Congress 1662
  • Álvaro Ordóñez, Dora B. Heras, Francisco Argüello
  • 978-1-6654-2792-0
  • IGARSS2022_International Geoscience and Remote Sensing Symposium. Kuala Lumpur, Malaysia. 2022

Multi-GPU registration of high-resolution multispectral images using HSI-KAZE in a cluster system

Feature-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.
Keywords: multispectral, image registration, MPI, GPU, CUDA
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