Castillo de la Rosa, Daniel delOrdóñez Iglesias, ÁlvaroBlanco Heras, DoraArgüello Pedreira, Francisco2024-09-262024-09-262024-07-07Published in: IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium979-8-3503-6032-5http://hdl.handle.net/10347/34881This 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.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.eng© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Multispectralimage registrationHeterogeneous computingGPUCUDA3304 Tecnología de los ordenadoresbook part10.1109/IGARSS53475.2024.106418842153-7003open access