Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44401
Title: Scalable architectures for real-time hyperspectral unmixing
Authors: Cervero, T. 
López, S. 
Callicó, G. M. 
López Feliciano, José Francisco 
Sarmiento, R. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: FPGA
Hyperspectral imaging
MVCA
Scalability
Issue Date: 2014
Publisher: 0026-2692
Journal: Microelectronics 
Abstract: 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. However, the downlink bandwidth is limited, and transmitting all data from the satellite to ground is a slow task that jeopardizes the use of this information for applications under real-time or near real-time constraints. This is the reason why most of the research activity is moving towards developing solutions which are able to process this data on-board, sending back to ground only relevant information. In this context, this paper presents three different FPGA-based architectures, implemented on an FPGA, which perform the Modified Vertex Component Analysis (MVCA) algorithm, as part of the hyperspectral linear unmixing processing chain. As a consequence, not only high performance but flexible and reusable designs have been designed. Moreover, final results demonstrate the influence of the implemented parallelization methodology over the final performance which motivates the system adaptivity through the scalability feature.
URI: http://hdl.handle.net/10553/44401
ISSN: 0026-2692
DOI: 10.1016/j.mejo.2014.03.010
Source: Microelectronics Journal[ISSN 0026-2692],v. 45, p. 1292-1303
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