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dc.contributor.authorVerstockt, Steven
dc.contributor.authorJiménez González, Daniel
dc.contributor.authorRios Rubiras, Oriol
dc.contributor.authorQueen, Lloyd
dc.contributor.authorPastor Ferrer, Elsa
dc.contributor.authorPlanas Cuchi, Eulàlia
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Química
dc.date.accessioned2021-03-05T13:59:20Z
dc.date.issued2021
dc.identifier.citationVerstockt, S. [et al.]. Thermal infrared video stabilization for aerial monitoring of active wildfires. "IEEE journal of selected topics in applied earth observations and remote sensing", Vol.14, 2021, pp. 2817-2832
dc.identifier.issn1939-1404
dc.identifier.urihttp://hdl.handle.net/2117/341046
dc.description.abstractMeasuring wildland fire behaviour is essential forfire science and fire management. Aerial thermal infrared (TIR)imaging provides outstanding opportunities to acquire suchinformation remotely. Variables such as fire rate of spread(ROS), fire radiative power (FRP) and fire line intensity maybe measured explicitly both in time and space, providing thenecessary data to study the response of fire behaviour to weather,vegetation, topography and firefighting efforts. However, raw TIRimagery acquired by Unmanned Aerial Vehicles (UAVs) requiresstabilization and georeferencing before any other processing canbe performed. Aerial video usually suffers from instabilitiesproduced by sensor movement. This problem is especially acutenear an active wildfire due to fire-generated turbulence. Fur-thermore, the nature of fire TIR video presents some specificchallenges that hinder robust inter-frame registration. There-fore, this paper presents a software-based video stabilizationalgorithm specifically designed for thermal infrared imageryof forest fires. After a comparative analysis of existing imageregistration algorithms, the KAZE feature-matching method wasselected and accompanied by pre- and post-processing modules.These included foreground histogram equalization and a multi-reference framework designed to increase the algorithm’s robust-ness in the presence of missing or faulty frames. Performanceof the proposed algorithm was validated in a total of ninevideo sequences acquired during field fire experiments. Theproposed algorithm yielded a registration accuracy between 10and 1000 times higher than other tested methods, returned 10xmore meaningful feature matches and proved robust in thepresence of faulty video frames. The ability to automaticallycancel camera movement for every frame in a video sequencesolves a key limitation in data processing pipelines and opensthe door to a number of systematic fire behaviour experimentalanalyses. Moreover, a completely automated process supports thedevelopment of decision support tools that can operate in realtime during an emergency.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria química
dc.subject.otherFire behaviour
dc.subject.otherImage registration
dc.subject.otherKAZE
dc.subject.otherRemote sensing
dc.subject.otherUAS
dc.subject.otherVideo stabilization
dc.subject.otherWildland fire
dc.titleThermal infrared video stabilization for aerial monitoring of active wildfires
dc.typeArticle
dc.subject.lemacIncendis -- Avaluació
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.contributor.groupUniversitat Politècnica de Catalunya. CERTEC - Centre d'Estudis del Risc Tecnològic
dc.identifier.doi10.1109/JSTARS.2021.3059054
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
local.identifier.drac30687043
dc.description.versionPostprint (author's final draft)
dc.date.lift2023-03-01
local.citation.authorVerstockt, S.; Jimenez, D.; Rios, O.; Queen, L.; Pastor, E.; Planas, E.
local.citation.publicationNameIEEE journal of selected topics in applied earth observations and remote sensing


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