Distributed conditional arithmetic coding based on adaptive source-symbol purging

Jingjian Li; Jianhua Chen

doi:10.1117/12.3004037

11 October 2023 Distributed conditional arithmetic coding based on adaptive source-symbol purging

Jingjian Li, Jianhua Chen

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 1280049 (2023) https://doi.org/10.1117/12.3004037
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

Distributed Source Coding (DSC) is a coding architecture that utilizes the correlation among multiple sources to compress them. It can be achieved by using entropy coding instead of channel codes. We propose a new DSC scheme based on arithmetic coding named “Distributed Conditional Arithmetic Coding based on Adaptive Source-symbol Purging”. Since the encoder only encodes a part of symbols in the source sequence, more compression can be obtained. For the source sequence with memory, the stronger the correlation strength within the source, the more compression gain obtained by this scheme. Compared with traditional arithmetic coding-based DSC schemes, this scheme is very effective when coding source sequences with strong internal correlation and short block length.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jingjian Li and Jianhua Chen "Distributed conditional arithmetic coding based on adaptive source-symbol purging", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 1280049 (11 October 2023); https://doi.org/10.1117/12.3004037

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