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Designing Multiplier-Less JPEG Luminance Quantisation Matrix

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Neural Information Processing (ICONIP 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1517))

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Abstract

A novel approach for generating a multiplier-less approximate JPEG quantisation matrix has been proposed in this paper. It is based on energy distribution of integer DCTs coefficients and rounding to integer power-of-two matrix. No multiplications required during the encode and decode stages using the combination between an integer DCT and the proposed rounded quantisation matrix. An arithmetic operation savings about 44.8% using the proposed quantisation matrix with integer DCT against the JPEG. The proposed quantisation matrix has been successfully evaluated against the conventional JPEG quantisation matrix for all different type test images. The experimental results reveal that JPEG compression scheme base on integer DCT combined with our proposed quantisation matrix can provide significant improvement in PSNR values compared with other quantisation matrices.

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Author information

Authors and Affiliations

  1. NDT Laboratory, Electronic Department, University of Jijel, Jijel, Algeria

    Nabila Brahimi

  2. NDT Laboratory, Automatic Department, University of Jijel, Jijel, Algeria

    Toufik Bouden

  3. LIASD Research Laboratory, University of Paris 8, Saint-Denis, France

    Larbi Boubchir

  4. L2EI Laboratory, Electronic Department, University of Jijel, Jijel, Algeria

    Tahar Brahimi

Authors
  1. Nabila Brahimi
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  2. Toufik Bouden
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  3. Larbi Boubchir
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  4. Tahar Brahimi
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Corresponding author

Correspondence to Larbi Boubchir .

Editor information

Editors and Affiliations

  1. Sampoerna University, Jakarta, Indonesia

    Teddy Mantoro

  2. Kyungpook National University, Daegu, Korea (Republic of)

    Minho Lee

  3. Sampoerna University, Jakarta, Indonesia

    Media Anugerah Ayu

  4. Murdoch University, Murdoch, WA, Australia

    Kok Wai Wong

  5. Universitas Indonesia, Depok, Indonesia

    Achmad Nizar Hidayanto

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Brahimi, N., Bouden, T., Boubchir, L., Brahimi, T. (2021). Designing Multiplier-Less JPEG Luminance Quantisation Matrix. In: Mantoro, T., Lee, M., Ayu, M.A., Wong, K.W., Hidayanto, A.N. (eds) Neural Information Processing. ICONIP 2021. Communications in Computer and Information Science, vol 1517. Springer, Cham. https://doi.org/10.1007/978-3-030-92310-5_79

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  • DOI: https://doi.org/10.1007/978-3-030-92310-5_79

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-92309-9

  • Online ISBN: 978-3-030-92310-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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