Lossless Image Coding Using Non-MMSE Algorithms to Calculate Linear Prediction Coefficients

This paper presents a lossless image compression method with a fast decoding time and flexible adjustment of coder parameters affecting its implementation complexity. A comparison of several approaches for computing non-MMSE prediction coefficients with different levels of complexity was made. The d...

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Main Authors: Grzegorz Ulacha, Mirosław Łazoryszczak
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/25/1/156
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author Grzegorz Ulacha
Mirosław Łazoryszczak
author_facet Grzegorz Ulacha
Mirosław Łazoryszczak
author_sort Grzegorz Ulacha
collection DOAJ
description This paper presents a lossless image compression method with a fast decoding time and flexible adjustment of coder parameters affecting its implementation complexity. A comparison of several approaches for computing non-MMSE prediction coefficients with different levels of complexity was made. The data modeling stage of the proposed codec was based on linear (calculated by the non-MMSE method) and non-linear (complemented by a context-dependent constant component removal block) predictions. Prediction error coding uses a two-stage compression: an adaptive Golomb code and a binary arithmetic code. The proposed solution results in 30% shorter decoding times and a lower bit average than competing solutions (by 7.9% relative to the popular JPEG-LS codec).
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spelling doaj.art-dfa1c0d4e40946a0a634dbee029aab4d2023-11-30T22:09:29ZengMDPI AGEntropy1099-43002023-01-0125115610.3390/e25010156Lossless Image Coding Using Non-MMSE Algorithms to Calculate Linear Prediction CoefficientsGrzegorz Ulacha0Mirosław Łazoryszczak1Faculty of Computer Science and Information Technology, West Pomeranian University of Technology in Szczecin, Ul. Żołnierska 49, 71-210 Szczecin, PolandFaculty of Computer Science and Information Technology, West Pomeranian University of Technology in Szczecin, Ul. Żołnierska 49, 71-210 Szczecin, PolandThis paper presents a lossless image compression method with a fast decoding time and flexible adjustment of coder parameters affecting its implementation complexity. A comparison of several approaches for computing non-MMSE prediction coefficients with different levels of complexity was made. The data modeling stage of the proposed codec was based on linear (calculated by the non-MMSE method) and non-linear (complemented by a context-dependent constant component removal block) predictions. Prediction error coding uses a two-stage compression: an adaptive Golomb code and a binary arithmetic code. The proposed solution results in 30% shorter decoding times and a lower bit average than competing solutions (by 7.9% relative to the popular JPEG-LS codec).https://www.mdpi.com/1099-4300/25/1/156lossless image codinglinear predictionentropy coding
spellingShingle Grzegorz Ulacha
Mirosław Łazoryszczak
Lossless Image Coding Using Non-MMSE Algorithms to Calculate Linear Prediction Coefficients
Entropy
lossless image coding
linear prediction
entropy coding
title Lossless Image Coding Using Non-MMSE Algorithms to Calculate Linear Prediction Coefficients
title_full Lossless Image Coding Using Non-MMSE Algorithms to Calculate Linear Prediction Coefficients
title_fullStr Lossless Image Coding Using Non-MMSE Algorithms to Calculate Linear Prediction Coefficients
title_full_unstemmed Lossless Image Coding Using Non-MMSE Algorithms to Calculate Linear Prediction Coefficients
title_short Lossless Image Coding Using Non-MMSE Algorithms to Calculate Linear Prediction Coefficients
title_sort lossless image coding using non mmse algorithms to calculate linear prediction coefficients
topic lossless image coding
linear prediction
entropy coding
url https://www.mdpi.com/1099-4300/25/1/156
work_keys_str_mv AT grzegorzulacha losslessimagecodingusingnonmmsealgorithmstocalculatelinearpredictioncoefficients
AT mirosławłazoryszczak losslessimagecodingusingnonmmsealgorithmstocalculatelinearpredictioncoefficients