Abstract
Hyperspectral imaging is a new emerging technology in remote sensing which generates hundreds of images, at different wavelength channels, for the same area on the surface of the Earth. Over the last years, many algorithms have been developed with the purpose of finding endmembers, assumed to be pure spectral signatures in remotely sensed hyperspectral data sets. One of the most popular techniques has been the pixel purity index (PPI). This algorithm is very time-consuming. The reconfigurability, compact size, and high computational power of Field programmable gate arrays (FPGAs) make them particularly attractive for exploitation in remote sensing applications with (near) real-time requirements. In this paper, we present an FPGA design for implementation of the PPI algorithm. Our systolic array design includes a DMA and implements a prefetching technique to reduce the penalties due to the I/O communications. We have also included a hardware module for random number generation. The proposed method has been tested using real hyperspectral data collected by NASA's Airborne Visible Infrared Imaging Spectrometer over the Cuprite mining district in Nevada. Experimental results reveal that the proposed hardware system is easily scalable and able to provide accurate results with compact size in (near) real-time, which make our reconfigurable system appealing for on-board hyperspectral data processing.
Highlights
Hyperspectral imaging is concerned with the measurement, analysis, and interpretation of spectra acquired from a given scene at a short, medium, or long distance by an airborne or satellite sensor [1]
The full system has been implemented on an XUPV2P board, a low-cost reconfigurable board with a single VirtexII PRO xc2vp30 Field programmable gate arrays (FPGAs) component, a DDR SDRAM DIMM slot which holds up to 2 GBytes, an RS232 port, and some additional components not used by our implementation
Current sensor design practices could greatly benefit from the inclusion of specialized processing modules, such as FPGAs, which can be mounted or embedded in the sensor due to its compact size
Summary
Hyperspectral imaging is concerned with the measurement, analysis, and interpretation of spectra acquired from a given scene (or specific object) at a short, medium, or long distance by an airborne or satellite sensor [1]. The concept of hyperspectral imaging originated at NASA’s Jet Propulsion Laboratory in California, which developed instruments such as the Airborne Imaging Spectrometer (AIS), called AVIRIS, for Airborne Visible Infrared Imaging Spectrometer [2]. This system is able to cover the wavelength region from 0.4 to 2.5 μm using more than two hundred spectral channels, at nominal spectral resolution of 10 nm. If the spatial resolution of the sensor is not high enough to separate different materials, these can jointly occupy a single pixel and the resulting spectral measurement will be a mixed pixel, that is, a composite of the individual pure spectra.
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