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A DCT-JND Profile for Disorderly Concealment Effect

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Advances in Multimedia Information Processing – PCM 2018 (PCM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11166))

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Abstract

Just noticeable distortion (JND) refers to the smallest visibility threshold of the human visual system (HVS). The existing JND profiles always overestimate the visibility threshold in orderly region and underestimate that of the disorderly region. In order to obtain a more accurate DCT-JND profile, a novel block-level disorder metric is proposed and disorderly concealment effect is taken into account in the DCT-JND model. Specifically, an improved perceptive Local Binary Patterns (LBP) algorithm is proposed to evaluate the disorder of each block in this paper. Since the visual acuity is insensitive to the disorder stimulus, a disorderly concealment effect factor is defined as the function of block disorder and background disorder in this paper. The factor is used to adjust the conventional JND threshold appropriately. The experimental result shows that the proposed JND model tolerates much more distortion with the same perceptual quality compared with the existing JND profiles.

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Acknowledgement

This work was supported in part by National Natural Science Foundation of China (NSFC) (No. 61231010) and National High Technology Research and Development Program (No.2015AA015901).

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Authors and Affiliations

  1. School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China

    Hongkui Wang, Li Yu & Tiansong Li

  2. College of Information Engineering, China Jiliang University, Hangzhou, China

    Mengting Fan

  3. School of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China

    Haibing Yin

Authors
  1. Hongkui Wang
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  2. Li Yu
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  3. Tiansong Li
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  4. Mengting Fan
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  5. Haibing Yin
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Corresponding author

Correspondence to Li Yu .

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Editors and Affiliations

  1. Hefei University of Technology, Hefei, China

    Richang Hong

  2. National Chiao Tung University, Hsinchu, Taiwan

    Wen-Huang Cheng

  3. University of Tokyo, Tokyo, Japan

    Toshihiko Yamasaki

  4. Hefei University of Technology, Hefei, China

    Meng Wang

  5. City University of Hong Kong, Hong Kong, Hong Kong

    Chong-Wah Ngo

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Wang, H., Yu, L., Li, T., Fan, M., Yin, H. (2018). A DCT-JND Profile for Disorderly Concealment Effect. In: Hong, R., Cheng, WH., Yamasaki, T., Wang, M., Ngo, CW. (eds) Advances in Multimedia Information Processing – PCM 2018. PCM 2018. Lecture Notes in Computer Science(), vol 11166. Springer, Cham. https://doi.org/10.1007/978-3-030-00764-5_18

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  • DOI: https://doi.org/10.1007/978-3-030-00764-5_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00763-8

  • Online ISBN: 978-3-030-00764-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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