Ordóñez Iglesias, ÁlvaroArgüello Pedreira, FranciscoBlanco Heras, Dora2018-12-052018-12-052017Ordonez, A., Arguello, F., & Heras, D. (2017). GPU Accelerated FFT-Based Registration of Hyperspectral Scenes. IEEE Journal Of Selected Topics In Applied Earth Observations And Remote Sensing, 10(11), 4869-4878. doi: 10.1109/jstars.2017.27340521939-1404http://hdl.handle.net/10347/17883Registration is a fundamental previous task in many applications of hyperspectrometry. Most of the algorithms developed are designed to work with RGB images and ignore the execution time. This paper presents a phase correlation algorithm on GPU to register two remote sensing hyperspectral images. The proposed algorithm is based on principal component analysis, multilayer fractional Fourier transform, combination of log-polar maps, and peak processing. It is fully developed in CUDA for NVIDIA GPUs. Different techniques such as the efficient use of the memory hierarchy, the use of CUDA libraries, and the maximization of the occupancy have been applied to reach the best performance on GPU. The algorithm is robust achieving speedups in GPU of up to 240.6×eng© 2017 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 worksCUDAFourier transformsGPUHyperspectral imagingImage registrationRemote sensingjournal article10.1109/JSTARS.2017.27340522151-1535open access