The pixel purity index algorithm is employed in remote sensing for analyzing hyperspectral images. A single pixel usually covers several different materials, and its observed spectrum can be expressed as a linear combination of a few pure spectral signatures. This algorithm tries to identify these pure spectra. In this paper, we present a Field Programmable Gate Array implementation of the algorithm, which has been implemented on a Virtex-II PRO XC2VP30 and on a Virtex-4 XC4VFX60 FPGAs and evaluated using the well-known “Cuprite” image (a standard benchmark in hyperspectral imaging applications). Our experimental results demonstrate that a hardware version of the PPI algorithm can significantly outperform an equivalent software version of the algorithm and retain excellent pure spectral extraction accuracy. In addition, the proposed architecture is easily scalable depending of the available resources and is more than three times faster than a recently developed FPGA implementation of the same algorithm due to the architectural improvements.
[1]
Antonio Plaza,et al.
FPGA design and implementation of a fast pixel purity index algorithm for endmember extraction in hyperspectral imagery
,
2005,
SPIE Optics East.
[2]
Antonio J. Plaza,et al.
A quantitative and comparative analysis of endmember extraction algorithms from hyperspectral data
,
2004,
IEEE Transactions on Geoscience and Remote Sensing.
[3]
Maya Gokhale,et al.
FPGA implementation of the pixel purity index algorithm
,
2000,
SPIE Optics East.
[4]
J. Boardman.
Automating spectral unmixing of AVIRIS data using convex geometry concepts
,
1993
.
[5]
Tarek A. El-Ghazawi,et al.
The Promise of High-Performance Reconfigurable Computing
,
2008,
Computer.
[6]
Antonio J. Plaza,et al.
A fast iterative algorithm for implementation of pixel purity index
,
2006,
IEEE Geoscience and Remote Sensing Letters.