On Image based Enhancement for 3D Dense Reconstruction of Low Light Aerial Visual Inspected Environments
Proceedings of the 2019 Computer Vision Conference (CVC), Volume 2
Document identifier: oai:DiVA.org:ltu-76966
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10.1007/978-3-030-17798-0_23Keyword: Engineering and Technology,
Electrical Engineering, Electronic Engineering, Information Engineering,
Control Engineering,
Teknik och teknologier,
Elektroteknik och elektronik,
Reglerteknik,
Low-illumination image processing,
3D reconstruction,
MAVsPublication year: 2019Relevant Sustainable Development Goals (SDGs):
The SDG label(s) above have been assigned by OSDG.aiAbstract: Micro Aerial Vehicles (MAV)s have been distinguished, in the last decade, for their potential to inspect infrastructures in an active manner and provide critical information to the asset owners. Inspired by this trend, the mining industry is lately focusing to incorporate MAVs in their production cycles. Towards this direction, this article proposes a novel method to enhance 3D reconstruction of low-light environments, like underground tunnels, by using image processing. More specifically, the main idea is to enhance the low light resolution of the collected images, captured onboard an aerial platform, before inserting them to the reconstruction pipeline. The proposed method is based on the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm that limits the noise, while amplifies the contrast of the image. The overall efficiency and improvement achieved of the novel architecture has been extensively and successfully evaluated by utilizing data sets captured from real scale underground tunnels using a quadrotor.
Authors
Christoforos Kanellakis
Luleå tekniska universitet; Signaler och system
Other publications
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Petros Karvelis
Luleå tekniska universitet; Signaler och system
Other publications
>>
George Nikolakopoulos
Luleå tekniska universitet; Signaler och system
Other publications
>>
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identifier: oai:DiVA.org:ltu-76966
datestamp: 2021-04-19T12:54:20Z
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recordCreationDate: 2019-11-29
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10.1007/978-3-030-17798-0_23
2-s2.0-85065479828
titleInfo:
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lang: eng
title: On Image based Enhancement for 3D Dense Reconstruction of Low Light Aerial Visual Inspected Environments
abstract: Micro Aerial Vehicles (MAV)s have been distinguished in the last decade for their potential to inspect infrastructures in an active manner and provide critical information to the asset owners. Inspired by this trend the mining industry is lately focusing to incorporate MAVs in their production cycles. Towards this direction this article proposes a novel method to enhance 3D reconstruction of low-light environments like underground tunnels by using image processing. More specifically the main idea is to enhance the low light resolution of the collected images captured onboard an aerial platform before inserting them to the reconstruction pipeline. The proposed method is based on the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm that limits the noise while amplifies the contrast of the image. The overall efficiency and improvement achieved of the novel architecture has been extensively and successfully evaluated by utilizing data sets captured from real scale underground tunnels using a quadrotor.
subject:
@attributes:
lang: eng
authority: uka.se
topic:
Engineering and Technology
Electrical Engineering Electronic Engineering Information Engineering
Control Engineering
@attributes:
lang: swe
authority: uka.se
topic:
Teknik och teknologier
Elektroteknik och elektronik
Reglerteknik
@attributes:
lang: eng
topic: Low-illumination image processing
@attributes:
lang: eng
topic: 3D reconstruction
@attributes:
lang: eng
topic: MAVs
@attributes:
lang: swe
authority: ltu
topic: Reglerteknik
genre: Research subject
@attributes:
lang: eng
authority: ltu
topic: Control Engineering
genre: Research subject
language:
languageTerm: eng
genre:
conference/other
ref
note:
Published
3
ISBN för värdpublikation: 978-3-030-17797-3 978-3-030-17798-0
name:
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type: personal
authority: ltu
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Kanellakis
Christoforos
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roleTerm: aut
affiliation:
Luleå tekniska universitet
Signaler och system
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chrkan
0000-0001-8870-6718
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authority: ltu
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Karvelis
Petros
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Luleå tekniska universitet
Signaler och system
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petkar
0000-0002-0483-4868
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authority: ltu
namePart:
Nikolakopoulos
George
role:
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affiliation:
Luleå tekniska universitet
Signaler och system
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0000-0003-0126-1897
originInfo:
dateIssued: 2019
publisher: Springer
relatedItem:
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titleInfo:
title: Advances in Computer Vision
subTitle: Proceedings of the 2019 Computer Vision Conference (CVC) Volume 2
part:
extent:
start: 265
end: 279
@attributes:
type: series
titleInfo:
title: Advances in Intelligent Systems and Computing
partNumber: 944
identifier:
2194-5357
2194-5365
location:
url: http://ltu.diva-portal.org/smash/get/diva2:1374231/FULLTEXT01.pdf
accessCondition: gratis
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form: electronic
typeOfResource: text