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Title: A novel FPGA-based architecture for the estimation of the virtual dimensionality in remotely sensed hyperspectral images
Authors: Gonzalez, Carlos
Lopez, Sebastian 
Mozos, Daniel
Sarmiento, Roberto 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Number of endmembers estimation
Hyperspectral imaging
Field-programmable gate arrays (FPGAs)
Virtual dimensionality
Reconfigurable hardware
Issue Date: 2018
Journal: Journal of Real-Time Image Processing 
Abstract: A challenging problem in spectral unmixing is how to determine the number of endmembers in a given scene. One of the most popular ways to determine the number of endmembers is by estimating the virtual dimensionality (VD) of the hyperspectral image using the well-known Harsanyi–Farrand–Chang (HFC) method. Due to the complexity and high dimensionality of hyperspectral scenes, this task is computationally expensive. Reconfigurable field-programmable gate arrays (FPGAs) are promising platforms that allow hardware/software codesign and the potential to provide powerful onboard computing capabilities and flexibility at the same time. In this paper, we present the first FPGA design for the HFC-VD algorithm. The proposed method has been implemented on a Virtex-7 XC7VX690T FPGA and tested using real hyperspectral data collected by NASA’s Airborne Visible Infra-Red Imaging Spectrometer over the Cuprite mining district in Nevada and the World Trade Center in New York. Experimental results demonstrate that our hardware version of the HFC-VD algorithm can significantly outperform an equivalent software version, which makes our reconfigurable system appealing for onboard hyperspectral data processing. Most important, our implementation exhibits real-time performance with regard to the time that the hyperspectral instrument takes to collect the image data.
ISSN: 1861-8200
DOI: 10.1007/s11554-014-0482-2
Source: Journal of Real-Time Image Processing [ISSN 1861-8200], v. 15 (2), p. 297-308
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