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Nighttime Image Stitching Method Based on Image Decomposition Enhancement

Image stitching technology realizes alignment and fusion of a series of images with common pixel areas taken from different viewpoints of the same scene to produce a wide field of view panoramic image with natural structure. The night environment is one of the important scenes of human life, and the...

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Autores principales: Yan, Mengying, Qin, Danyang, Zhang, Gengxin, Tang, Huapeng, Ma, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10529531/
https://www.ncbi.nlm.nih.gov/pubmed/37761582
http://dx.doi.org/10.3390/e25091282
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author Yan, Mengying
Qin, Danyang
Zhang, Gengxin
Tang, Huapeng
Ma, Lin
author_facet Yan, Mengying
Qin, Danyang
Zhang, Gengxin
Tang, Huapeng
Ma, Lin
author_sort Yan, Mengying
collection PubMed
description Image stitching technology realizes alignment and fusion of a series of images with common pixel areas taken from different viewpoints of the same scene to produce a wide field of view panoramic image with natural structure. The night environment is one of the important scenes of human life, and the night image stitching technology has more urgent practical significance in the fields of security monitoring and intelligent driving at night. Due to the influence of artificial light sources at night, the brightness of the image is unevenly distributed and there are a large number of dark light areas, but often these dark light areas have rich structural information. The structural features hidden in the darkness are difficult to extract, resulting in ghosting and misalignment when stitching, which makes it difficult to meet the practical application requirements. Therefore, a nighttime image stitching method based on image decomposition enhancement is proposed to address the problem of insufficient line feature extraction in the stitching process of nighttime images. The proposed algorithm performs luminance enhancement on the structural layer, smoothes the nighttime image noise using a denoising algorithm on the texture layer, and finally complements the texture of the fused image by an edge enhancement algorithm. The experimental results show that the proposed algorithm improves the image quality in terms of information entropy, contrast, and noise suppression compared with other algorithms. Moreover, the proposed algorithm extracts the most line features from the processed nighttime images, which is more helpful for the stitching of nighttime images.
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spelling pubmed-105295312023-09-28 Nighttime Image Stitching Method Based on Image Decomposition Enhancement Yan, Mengying Qin, Danyang Zhang, Gengxin Tang, Huapeng Ma, Lin Entropy (Basel) Article Image stitching technology realizes alignment and fusion of a series of images with common pixel areas taken from different viewpoints of the same scene to produce a wide field of view panoramic image with natural structure. The night environment is one of the important scenes of human life, and the night image stitching technology has more urgent practical significance in the fields of security monitoring and intelligent driving at night. Due to the influence of artificial light sources at night, the brightness of the image is unevenly distributed and there are a large number of dark light areas, but often these dark light areas have rich structural information. The structural features hidden in the darkness are difficult to extract, resulting in ghosting and misalignment when stitching, which makes it difficult to meet the practical application requirements. Therefore, a nighttime image stitching method based on image decomposition enhancement is proposed to address the problem of insufficient line feature extraction in the stitching process of nighttime images. The proposed algorithm performs luminance enhancement on the structural layer, smoothes the nighttime image noise using a denoising algorithm on the texture layer, and finally complements the texture of the fused image by an edge enhancement algorithm. The experimental results show that the proposed algorithm improves the image quality in terms of information entropy, contrast, and noise suppression compared with other algorithms. Moreover, the proposed algorithm extracts the most line features from the processed nighttime images, which is more helpful for the stitching of nighttime images. MDPI 2023-08-31 /pmc/articles/PMC10529531/ /pubmed/37761582 http://dx.doi.org/10.3390/e25091282 Text en © 2023 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
Yan, Mengying
Qin, Danyang
Zhang, Gengxin
Tang, Huapeng
Ma, Lin
Nighttime Image Stitching Method Based on Image Decomposition Enhancement
title Nighttime Image Stitching Method Based on Image Decomposition Enhancement
title_full Nighttime Image Stitching Method Based on Image Decomposition Enhancement
title_fullStr Nighttime Image Stitching Method Based on Image Decomposition Enhancement
title_full_unstemmed Nighttime Image Stitching Method Based on Image Decomposition Enhancement
title_short Nighttime Image Stitching Method Based on Image Decomposition Enhancement
title_sort nighttime image stitching method based on image decomposition enhancement
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10529531/
https://www.ncbi.nlm.nih.gov/pubmed/37761582
http://dx.doi.org/10.3390/e25091282
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AT tanghuapeng nighttimeimagestitchingmethodbasedonimagedecompositionenhancement
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