Journal of Real-Time Image Processing

, Volume 15, Issue 2, pp 297–308 | Cite as

A novel FPGA-based architecture for the estimation of the virtual dimensionality in remotely sensed hyperspectral images

  • Carlos GonzalezEmail author
  • Sebastian Lopez
  • Daniel Mozos
  • Roberto Sarmiento
Original Research Paper


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.


Number of endmembers estimation Hyperspectral imaging Field-programmable gate arrays (FPGAs) Virtual dimensionality Reconfigurable hardware 



This work has been supported by the by the Spanish Ministry of Science and Innovation under references READAR (TIN2013-40968-P) and DREAMS (TEC2011-28666-C04-04).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Carlos Gonzalez
    • 1
    Email author
  • Sebastian Lopez
    • 2
  • Daniel Mozos
    • 1
  • Roberto Sarmiento
    • 2
  1. 1.Department of Computer Architecture and Automatics, Computer Science FacultyComplutense University of MadridMadridSpain
  2. 2.Institute for Applied Microelectronics (IUMA)University of Las Palmas de Gran CanariaLas PalmasSpain

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