Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/44400
Título: A Scalable and Dynamically Reconfigurable FPGA-Based Embedded System for Real-Time Hyperspectral Unmixing
Autores/as: Cervero, Teresa G. 
Caba, Julián
López, Sebastián 
Dondo, Julio Daniel
Sarmiento, Roberto 
Rincón, Fernando
López, Juan 
Clasificación UNESCO: 3307 Tecnología electrónica
Palabras clave: Vectors , Hyperspectral imaging , Field programmable gate arrays , Hardware , Scalability , Algorithm design and analysis , Dynamic reconfiguration , Field-Programmable Gate Array (FPGA) , hyperspectral images , linear unmixing , Modified Vertex Component Analysis (MVCA)
Fecha de publicación: 2015
Editor/a: 1939-1404
Publicación seriada: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 
Conferencia: 6th Workshop on Hyperspectral Image and Signal Processing - Evolution in Remote Sensing (WHISPERS) 
Resumen: Earth observation hyperspectral imaging instruments capture and collect hundreds of different wavelength data corresponding to the same surface. As a result, tons of information must be stored, processed, and transmitted to ground by means of a combination of time-consuming processes. However, one of the requirements of paramount importance when dealing with applications that demand swift responses is the ability to achieve real-time. In this sense, the authors present a flexible and adaptable Field-Programmable Gate Array (FPGA)-based solution for extracting the endmembers of a hyperspectral image according to the Modified Vertex Component Analysis (MVCA) algorithm. The proposed approach is capable of adapting its parallelization execution by scaling the execution in hardware. Thus, the solution uses the dynamic and partial reconfiguration property of FPGAs in order to exploit and vary the level of parallelism at run-time. In order to validate the convenience of using this kind of solutions, the performance of our proposal has been assessed with a set of synthetic images as well as with the well-known Cuprite hyperspectral image. The achieved results demonstrate that the proposed system might be dynamically scaled without significantly affecting total execution times, being able to extract the endmembers of the Cuprite dataset in real-time.
URI: http://hdl.handle.net/10553/44400
ISSN: 1939-1404
DOI: 10.1109/JSTARS.2014.2347075
Fuente: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing[ISSN 1939-1404],v. 8 (6897942), p. 2894-2911
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