537 research outputs found
Detecting anomalies in remotely sensed hyperspectral signatures via wavelet transforms
An automated subpixel target detection system has been designed and tested for use with remotely sensed hyperspectral images. A database of hyperspectral signatures was created to test the system using a variety of Gaussian shaped targets. The signal-to-noise ratio of the targets varied from -95dB to -50dB. The system utilizes a wavelet-based method (discrete wavelet transform) to extract an energy feature vector from each input pixel signature. The dimensionality of the feature vector is reduced to a one-dimensional feature scalar through the process of linear discriminant analysis. Signature classification is determined by nearest mean criterion that is used to assign each input signature to one of two classes, no target present or target present. Classification accuracy ranged from nearly 60% with target SNR at -95dB without any a priori knowledge of the target, to 100% with target SNR at -50dB and a priori knowledge about the location of the target within the spectral bands of the signature
A multi-temporal hyperspectral camouflage detection and transparency experiment
Hyperspectral sensors are used to measure the electromagnetic spectrum in hundreds of narrow and contiguous
spectral bands. The recorded data exhibits characteristic features of materials and objects. For tasks within
the security and defense domain, this valuable information can be gathered remotely using drones, airplanes
or satellites. In 2021, we conducted an experiment in Ettlingen, Germany, using a drone-borne hyperspectral
sensor to record data of various camouflage setups. The goal was the inference of camouflage detection limits
from typical hyperspectral data evaluation approaches for different scenarios. The experimental site is a natural
strip of vegetation between two corn fields. Our main experiment was a camouflage garage that covered different
target materials and objects. The distance between the targets and the roof of the camouflage garage was
modified during the experiment. Together with the target variations, this was done to determine the material
dependent detection limits and the transparency of the camouflage garage. Another experiment was carried
out using two different types of camouflage nets in various states of occlusion by freshly cut vegetation. This
manuscript contains a detailed experiment description, as well as, the first results of the camouflage transparency
and occlusion experiment. We show that it is possible to determine the target inside the camouflage garage and
that vegetation cover is not suitable additional camouflage for hyperspectral sensors
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