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Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model

This paper has proposed a new thermal wave image sequence compression algorithm by combining double exponential decay fitting model and differential evolution algorithm. This study benchmarked fitting compression results and precision of the proposed method was benchmarked to that of the traditional...

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Detalles Bibliográficos
Autores principales: Zhang, Jin-Yu, Meng, Xiang-Bing, Xu, Wei, Zhang, Wei, Zhang, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3947782/
https://www.ncbi.nlm.nih.gov/pubmed/24696649
http://dx.doi.org/10.1155/2014/601506
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author Zhang, Jin-Yu
Meng, Xiang-Bing
Xu, Wei
Zhang, Wei
Zhang, Yong
author_facet Zhang, Jin-Yu
Meng, Xiang-Bing
Xu, Wei
Zhang, Wei
Zhang, Yong
author_sort Zhang, Jin-Yu
collection PubMed
description This paper has proposed a new thermal wave image sequence compression algorithm by combining double exponential decay fitting model and differential evolution algorithm. This study benchmarked fitting compression results and precision of the proposed method was benchmarked to that of the traditional methods via experiment; it investigated the fitting compression performance under the long time series and improved model and validated the algorithm by practical thermal image sequence compression and reconstruction. The results show that the proposed algorithm is a fast and highly precise infrared image data processing method.
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spelling pubmed-39477822014-04-02 Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model Zhang, Jin-Yu Meng, Xiang-Bing Xu, Wei Zhang, Wei Zhang, Yong ScientificWorldJournal Research Article This paper has proposed a new thermal wave image sequence compression algorithm by combining double exponential decay fitting model and differential evolution algorithm. This study benchmarked fitting compression results and precision of the proposed method was benchmarked to that of the traditional methods via experiment; it investigated the fitting compression performance under the long time series and improved model and validated the algorithm by practical thermal image sequence compression and reconstruction. The results show that the proposed algorithm is a fast and highly precise infrared image data processing method. Hindawi Publishing Corporation 2014-02-13 /pmc/articles/PMC3947782/ /pubmed/24696649 http://dx.doi.org/10.1155/2014/601506 Text en Copyright © 2014 Jin-Yu Zhang et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhang, Jin-Yu
Meng, Xiang-Bing
Xu, Wei
Zhang, Wei
Zhang, Yong
Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model
title Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model
title_full Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model
title_fullStr Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model
title_full_unstemmed Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model
title_short Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model
title_sort research on the compression algorithm of the infrared thermal image sequence based on differential evolution and double exponential decay model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3947782/
https://www.ncbi.nlm.nih.gov/pubmed/24696649
http://dx.doi.org/10.1155/2014/601506
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