Combining Exemplar-Based Approach and learning-Based Approach for Light Field Super-Resolution Using a Hybrid Imaging System

Haitian Zheng; Minghao Guo; Haoqian Wang; Yebin Liu; Lu Fang

doi:10.1109/ICCVW.2017.292

Combining Exemplar-Based Approach and learning-Based Approach for Light Field Super-Resolution Using a Hybrid Imaging System

Haitian Zheng, Minghao Guo, Haoqian Wang, Yebin Liu, Lu Fang

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

24 Citations (Scopus)

Abstract

We propose a new method to super-resolve images captured by a hybrid light field system that consists of a standard light field camera and a high-resolution standard camera. The high-resolution image is taken as a reference to help with super-resolving the low-resolution light field images. Our method combines an exemplar-based algorithm with the state of-the-art single image super-resolution approach and draws on the strengths of both. Both quantitative and qualitative experiments show that our proposed method substantially outperforms existing methods on standard light field datasets in the challenging large parallax setting.

Original language	English
Title of host publication	Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2481-2486
Number of pages	6
ISBN (Electronic)	9781538610343
DOIs	https://doi.org/10.1109/ICCVW.2017.292
Publication status	Published - 1 Jul 2017
Externally published	Yes
Event	16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017 - Venice, Italy Duration: 22 Oct 2017 → 29 Oct 2017

Publication series

Name	Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
Volume	2018-January

Conference

Conference	16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017
Country/Territory	Italy
City	Venice
Period	22/10/17 → 29/10/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Access to Document

10.1109/ICCVW.2017.292

Cite this

Zheng, H., Guo, M., Wang, H., Liu, Y., & Fang, L. (2017). Combining Exemplar-Based Approach and learning-Based Approach for Light Field Super-Resolution Using a Hybrid Imaging System. In Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017 (pp. 2481-2486). (Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCVW.2017.292

Zheng, Haitian ; Guo, Minghao ; Wang, Haoqian et al. / Combining Exemplar-Based Approach and learning-Based Approach for Light Field Super-Resolution Using a Hybrid Imaging System. Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 2481-2486 (Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017).

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title = "Combining Exemplar-Based Approach and learning-Based Approach for Light Field Super-Resolution Using a Hybrid Imaging System",

abstract = "We propose a new method to super-resolve images captured by a hybrid light field system that consists of a standard light field camera and a high-resolution standard camera. The high-resolution image is taken as a reference to help with super-resolving the low-resolution light field images. Our method combines an exemplar-based algorithm with the state of-the-art single image super-resolution approach and draws on the strengths of both. Both quantitative and qualitative experiments show that our proposed method substantially outperforms existing methods on standard light field datasets in the challenging large parallax setting.",

author = "Haitian Zheng and Minghao Guo and Haoqian Wang and Yebin Liu and Lu Fang",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017 ; Conference date: 22-10-2017 Through 29-10-2017",

year = "2017",

month = jul,

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doi = "10.1109/ICCVW.2017.292",

language = "English",

series = "Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017",

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Zheng, H, Guo, M, Wang, H, Liu, Y & Fang, L 2017, Combining Exemplar-Based Approach and learning-Based Approach for Light Field Super-Resolution Using a Hybrid Imaging System. in Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017. Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 2481-2486, 16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017, Venice, Italy, 22/10/17. https://doi.org/10.1109/ICCVW.2017.292

Combining Exemplar-Based Approach and learning-Based Approach for Light Field Super-Resolution Using a Hybrid Imaging System. / Zheng, Haitian; Guo, Minghao; Wang, Haoqian et al.
Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 2481-2486 (Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017; Vol. 2018-January).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

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AU - Fang, Lu

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AB - We propose a new method to super-resolve images captured by a hybrid light field system that consists of a standard light field camera and a high-resolution standard camera. The high-resolution image is taken as a reference to help with super-resolving the low-resolution light field images. Our method combines an exemplar-based algorithm with the state of-the-art single image super-resolution approach and draws on the strengths of both. Both quantitative and qualitative experiments show that our proposed method substantially outperforms existing methods on standard light field datasets in the challenging large parallax setting.

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M3 - Conference Paper published in a book

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Zheng H, Guo M, Wang H, Liu Y, Fang L. Combining Exemplar-Based Approach and learning-Based Approach for Light Field Super-Resolution Using a Hybrid Imaging System. In Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 2481-2486. (Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017). doi: 10.1109/ICCVW.2017.292

Combining Exemplar-Based Approach and learning-Based Approach for Light Field Super-Resolution Using a Hybrid Imaging System

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