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Histogram-Based Near-Lossless Data Hiding and Its Application to Image Compression

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Advances in Multimedia Information Processing -- PCM 2015 (PCM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9315))

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Abstract

This paper proposes a near-lossless data hiding (DH) method for images where the proposed method can improve the image compression efficiency. The proposed method firstly quantizes an image in accordance with a user-given maximum allowed error. This method, then, embeds data to the quantized image based on histogram shifting (HS). Even this method uses HS-based DH which requires to memorize the shifted bins for data extraction, the method, under some conditions, takes data out from the marked image by just applying re-quantization as least significant bitplane (LSB) substitution-based DH. So the proposed method is based on unification of HS- and LSB substitution-based DH. In the method, lossless compression of the marked image can achieve better compression efficiency than lossy compression of the original image. Experimental results show the effectiveness of the proposed method.

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Authors and Affiliations

  1. Department of Information and Commununication Systems, Tokyo Metropolitan University, 6–6 Asahigaoka, Hino-shi, Tokyo, 191–0065, Japan

    Masaaki Fujiyoshi & Hitoshi Kiya

Authors
  1. Masaaki Fujiyoshi
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  2. Hitoshi Kiya
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Corresponding author

Correspondence to Masaaki Fujiyoshi .

Editor information

Editors and Affiliations

  1. Gwangju Institute of Science and Technology, Gwangju, Korea (Republic of)

    Yo-Sung Ho

  2. Chinese Academy of Sciences, Institute of Automation, Beijing, China

    Jitao Sang

  3. KAIST, Daejeon, Korea (Republic of)

    Yong Man Ro

  4. KAIST, Daejeon, Korea (Republic of)

    Junmo Kim

  5. College of Computer Science, Zhejiang University, Hangzhou, China

    Fei Wu

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Fujiyoshi, M., Kiya, H. (2015). Histogram-Based Near-Lossless Data Hiding and Its Application to Image Compression. In: Ho, YS., Sang, J., Ro, Y., Kim, J., Wu, F. (eds) Advances in Multimedia Information Processing -- PCM 2015. PCM 2015. Lecture Notes in Computer Science(), vol 9315. Springer, Cham. https://doi.org/10.1007/978-3-319-24078-7_22

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  • DOI: https://doi.org/10.1007/978-3-319-24078-7_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24077-0

  • Online ISBN: 978-3-319-24078-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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