Reducing the Complexity of CCSDS 123.0-B-2 Hybrid Entropy Coding

This letter addresses the complexity of the hybrid entropy encoder in the Consultative Committee for Space Data Systems (CCSDS) 123.0-B-2 compression standard and proposes an improved encoding method. By eliminating the refresh table from the original standard, simplifying the encoding process, and using forward decoding, the proposed method significantly reduces encoding complexity and enhances error resilience. The improved algorithm is particularly optimized for handling high-resolution accumulators, reducing bitstream redundancy while maintaining compression performance comparable to the original standard. Experimental results demonstrate that the new algorithm excels in both lossless and lossy compression, achieving higher compression ratios (CRs) and better image quality, making it well-suited for satellite platform applications with bandwidth and power consumption constraints.

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Publication Details

Journal
IEEE Geoscience and Remote Sensing Letters
Published
2024-12-13
DOI
https://doi.org/10.1109/lgrs.2024.3517146
Primary Topic
Advanced Data Compression Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Reducing the Complexity of CCSDS 123.0-B-2 Hybrid Entropy Coding

Chengpeng Song, Longsheng Zhang, Lili Zhang, Peng Zhang
IEEE Geoscience and Remote Sensing Letters
Advanced Data Compression Techniques
article

Reducing the Complexity of CCSDS 123.0-B-2 Hybrid Entropy Coding

Chengpeng Song, Longsheng Zhang, Lili Zhang, Peng Zhang
article en

Abstract

This letter addresses the complexity of the hybrid entropy encoder in the Consultative Committee for Space Data Systems (CCSDS) 123.0-B-2 compression standard and proposes an improved encoding method. By eliminating the refresh table from the original standard, simplifying the encoding process, and using forward decoding, the proposed method significantly reduces encoding complexity and enhances error resilience. The improved algorithm is particularly optimized for handling high-resolution accumulators, reducing bitstream redundancy while maintaining compression performance comparable to the original standard. Experimental results demonstrate that the new algorithm excels in both lossless and lossy compression, achieving higher compression ratios (CRs) and better image quality, making it well-suited for satellite platform applications with bandwidth and power consumption constraints.

IEEE Geoscience and Remote Sensing LettersVol. 22
Shenyang Aerospace University (CN)
Affordable and clean energy
Openalex Percentile: Top 77%
Advanced Data Compression Techniques
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