RT Journal Article
T1 Using heterogeneous computing and edge computing to accelerate anomaly detection in remotely sensed multispectral images
A1 López Fandiño, Javier
A1 Blanco Heras, Dora
A1 Argüello Pedreira, Francisco
K1 Multispectral
K1 Anomaly detection
K1 Extinction profiles
K1 Heterogeneous computing
K1 Edge computing
AB This paper proposes a parallel algorithm exploiting heterogeneous computing and edge computing for anomaly detection (AD) in remotely sensed multispectral images. These images present high spatial resolution and are captured onboard unmanned aerial vehicles. AD is applied to identify patterns within an image that do not conform to the expected behavior. In this paper, the anomalies correspond to human-made constructions that trigger alarms related to the integrity of fluvial ecosystems. An algorithm based on extracting spatial information by using extinction profiles (EPs) and detecting anomalies by using the Reed–Xiaoli (RX) technique is proposed. The parallel algorithm presented in this paper is designed to be executed on multi-node heterogeneous computing platforms that include nodes with multi-core central processing units (CPUs) and graphics processing units (GPUs) and on a mobile embedded system consisting of a multi-core CPU and a GPU. The experiments are carried out on nodes of the FinisTerrae III supercomputer and, with the objective of analyzing its efficiency under different energy consumption scenarios, on a Jetson AGX Orin.
PB Springer
SN 0920-8542
YR 2024
FD 2024
LK http://hdl.handle.net/10347/33670
UL http://hdl.handle.net/10347/33670
LA eng
NO López-Fandiño, J., B. Heras, D. & Argüello, F. Using heterogeneous computing and edge computing to accelerate anomaly detection in remotely sensed multispectral images. J Supercomput (2024)
NO Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was supported in part by the Civil Program UAVs Initiative, promoted by the Xunta de Galicia and developed in partnership with the Babcock company to promote the use of unmanned technologies in civil services. It was also supported by grants PID2019–104834GB–I00, PID2022–141623NB-I00, and TED2021–130367B–I00 funded by MCIN/AEI/10.13039/501100011033 and by “European Union NextGenerationEU/PRTR.” We also have to acknowledge the support by Xunta de Galicia—Consellería de Cultura, Educación, Formación Profesional e Universidades [Centro de investigación de Galicia accreditation 2019–2022 ED431G-2019/04 and Reference Competitive Group accreditation, ED431C-2022/16], by Junta de Castilla y León [Project VA226P20 (PROPHET–II)], and by European Regional Development Fund (ERDF).
DS Minerva
RD 22 abr 2026