RT Book,_Section
T1 Region-based multispectral image registration on heterogeneous computing platforms
A1 Castillo de la Rosa, Daniel del
A1 Ordóñez Iglesias, Álvaro
A1 Blanco Heras, Dora
A1 Argüello Pedreira, Francisco
K1 Multispectral
K1 image registration
K1 Heterogeneous computing
K1 GPU
K1 CUDA
AB Feature-based methods are widely used for the registration of remote sensing images because of their robustness to viewpoint, scale, and light changes. However, they are computationally demanding, especially when dealing with multi or hyperspectral images. Hyperspectral Maximally Stable Extremal Regions (HSI-MSER) is a hyperspectral remote sensing image registration method based on MSER for feature detection and Scale Invariant Feature Transform (SIFT) for feature description. This article presents a first approach to a parallel implementation of the HSI-MSER algorithm for the registration of multispectral images on a heterogeneous computing platform. The results of the registration capabilities under extreme scaling and rotating conditions show that the proposed parallel implementation obtains a speedup of 3.33 times compared to the sequential implementation making it suitable for applications with execution time constraints.
PB IEEE
SN 979-8-3503-6032-5
YR 2024
FD 2024-07-07
LK http://hdl.handle.net/10347/34881
UL http://hdl.handle.net/10347/34881
LA eng
NO Published in: IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
NO This a post-print of the article “Region-based multispectral image registration on heterogeneous computing platforms” published in the Proceedings of IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium.
NO This work was supported in part by grants TED2021-130367B-I00 and PID2022-141623NB-I00 funded by MCIN/AEI/10.13039/501100011033 and by European Union NextGenerationEU/PRTR. It was also supported 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], and by ERDF/EU.
DS Minerva
RD 28 abr 2026