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Research on Underwater Complex Scene SLAM Algorithm Based on Image Enhancement

Underwater images typically suffer from less explicit feature point information and more redundant information due to wild conditions. To solve these degradation problems, we propose the VINS-MONO algorithm to enhance the quality of the underwater image. Specifically, we first used the FAST feature...

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Detalles Bibliográficos
Autores principales: Wu, Renhan, Gao, Yuzhuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9656716/
https://www.ncbi.nlm.nih.gov/pubmed/36366215
http://dx.doi.org/10.3390/s22218517
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author Wu, Renhan
Gao, Yuzhuo
author_facet Wu, Renhan
Gao, Yuzhuo
author_sort Wu, Renhan
collection PubMed
description Underwater images typically suffer from less explicit feature point information and more redundant information due to wild conditions. To solve these degradation problems, we propose the VINS-MONO algorithm to enhance the quality of the underwater image. Specifically, we first used the FAST feature point extraction algorithm to improve the extraction speed. Then, the inverse optical flow method was used to improve the accuracy of feature extraction. At the same time, several kinds of residual information were extracted and marginalized, separately, in the marginalization part of the back-end, in order to improve the marginalization speed. Extensive experiments on underwater dataset HAUD-Dataset and public dataset EuRoC show that our approach is superior to the original VINS-MONO algorithm. In addition, the original algorithm optimizes the situation in which the feature point information is not obvious, and the redundant information is more complex in the underwater environment, which effectively improves the visual quality of the underwater image.
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spelling pubmed-96567162022-11-15 Research on Underwater Complex Scene SLAM Algorithm Based on Image Enhancement Wu, Renhan Gao, Yuzhuo Sensors (Basel) Article Underwater images typically suffer from less explicit feature point information and more redundant information due to wild conditions. To solve these degradation problems, we propose the VINS-MONO algorithm to enhance the quality of the underwater image. Specifically, we first used the FAST feature point extraction algorithm to improve the extraction speed. Then, the inverse optical flow method was used to improve the accuracy of feature extraction. At the same time, several kinds of residual information were extracted and marginalized, separately, in the marginalization part of the back-end, in order to improve the marginalization speed. Extensive experiments on underwater dataset HAUD-Dataset and public dataset EuRoC show that our approach is superior to the original VINS-MONO algorithm. In addition, the original algorithm optimizes the situation in which the feature point information is not obvious, and the redundant information is more complex in the underwater environment, which effectively improves the visual quality of the underwater image. MDPI 2022-11-05 /pmc/articles/PMC9656716/ /pubmed/36366215 http://dx.doi.org/10.3390/s22218517 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
Wu, Renhan
Gao, Yuzhuo
Research on Underwater Complex Scene SLAM Algorithm Based on Image Enhancement
title Research on Underwater Complex Scene SLAM Algorithm Based on Image Enhancement
title_full Research on Underwater Complex Scene SLAM Algorithm Based on Image Enhancement
title_fullStr Research on Underwater Complex Scene SLAM Algorithm Based on Image Enhancement
title_full_unstemmed Research on Underwater Complex Scene SLAM Algorithm Based on Image Enhancement
title_short Research on Underwater Complex Scene SLAM Algorithm Based on Image Enhancement
title_sort research on underwater complex scene slam algorithm based on image enhancement
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9656716/
https://www.ncbi.nlm.nih.gov/pubmed/36366215
http://dx.doi.org/10.3390/s22218517
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