Comparison of entropy coders for lossless grayscale image compression

In this paper, a comparison between three lossless entropy coders, interpolative coding combined with FELICS, arithmetic coding, and ANS coding, in terms of grayscale image compression is presented. The encoders were compared on sequences of values, produced by applying the JPEG-LS prediction to the...

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Veröffentlicht in:2023 International Conference on Data, Information and Computing Science (CDICS) S. 1 - 6
Hauptverfasser: Jeromel, Aljaz, Zalik, Borut
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 08.12.2023
Schlagworte:
Arithmetic
arithmetic coding
asymmetric numeral systems
Data compression
Entropy
Gray-scale
Image coding
image compression
interpolative coding
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Zusammenfassung:In this paper, a comparison between three lossless entropy coders, interpolative coding combined with FELICS, arithmetic coding, and ANS coding, in terms of grayscale image compression is presented. The encoders were compared on sequences of values, produced by applying the JPEG-LS prediction to the image, and calculating the differences between the actual values and predicted values. These values were then transformed to obtain positive numbers, which can be entropy coded by the three encoders. Experimental results show that the ANS coding is the most efficient of the three, closely followed by arithmetic coding, and interpolative coding combined with FELICS. The first two entropy coders, the ANS coder and arithmetic coder, also outperformed the PNG algorithm by a small margin.
DOI:10.1109/CDICS61497.2023.00011