingwei Zhang; Kai Feng; Xun Zhang; Jiaxin Yao; Yongqiang Zhao; Suina Ma; Fan He; Yangyang Dong; Shufang Yu; Difa Qiu; Jinhui Liu; Mengzhao Bi; Beibei Song; Wen Fang Sun; Jiesi Zheng; Bowen Zhao; Yanpeng Cao; Jiangxin Yang; Yanlong Cao; Xiangyu Kong; Jingbo Yu; Yuanyang Xue; Zheng Xie

doi:10.1109/CVPRW56347.2022.00103

NTIRE 2022 Spectral Demosaicing Challenge and Data Set

Boaz Arad, Radu Timofte, Rony Yahel, Nimrod Morag, Amir Bernat, Yaqi Wu, Xun Wu, Zhihao Fan, Chenjie Xia, Feng Zhang, Shuai Liu, Yongqiang Li, Chaoyu Feng, Lei Lei, Mingwei Zhang, Kai Feng, Xun Zhang, Jiaxin Yao, Yongqiang Zhao, Suina MaFan He, Yangyang Dong, Shufang Yu, Difa Qiu, Jinhui Liu, Mengzhao Bi, Beibei Song, Wen Fang Sun, Jiesi Zheng, Bowen Zhao, Yanpeng Cao, Jiangxin Yang, Yanlong Cao, Xiangyu Kong, Jingbo Yu, Yuanyang Xue, Zheng Xie

Department of Computer Science

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

37 Scopus citations

Abstract

This paper presents the first challenge on demosaicing of natural spectral images for snapshot hyperspectral imaging systems (HIS) which utilize a multi-spectral filer array (MSFA), i.e., the recovery of whole-scene hyperspectral information from spatially sub-sampled hyperspectral information. This challenge expands the "ARAD_1K"data set to a first-of-its-kind large-scale data set for multispectral filter array demosaicing of natural scenes containing 1,000 images. Challenge participants were required to recover hyperspectral information from synthetically generated MSFA images simulating capture by a known calibrated snapshot mosaic hyperspectral camera. The challenge was attended by 157 teams, with 29 teams competing in the final testing phase, 7 of which provided detailed descriptions of their methodology which are included in this report. The performance of these submissions is reviewed and provided here as a gauge for the current state-of-the-art in multi-spectral filter array demosaicing of natural images.

Original language	English
Title of host publication	Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
Publisher	Institute of Electrical and Electronics Engineers
Pages	881-895
Number of pages	15
ISBN (Electronic)	9781665487399
DOIs	https://doi.org/10.1109/CVPRW56347.2022.00103
State	Published - 1 Jan 2022
Event	2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 - New Orleans, United States Duration: 19 Jun 2022 → 20 Jun 2022

Publication series

Name	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume	2022-June
ISSN (Print)	2160-7508
ISSN (Electronic)	2160-7516

Conference

Conference	2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
Country/Territory	United States
City	New Orleans
Period	19/06/22 → 20/06/22

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

Access to Document

10.1109/CVPRW56347.2022.00103

Cite this

Arad, B., Timofte, R., Yahel, R., Morag, N., Bernat, A., Wu, Y., Wu, X., Fan, Z., Xia, C., Zhang, F., Liu, S., Li, Y., Feng, C., Lei, L., Zhang, M., Feng, K., Zhang, X., Yao, J., Zhao, Y., ... Xie, Z. (2022). NTIRE 2022 Spectral Demosaicing Challenge and Data Set. In Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 (pp. 881-895). (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2022-June). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CVPRW56347.2022.00103

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abstract = "This paper presents the first challenge on demosaicing of natural spectral images for snapshot hyperspectral imaging systems (HIS) which utilize a multi-spectral filer array (MSFA), i.e., the recovery of whole-scene hyperspectral information from spatially sub-sampled hyperspectral information. This challenge expands the {"}ARAD_1K{"}data set to a first-of-its-kind large-scale data set for multispectral filter array demosaicing of natural scenes containing 1,000 images. Challenge participants were required to recover hyperspectral information from synthetically generated MSFA images simulating capture by a known calibrated snapshot mosaic hyperspectral camera. The challenge was attended by 157 teams, with 29 teams competing in the final testing phase, 7 of which provided detailed descriptions of their methodology which are included in this report. The performance of these submissions is reviewed and provided here as a gauge for the current state-of-the-art in multi-spectral filter array demosaicing of natural images.",

author = "Boaz Arad and Radu Timofte and Rony Yahel and Nimrod Morag and Amir Bernat and Yaqi Wu and Xun Wu and Zhihao Fan and Chenjie Xia and Feng Zhang and Shuai Liu and Yongqiang Li and Chaoyu Feng and Lei Lei and Mingwei Zhang and Kai Feng and Xun Zhang and Jiaxin Yao and Yongqiang Zhao and Suina Ma and Fan He and Yangyang Dong and Shufang Yu and Difa Qiu and Jinhui Liu and Mengzhao Bi and Beibei Song and Sun, {Wen Fang} and Jiesi Zheng and Bowen Zhao and Yanpeng Cao and Jiangxin Yang and Yanlong Cao and Xiangyu Kong and Jingbo Yu and Yuanyang Xue and Zheng Xie",

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Arad, B, Timofte, R, Yahel, R, Morag, N, Bernat, A, Wu, Y, Wu, X, Fan, Z, Xia, C, Zhang, F, Liu, S, Li, Y, Feng, C, Lei, L, Zhang, M, Feng, K, Zhang, X, Yao, J, Zhao, Y, Ma, S, He, F, Dong, Y, Yu, S, Qiu, D, Liu, J, Bi, M, Song, B, Sun, WF, Zheng, J, Zhao, B, Cao, Y, Yang, J, Cao, Y, Kong, X, Yu, J, Xue, Y & Xie, Z 2022, NTIRE 2022 Spectral Demosaicing Challenge and Data Set. in Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 2022-June, Institute of Electrical and Electronics Engineers, pp. 881-895, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022, New Orleans, United States, 19/06/22. https://doi.org/10.1109/CVPRW56347.2022.00103

NTIRE 2022 Spectral Demosaicing Challenge and Data Set. / Arad, Boaz; Timofte, Radu; Yahel, Rony et al.
Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. Institute of Electrical and Electronics Engineers, 2022. p. 881-895 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2022-June).

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

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AU - Timofte, Radu

AU - Yahel, Rony

AU - Morag, Nimrod

AU - Bernat, Amir

AU - Wu, Yaqi

AU - Wu, Xun

AU - Fan, Zhihao

AU - Xia, Chenjie

AU - Zhang, Feng

AU - Liu, Shuai

AU - Li, Yongqiang

AU - Feng, Chaoyu

AU - Lei, Lei

AU - Zhang, Mingwei

AU - Feng, Kai

AU - Zhang, Xun

AU - Yao, Jiaxin

AU - Zhao, Yongqiang

AU - Ma, Suina

AU - He, Fan

AU - Dong, Yangyang

AU - Yu, Shufang

AU - Qiu, Difa

AU - Liu, Jinhui

AU - Bi, Mengzhao

AU - Song, Beibei

AU - Sun, Wen Fang

AU - Zheng, Jiesi

AU - Zhao, Bowen

AU - Cao, Yanpeng

AU - Yang, Jiangxin

AU - Cao, Yanlong

AU - Kong, Xiangyu

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AU - Xue, Yuanyang

AU - Xie, Zheng

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AB - This paper presents the first challenge on demosaicing of natural spectral images for snapshot hyperspectral imaging systems (HIS) which utilize a multi-spectral filer array (MSFA), i.e., the recovery of whole-scene hyperspectral information from spatially sub-sampled hyperspectral information. This challenge expands the "ARAD_1K"data set to a first-of-its-kind large-scale data set for multispectral filter array demosaicing of natural scenes containing 1,000 images. Challenge participants were required to recover hyperspectral information from synthetically generated MSFA images simulating capture by a known calibrated snapshot mosaic hyperspectral camera. The challenge was attended by 157 teams, with 29 teams competing in the final testing phase, 7 of which provided detailed descriptions of their methodology which are included in this report. The performance of these submissions is reviewed and provided here as a gauge for the current state-of-the-art in multi-spectral filter array demosaicing of natural images.

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M3 - Conference contribution

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BT - Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022

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Arad B, Timofte R, Yahel R, Morag N, Bernat A, Wu Y et al. NTIRE 2022 Spectral Demosaicing Challenge and Data Set. In Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022. Institute of Electrical and Electronics Engineers. 2022. p. 881-895. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). doi: 10.1109/CVPRW56347.2022.00103

NTIRE 2022 Spectral Demosaicing Challenge and Data Set

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