Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-15567-3_24
Title: Colorization for single image super resolution
Authors: Liu, S.
Brown, M.S. 
Kim, S.J. 
Tai, Y.-W.
Keywords: colorization
image upsampling
Super resolution
Issue Date: 2010
Source: Liu, S.,Brown, M.S.,Kim, S.J.,Tai, Y.-W. (2010). Colorization for single image super resolution. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6316 LNCS (PART 6) : 323-336. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-15567-3_24
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. © 2010 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/41472
ISBN: 3642155669
ISSN: 03029743
DOI: 10.1007/978-3-642-15567-3_24
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