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Automatic Color Image Enhancement Using Double Channels

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Advances in Multimedia Information Processing - PCM 2016 (PCM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9917))

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Abstract

Digital cameras have been widely used in taking photos. However, some photos lack details and need enhancement. Many existing image enhancement algorithms are patch-based and the patch size is always fixed. Users have to tune the parameter to obtain the appropriate enhancement. In this paper, we propose an automatic consumer image enhancement method based on double channels and adaptive patch size. The method enhances an image pixel by pixel using both dark and bright channels. The local patch size is selected automatically by contrast feature. Our proposed method is able to automatically enhance both foggy and under-exposed consumer images without any user interaction. Experiment results show that our method can provide a significant improvement to existing patch-based image enhancement algorithms.

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Acknowledgments

This research was supported by Zhejiang Provincial Natural Science Foundation of China under Grant No. LQ14F020003 and in part by the National Natural Science Foundation of China (61572428, U1509206).

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Authors and Affiliations

  1. Zhejiang International Studies University, Hangzhou, 310012, People’s Republic of China

    Na Li

  2. Zhejiang University, Hangzhou, 310027, People’s Republic of China

    Zhao Liu, Jie Lei, Mingli Song & Jiajun Bu

Authors
  1. Na Li
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  2. Zhao Liu
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  3. Jie Lei
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  4. Mingli Song
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  5. Jiajun Bu
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Corresponding author

Correspondence to Na Li .

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Editors and Affiliations

  1. Zhengzhou University, Zhengzhou, China

    Enqing Chen

  2. Jiaotong University, Xi’an, China

    Yihong Gong

  3. Zhengzhou University, Zhengzhou, China

    Yun Tie

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Li, N., Liu, Z., Lei, J., Song, M., Bu, J. (2016). Automatic Color Image Enhancement Using Double Channels. In: Chen, E., Gong, Y., Tie, Y. (eds) Advances in Multimedia Information Processing - PCM 2016. PCM 2016. Lecture Notes in Computer Science(), vol 9917. Springer, Cham. https://doi.org/10.1007/978-3-319-48896-7_8

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  • DOI: https://doi.org/10.1007/978-3-319-48896-7_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48895-0

  • Online ISBN: 978-3-319-48896-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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