Images analysis for automatic volcano visibility estimation

In this paper, a method for estimating the volcano visibility in the images is presented. This method includes algorithms for analyzing parametric edges of objects under observation and frequency characteristics of the images. Procedures for constructing parametric edges of a volcano and their compa...

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Published in:Computer Optics
Main Authors: Alexandr Kamaev, Igor Urmanov, Aleksei Sorokin, Dmitry Karmanov, Sergey Korolev
Format: Article in Journal/Newspaper
Language:English
Russian
Published: Samara National Research University 2018
Subjects:
Online Access:https://doi.org/10.18287/2412-6179-2018-42-1-128-140
https://doaj.org/article/1829493f0fd946a7842c31bcaafa1660
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spelling ftdoajarticles:oai:doaj.org/article:1829493f0fd946a7842c31bcaafa1660 2023-05-15T16:59:21+02:00 Images analysis for automatic volcano visibility estimation Alexandr Kamaev Igor Urmanov Aleksei Sorokin Dmitry Karmanov Sergey Korolev 2018-02-01T00:00:00Z https://doi.org/10.18287/2412-6179-2018-42-1-128-140 https://doaj.org/article/1829493f0fd946a7842c31bcaafa1660 EN RU eng rus Samara National Research University http://computeroptics.smr.ru/KO/PDF/KO42-1/420116.pdf https://doaj.org/toc/0134-2452 https://doaj.org/toc/2412-6179 doi:10.18287/2412-6179-2018-42-1-128-140 0134-2452 2412-6179 https://doaj.org/article/1829493f0fd946a7842c31bcaafa1660 Компьютерная оптика, Vol 42, Iss 1, Pp 128-140 (2018) image analysis algorithms edge detection parametric edges volcano edge matching video surveillance visibility analysis Information theory Q350-390 Optics. Light QC350-467 article 2018 ftdoajarticles https://doi.org/10.18287/2412-6179-2018-42-1-128-140 2022-12-31T09:38:14Z In this paper, a method for estimating the volcano visibility in the images is presented. This method includes algorithms for analyzing parametric edges of objects under observation and frequency characteristics of the images. Procedures for constructing parametric edges of a volcano and their comparison are considered. An algorithm is proposed for identifying the most persistent edges for a group of several reference images. The visibility of a volcano is estimated by comparing these edges to those of the image under analysis. The visibility estimation is maximized with respect to a planar shift and rotation of the camera to eliminate their influence on the estimation. If the image quality is low, making it hardly suitable for further visibility analysis, the estimation is corrected using an algorithm for analyzing the image frequency response represented as a vector of the octave frequency contribution to the image luminance. A comparison of the reference frequency characteristics and the characteristics of the analyzed image allows us to estimate the contribution of different frequencies to the formation of volcano images. We discuss results of the verification of the proposed algorithms performed using the archive of a video observation system of Kamchatka volcanoes. The estimates obtained corroborate the effectiveness of the proposed methods, enabling the non-informative imagery to be automatically filtered off while monitoring the volcanic activity. Article in Journal/Newspaper Kamchatka Directory of Open Access Journals: DOAJ Articles Computer Optics 42 1 128 140
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
Russian
topic image analysis
algorithms
edge detection
parametric edges
volcano
edge matching
video surveillance
visibility analysis
Information theory
Q350-390
Optics. Light
QC350-467
spellingShingle image analysis
algorithms
edge detection
parametric edges
volcano
edge matching
video surveillance
visibility analysis
Information theory
Q350-390
Optics. Light
QC350-467
Alexandr Kamaev
Igor Urmanov
Aleksei Sorokin
Dmitry Karmanov
Sergey Korolev
Images analysis for automatic volcano visibility estimation
topic_facet image analysis
algorithms
edge detection
parametric edges
volcano
edge matching
video surveillance
visibility analysis
Information theory
Q350-390
Optics. Light
QC350-467
description In this paper, a method for estimating the volcano visibility in the images is presented. This method includes algorithms for analyzing parametric edges of objects under observation and frequency characteristics of the images. Procedures for constructing parametric edges of a volcano and their comparison are considered. An algorithm is proposed for identifying the most persistent edges for a group of several reference images. The visibility of a volcano is estimated by comparing these edges to those of the image under analysis. The visibility estimation is maximized with respect to a planar shift and rotation of the camera to eliminate their influence on the estimation. If the image quality is low, making it hardly suitable for further visibility analysis, the estimation is corrected using an algorithm for analyzing the image frequency response represented as a vector of the octave frequency contribution to the image luminance. A comparison of the reference frequency characteristics and the characteristics of the analyzed image allows us to estimate the contribution of different frequencies to the formation of volcano images. We discuss results of the verification of the proposed algorithms performed using the archive of a video observation system of Kamchatka volcanoes. The estimates obtained corroborate the effectiveness of the proposed methods, enabling the non-informative imagery to be automatically filtered off while monitoring the volcanic activity.
format Article in Journal/Newspaper
author Alexandr Kamaev
Igor Urmanov
Aleksei Sorokin
Dmitry Karmanov
Sergey Korolev
author_facet Alexandr Kamaev
Igor Urmanov
Aleksei Sorokin
Dmitry Karmanov
Sergey Korolev
author_sort Alexandr Kamaev
title Images analysis for automatic volcano visibility estimation
title_short Images analysis for automatic volcano visibility estimation
title_full Images analysis for automatic volcano visibility estimation
title_fullStr Images analysis for automatic volcano visibility estimation
title_full_unstemmed Images analysis for automatic volcano visibility estimation
title_sort images analysis for automatic volcano visibility estimation
publisher Samara National Research University
publishDate 2018
url https://doi.org/10.18287/2412-6179-2018-42-1-128-140
https://doaj.org/article/1829493f0fd946a7842c31bcaafa1660
genre Kamchatka
genre_facet Kamchatka
op_source Компьютерная оптика, Vol 42, Iss 1, Pp 128-140 (2018)
op_relation http://computeroptics.smr.ru/KO/PDF/KO42-1/420116.pdf
https://doaj.org/toc/0134-2452
https://doaj.org/toc/2412-6179
doi:10.18287/2412-6179-2018-42-1-128-140
0134-2452
2412-6179
https://doaj.org/article/1829493f0fd946a7842c31bcaafa1660
op_doi https://doi.org/10.18287/2412-6179-2018-42-1-128-140
container_title Computer Optics
container_volume 42
container_issue 1
container_start_page 128
op_container_end_page 140
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