Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44986
Title: FPGA implementation to estimate the number of endmembers in hyperspectral images
Authors: Gonzalez, Carlos 
Mozos, Daniel 
López, Sebastián 
Sarmiento, Roberto 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Hyperspectral imaging
Estimation
Noise
Field programmable gate arrays
Covariance matrices
Correlation
Issue Date: 2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Journal: International Conference on Field Programmable Logic and Applications 
Conference: 25th International Conference on Field Programmable Logic and Applications, FPL 2015 
Abstract: Spectral unmixing is an important task for remotely sensed hyperspectral data exploitation. It amounts the identification of pure spectral signatures (endmembers) in the data, and the estimation of the abundance of each endmember in each (possibly mixed) pixel. A challenging problem in spectral unmixing is how to determine the number of endmembers in a given scene. For this purpose, many algorithms have been proposed in the recent literature, being the estimation of the Virtual Dimensionality (VD) of the hyperspectral image and the hyperspectral signal subspace estimator (HySime) two of the most popular choices. Unfortunately, the high dimensionality of the hyperspectral data provided by modern sensors as well as the inherent computational complexity clearly make the use of these algorithms prohibitive for applications under real-time or near real-time constraints. Hence, the utilization of high performance computing platforms in order to accelerate the process of unmixing a hyperspectral image becomes mandatory for such scenarios. Reconfigurable hardware solutions such as field programmable gate arrays (FPGAs) have consolidated during the last years as one of the preferred choices for the fast processing of hyperspectral remotely sensed images due to their advantages over other high performance computing systems, such as clusters of computers, multicore processors and/or graphical processing units (GPUs). This paper uncovers two FPGA-based architectures for accelerating the process of estimating the number of endmembers that constitute a hyperspectral image according to the VD and the HySime algorithms. The proposed methods have been implemented on a Virtex-7 XC7VX690T FPGA and tested using real hyperspectral data collected by NASAs Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the Cuprite mining district in Nevada and the World Trade Center in New York. Experimental results demonstrate that the VD implementation exhibits real-time performance while the HySime implementation exhibits near real-time performance. Both implementations significantly outperform a software version, which makes our reconfigurable system appealing for onboard hyperspectral data processing.
URI: http://hdl.handle.net/10553/44986
ISBN: 978-0-9934-2800-5
ISSN: 1946-147X
DOI: 10.1109/FPL.2015.7293936
Source: 25th International Conference on Field Programmable Logic and Applications, FPL 2015 (7293936)
Appears in Collections:Actas de congresos
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