Pushbroom hyperspectral imagers (HSIs) are being increasingly used for aerial vegetative and/or geological
ground mapping1. There is also considerable interest in using hyperspectral imagers for aerial surveillance and
military targeting2. The Optics and Lasers Department of the Advanced Technology Centre (ATC) of BAE
Systems has been working on these problems for several years3. To this end a number of spatial and spectral
detection algorithms have been developed, based on change detection, matched filtering and anomaly detection4.
The department owns several visible (VIS) and short wave infrared (SWIR) hyperspectral cameras systems,
with different resolutions, field of views, and operational speeds.
Advanced multispectral, or hyperspectral, camera systems are being used to identify objects of interest on the
basis of spectral characteristics. In previous papers we have described the development of a hyperspectral real
time tracking system using matched filtering. This paper will discuss alternative methods of gathering
hyperspectral imagery and consider how they should be adapted to suit the various applications. It will also
present some recent improvements made to the design and operation of our fast visible hyperspectral imaging
system. These improvements are allowing objects of interest to be successfully tracked in lower light levels with
reduced false alarm levels. Aerial applications of hyperspectral imagers will also be discussed.
Advanced multispectral, or hyperspectral, camera systems are being used to identify objects of interest on the basis of spectral characteristics. This paper will describe developments in the field of a real time spectral matched filtering. Matched filtering relies on there being a measurable difference between the spectrum of the target and that of background materials such as soil, vegetation, concrete and tarmac. If prior knowledge is available then the target can be found by matching the two spectra numerically. Previous work has identified the most robust and effective matched filtering technique. Software has been written to interface with a pushbroom hyperspectral sensor to enable fast spectrally tracking of objects. False alarms have been reduced by means of additional processing. Example detections of a number of unclassified objects will be presented.
This paper will describe the development of a real time matched filtering technique for hyperspectral imagery.
Advanced multispectral, or hyperspectral, camera systems can potentially be used to identify objects of interest on the
basis of spectral characteristics. Matched filtering relies on there being a measurable difference between the spectrum of
the target and that of background materials such as soil, vegetation, concrete and tarmac. If prior knowledge is available
then the target can be found by numerically matching the two spectra. Tests have been carried out to evaluate the
effectiveness of a technique that utilises a specific type of spectral matched filter. Some results from the tests will be
presented that indicate how our technique is affected by changes in environmental and illumination conditions. Example
detections of a number of unclassified objects will be presented.
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