Hyperspectral instruments have been incorporated in satellite missions, providing large amounts of data of high spectral resolution of the Earth surface. This data can be used in remote sensing applications that often require a
real-time or near real-time response. To avoid delays between hyperspectral image acquisition and its interpretation, the last usually done on a ground station, onboard systems have emerged to process data, reducing the volume of
information to transfer from the satellite to the ground station. For this purpose, compact reconfigurable hardware modules, such as field programmable gate arrays (FPGAs) are widely used.

This paper proposes an FPGA-based architecture for hyperspectral unmixing. This method based on the Vertex Component Analysis (VCA) and it works without dimensionality reduction (DR) pre-processing step. The architecture
has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems, opening new perspectives for onboard hyperspectral image processing.