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Analysis of Noisy Image Lossy Compression by BPG

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Integrated Computer Technologies in Mechanical Engineering - 2021 (ICTM 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 367))

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Abstract

Acquired remote sensing images are often large and distorted by noise. On the one hand, this leads to the need to compress them. On the other hand, the presence of noise should be taken into account at the image compression stage and while evaluating the compression efficiency.

Our work investigates the noise influence on the BPG method of image compression with losses supposing that data are distorted by additive Gaussian noise of different intensity. Within the framework of this study, the PSNR metric (peak signal to noise ratio, measured in dB) was chosen as a criterion for evaluating the quality of compression.

It is shown that three typical dependences of the metric calculated between compressed and noise-free images are possible. Depending on the situation, there are different recommendations for setting a parameter that controls compression (PCC). In particular, if there is an optimal operating point (OOP), the compression should be done in its neighborhood. The examples of dependences of PSNR on PCC for several test images are given. It is shown that existence of OOP and its position depend on image complexity and noise intensity.

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Authors and Affiliations

  1. National Aerospace University, 17 Chkalov Street, Kharkiv, 61070, Ukraine

    Victoria Naumenko, Vladimir Lukin & Sergey Krivenko

Authors
  1. Victoria Naumenko
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  2. Vladimir Lukin
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  3. Sergey Krivenko
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Corresponding author

Correspondence to Victoria Naumenko .

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Editors and Affiliations

  1. National Aerospace University – Kharki, Kharkov, Ukraine

    Mykola Nechyporuk

  2. Kharkov Aviation Institute, National Aerospace University, Kharkov, Ukraine

    Vladimir Pavlikov

  3. Kharkov Aviation Institute, National Aerospace University, Kharkov, Ukraine

    Dmitriy Kritskiy

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Naumenko, V., Lukin, V., Krivenko, S. (2022). Analysis of Noisy Image Lossy Compression by BPG. In: Nechyporuk, M., Pavlikov, V., Kritskiy, D. (eds) Integrated Computer Technologies in Mechanical Engineering - 2021. ICTM 2021. Lecture Notes in Networks and Systems, vol 367. Springer, Cham. https://doi.org/10.1007/978-3-030-94259-5_71

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  • DOI: https://doi.org/10.1007/978-3-030-94259-5_71

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-94258-8

  • Online ISBN: 978-3-030-94259-5

  • eBook Packages: EngineeringEngineering (R0)

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