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Tone Image Classification and Weighted Learning for Visible and NIR Image Fusion

In this paper, to improve the slow processing speed of the rule-based visible and NIR (near-infrared) image synthesis method, we present a fast image fusion method using DenseFuse, one of the CNN (convolutional neural network)-based image synthesis methods. The proposed method applies a raster scan...

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Detalles Bibliográficos
Autores principales: Im, Chan-Gi, Son, Dong-Min, Kwon, Hyuk-Ju, Lee, Sung-Hak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9601651/
https://www.ncbi.nlm.nih.gov/pubmed/37420457
http://dx.doi.org/10.3390/e24101435
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author Im, Chan-Gi
Son, Dong-Min
Kwon, Hyuk-Ju
Lee, Sung-Hak
author_facet Im, Chan-Gi
Son, Dong-Min
Kwon, Hyuk-Ju
Lee, Sung-Hak
author_sort Im, Chan-Gi
collection PubMed
description In this paper, to improve the slow processing speed of the rule-based visible and NIR (near-infrared) image synthesis method, we present a fast image fusion method using DenseFuse, one of the CNN (convolutional neural network)-based image synthesis methods. The proposed method applies a raster scan algorithm to secure visible and NIR datasets for effective learning and presents a dataset classification method using luminance and variance. Additionally, in this paper, a method for synthesizing a feature map in a fusion layer is presented and compared with the method for synthesizing a feature map in other fusion layers. The proposed method learns the superior image quality of the rule-based image synthesis method and shows a clear synthesized image with better visibility than other existing learning-based image synthesis methods. Compared with the rule-based image synthesis method used as the target image, the proposed method has an advantage in processing speed by reducing the processing time to three times or more.
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spelling pubmed-96016512022-10-27 Tone Image Classification and Weighted Learning for Visible and NIR Image Fusion Im, Chan-Gi Son, Dong-Min Kwon, Hyuk-Ju Lee, Sung-Hak Entropy (Basel) Article In this paper, to improve the slow processing speed of the rule-based visible and NIR (near-infrared) image synthesis method, we present a fast image fusion method using DenseFuse, one of the CNN (convolutional neural network)-based image synthesis methods. The proposed method applies a raster scan algorithm to secure visible and NIR datasets for effective learning and presents a dataset classification method using luminance and variance. Additionally, in this paper, a method for synthesizing a feature map in a fusion layer is presented and compared with the method for synthesizing a feature map in other fusion layers. The proposed method learns the superior image quality of the rule-based image synthesis method and shows a clear synthesized image with better visibility than other existing learning-based image synthesis methods. Compared with the rule-based image synthesis method used as the target image, the proposed method has an advantage in processing speed by reducing the processing time to three times or more. MDPI 2022-10-09 /pmc/articles/PMC9601651/ /pubmed/37420457 http://dx.doi.org/10.3390/e24101435 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Im, Chan-Gi
Son, Dong-Min
Kwon, Hyuk-Ju
Lee, Sung-Hak
Tone Image Classification and Weighted Learning for Visible and NIR Image Fusion
title Tone Image Classification and Weighted Learning for Visible and NIR Image Fusion
title_full Tone Image Classification and Weighted Learning for Visible and NIR Image Fusion
title_fullStr Tone Image Classification and Weighted Learning for Visible and NIR Image Fusion
title_full_unstemmed Tone Image Classification and Weighted Learning for Visible and NIR Image Fusion
title_short Tone Image Classification and Weighted Learning for Visible and NIR Image Fusion
title_sort tone image classification and weighted learning for visible and nir image fusion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9601651/
https://www.ncbi.nlm.nih.gov/pubmed/37420457
http://dx.doi.org/10.3390/e24101435
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