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Colorization for Single Image Super Resolution

  • Shuaicheng Liu
  • Michael S. Brown
  • Seon Joo Kim
  • Yu-Wing Tai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6316)

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.

Keywords

Markov Random Field IEEE Conf Seed Point Color Assignment Super Resolution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Shuaicheng Liu
    • 1
  • Michael S. Brown
    • 1
  • Seon Joo Kim
    • 1
  • Yu-Wing Tai
    • 2
  1. 1.National University ofSingapore
  2. 2.Korea Advanced Institute of Science and Technology 

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