Video compression by chroma prediction using semantic communications

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Samarathunga, Prabhath and Ganearachchi, Yasith and Fernando, Anil; (2023) Video compression by chroma prediction using semantic communications. In: IEEE 42nd International Conference on Consumer Electronics. IEEE, USA. (In Press)

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Abstract

Conventional video coding is evolving to meet unprecedented consumer device requirements, but the statistical signal processing based approach may find limitations in handling new media contents. Deep neural network and semantic communication based video compression systems show potential to be used as video encoders and decoders, but reaching the rate distortion performance of state-of-the-art conventional video coding systems remains to be achieved. A novel video compression system by predicting the chroma components of video using the semantically encoded luma component and reference intra-coded frames is proposed and tested against high efficiency video coding (HEVC) for bit rate comparison and rate-distortion performance evaluation. The proposed system demonstrated 18% to 30% saving of bit rate for high and medium motion videos without significant reductions of rate-distortion with the saving increasing with higher group of picture sizes, but low motion videos only demonstrated negligible savings.

ORCID iDs

Samarathunga, Prabhath, Ganearachchi, Yasith ORCID logoORCID: https://orcid.org/0000-0002-8337-3739 and Fernando, Anil;
  • Item type:Book Section
    ID code:88130
    Dates:
    Date
    Event
    4 November 2023
    Published
    4 November 2023
    Accepted
    Notes:© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Science > Mathematics > Electronic computers. Computer science
    Department:Faculty of Science > Computer and Information Sciences
    Depositing user: Pure Administrator
    Date deposited:08 Feb 2024 12:06
    Last modified:17 Dec 2024 01:06
    URI:https://strathprints.strath.ac.uk/id/eprint/88130
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