Colorization for single image super resolution

Shuaicheng Liu; Michael S. Brown; Seon Joo Kim; Yu Wing Tai

doi:10.1007/978-3-642-15567-3_24

Colorization for single image super resolution

Shuaicheng Liu, Michael S. Brown, Seon Joo Kim, Yu Wing Tai

College of Computing

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

10 Citations (Scopus)

Abstract

This paper introduces a new procedure to handle color in single image super resolution (SR). Most existing SR techniques focus primarily on enforcing image priors or synthesizing image details; less attention is paid to the final color assignment. As a result, many existing SR techniques exhibit some form of color aberration in the final upsampled image. In this paper, we outline a procedure based on image colorization and back-projection to perform color assignment guided by the super-resolution luminance channel. We have found that our procedure produces better results both quantitatively and qualitatively than existing approaches. In addition, our approach is generic and can be incorporated into any existing SR techniques.

Original language	English
Title of host publication	Computer Vision, ECCV 2010 - 11th European Conference on Computer Vision, Proceedings
Publisher	Springer Verlag
Pages	323-336
Number of pages	14
Edition	PART 6
ISBN (Print)	3642155669, 9783642155666
DOIs	https://doi.org/10.1007/978-3-642-15567-3_24
Publication status	Published - 2010
Event	11th European Conference on Computer Vision, ECCV 2010 - Heraklion, Crete, Greece Duration: 2010 Sept 10 → 2010 Sept 11

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 6
Volume	6316 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th European Conference on Computer Vision, ECCV 2010
Country/Territory	Greece
City	Heraklion, Crete
Period	10/9/10 → 10/9/11

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-15567-3_24

Cite this

Liu, S., Brown, M. S., Kim, S. J., & Tai, Y. W. (2010). Colorization for single image super resolution. In Computer Vision, ECCV 2010 - 11th European Conference on Computer Vision, Proceedings (PART 6 ed., pp. 323-336). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6316 LNCS, No. PART 6). Springer Verlag. https://doi.org/10.1007/978-3-642-15567-3_24

Liu, Shuaicheng ; Brown, Michael S. ; Kim, Seon Joo et al. / Colorization for single image super resolution. Computer Vision, ECCV 2010 - 11th European Conference on Computer Vision, Proceedings. PART 6. ed. Springer Verlag, 2010. pp. 323-336 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 6).

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title = "Colorization for single image super resolution",

abstract = "This paper introduces a new procedure to handle color in single image super resolution (SR). Most existing SR techniques focus primarily on enforcing image priors or synthesizing image details; less attention is paid to the final color assignment. As a result, many existing SR techniques exhibit some form of color aberration in the final upsampled image. In this paper, we outline a procedure based on image colorization and back-projection to perform color assignment guided by the super-resolution luminance channel. We have found that our procedure produces better results both quantitatively and qualitatively than existing approaches. In addition, our approach is generic and can be incorporated into any existing SR techniques.",

author = "Shuaicheng Liu and Brown, {Michael S.} and Kim, {Seon Joo} and Tai, {Yu Wing}",

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Liu, S, Brown, MS, Kim, SJ & Tai, YW 2010, Colorization for single image super resolution. in Computer Vision, ECCV 2010 - 11th European Conference on Computer Vision, Proceedings. PART 6 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 6, vol. 6316 LNCS, Springer Verlag, pp. 323-336, 11th European Conference on Computer Vision, ECCV 2010, Heraklion, Crete, Greece, 10/9/10. https://doi.org/10.1007/978-3-642-15567-3_24

Colorization for single image super resolution. / Liu, Shuaicheng; Brown, Michael S.; Kim, Seon Joo et al.
Computer Vision, ECCV 2010 - 11th European Conference on Computer Vision, Proceedings. PART 6. ed. Springer Verlag, 2010. p. 323-336 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6316 LNCS, No. PART 6).

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

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AU - Liu, Shuaicheng

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N2 - This paper introduces a new procedure to handle color in single image super resolution (SR). Most existing SR techniques focus primarily on enforcing image priors or synthesizing image details; less attention is paid to the final color assignment. As a result, many existing SR techniques exhibit some form of color aberration in the final upsampled image. In this paper, we outline a procedure based on image colorization and back-projection to perform color assignment guided by the super-resolution luminance channel. We have found that our procedure produces better results both quantitatively and qualitatively than existing approaches. In addition, our approach is generic and can be incorporated into any existing SR techniques.

AB - This paper introduces a new procedure to handle color in single image super resolution (SR). Most existing SR techniques focus primarily on enforcing image priors or synthesizing image details; less attention is paid to the final color assignment. As a result, many existing SR techniques exhibit some form of color aberration in the final upsampled image. In this paper, we outline a procedure based on image colorization and back-projection to perform color assignment guided by the super-resolution luminance channel. We have found that our procedure produces better results both quantitatively and qualitatively than existing approaches. In addition, our approach is generic and can be incorporated into any existing SR techniques.

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SN - 9783642155666

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Liu S, Brown MS, Kim SJ, Tai YW. Colorization for single image super resolution. In Computer Vision, ECCV 2010 - 11th European Conference on Computer Vision, Proceedings. PART 6 ed. Springer Verlag. 2010. p. 323-336. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 6). doi: 10.1007/978-3-642-15567-3_24

Colorization for single image super resolution

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