A learned pixel-by-pixel lossless image compression method with 59K parameters and parallel decoding

This paper considers lossless image compression and presents a learned compression system that can achieve state-of-the-art lossless compression performance but uses only 59K parameters, which is one or two order of magnitudes less than other learned systems proposed recently in the literature. The...

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Bibliographic Details
Published in:	Multimedia tools and applications Vol. 83; no. 8; pp. 22975 - 22993
Main Authors:	Gümüş, Sinem, Kamisli, Fatih
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.03.2024 Springer Nature B.V
Subjects:	Algorithms Computer Communication Networks Computer Science Data Structures and Information Theory Encoding-Decoding Entropy Image coding Image compression Methods Multimedia Multimedia Information Systems Neural networks Parameters Pixels Probability distribution Software Special Purpose and Application-Based Systems Wavelet transforms Image compression Entropy coding Gaussian mixture model Artificial neural networks
ISSN:	1573-7721, 1380-7501, 1573-7721
Online Access:	Get full text
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