Ordóñez Iglesias, ÁlvaroBlanco Heras, DoraArgüello Pedreira, Francisco2024-02-012024-02-012022http://hdl.handle.net/10347/32200This a post-print of the article “Multi-GPU registration of high-resolution multispectral images using HSI-KAZE in a cluster system” published in the Proceedings of IGARSS 2022 – 2022 IEEE International Geoscience and Remote Sensing Symposium. The published article is available on https://doi.org/ 10.1109/IGARSS46834.2022.9884717Feature-based registration methods have been demonstrated to be very effective to register multispectral images with large distortions or transformations despite the higher execution time that they require. In this paper, a first approach to a multi-node, multi-GPU implementation of the Hyperspectral KAZE (HSI-KAZE) method for co-registering bands and multispectral images is presented. Different multispectral datasets are distributed among the available nodes of a cluster using MPI and exploiting the parallel stream-based capabilities of the GPUs inside each node using CUDA.eng© 2022 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.MPIGPUCUDAMultispectralImage registration330406 Arquitectura de ordenadoresconference outputopen access