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Extended Multi WLS Method for Lossless Image Coding

In this paper, the most efficient (from data compaction point of view) and current image lossless coding method is presented. Being computationally complex, the algorithm is still more time efficient than its main competitors. The presented cascaded method is based on the Weighted Least Square (WLS)...

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Autores principales: Ulacha, Grzegorz, Stasiński, Ryszard, Wernik, Cezary
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597162/
https://www.ncbi.nlm.nih.gov/pubmed/33286688
http://dx.doi.org/10.3390/e22090919
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author Ulacha, Grzegorz
Stasiński, Ryszard
Wernik, Cezary
author_facet Ulacha, Grzegorz
Stasiński, Ryszard
Wernik, Cezary
author_sort Ulacha, Grzegorz
collection PubMed
description In this paper, the most efficient (from data compaction point of view) and current image lossless coding method is presented. Being computationally complex, the algorithm is still more time efficient than its main competitors. The presented cascaded method is based on the Weighted Least Square (WLS) technique, with many improvements introduced, e.g., its main stage is followed by a two-step NLMS predictor ended with Context-Dependent Constant Component Removing. The prediction error is coded by a highly efficient binary context arithmetic coder. The performance of the new algorithm is compared to that of other coders for a set of widely used benchmark images.
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spelling pubmed-75971622020-11-09 Extended Multi WLS Method for Lossless Image Coding Ulacha, Grzegorz Stasiński, Ryszard Wernik, Cezary Entropy (Basel) Article In this paper, the most efficient (from data compaction point of view) and current image lossless coding method is presented. Being computationally complex, the algorithm is still more time efficient than its main competitors. The presented cascaded method is based on the Weighted Least Square (WLS) technique, with many improvements introduced, e.g., its main stage is followed by a two-step NLMS predictor ended with Context-Dependent Constant Component Removing. The prediction error is coded by a highly efficient binary context arithmetic coder. The performance of the new algorithm is compared to that of other coders for a set of widely used benchmark images. MDPI 2020-08-22 /pmc/articles/PMC7597162/ /pubmed/33286688 http://dx.doi.org/10.3390/e22090919 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ulacha, Grzegorz
Stasiński, Ryszard
Wernik, Cezary
Extended Multi WLS Method for Lossless Image Coding
title Extended Multi WLS Method for Lossless Image Coding
title_full Extended Multi WLS Method for Lossless Image Coding
title_fullStr Extended Multi WLS Method for Lossless Image Coding
title_full_unstemmed Extended Multi WLS Method for Lossless Image Coding
title_short Extended Multi WLS Method for Lossless Image Coding
title_sort extended multi wls method for lossless image coding
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597162/
https://www.ncbi.nlm.nih.gov/pubmed/33286688
http://dx.doi.org/10.3390/e22090919
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