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Advisor(s)
Abstract(s)
This paper presents a new parallel implementation of a previously hyperspectral coded aperture (HYCA) algorithm for compressive sensing on graphics processing units (GPUs). HYCA method combines the ideas of spectral unmixing and compressive sensing exploiting the high spatial correlation that can be observed in the data and the generally low number of endmembers needed in order to explain the data. The proposed implementation exploits the GPU architecture at low level, thus taking full advantage of the computational power of GPUs using shared memory and coalesced accesses to memory. The proposed algorithm is evaluated not only in terms of reconstruction error but also in terms of computational performance using two different GPU architectures by NVIDIA: GeForce GTX 590 and GeForce GTX TITAN. Experimental results using real data reveals signficant speedups up with regards to serial implementation.
Description
Keywords
Hyperspectral imaging Coded aperture Compressive sensing CS Graphics processing units GPUS
Citation
BERNABE, Sergio; [et al] - GPU implementation of a hyperspectral coded aperture algorithm for compressive sensing. IGARSS 2015 - IEEE International Geoscience and Remote Sensing Symposium. 2015. ISBN 978-1-4799-7929-5. Pp. 521-524
Publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.