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Remotely sensed hyperspectral imagery provides, at each pixel, a radiance spectrum with up to hundreds of distinct wavelength channels. This high-dimensional spectral information allows for pixel-level material discrimination, including applications to remotely detecting the presence of particular materials of interest within a scene. Target detection takes a spectrum (or multiple spectra) corresponding...
Imagery collected from satellites and airborne platforms provides an important tool for remotely analyzing the content of a scene. In particular, the ability to remotely detect a specific material within a scene is of critical importance in nonproliferation and other applications. The sensor systems that process hyperspectral images collect the high-dimensional spectral information necessary to perform...
The analysis of remotely sensed spectral imagery has a variety of applications in both the public and private sectors, including tracking urban development, monitoring the spread of diseased crops, and mapping environmental disasters. The high spatial and spectral resolutions in hyperspectral imagery (HSI) make it particularly desirable for these types of analyses, as HSI sensors capture “color” information...
Hyperspectral image data are traditionally analyzed using statistical models. However, as the spatial and spectral resolutions of the images improve as a result of advances in sensor technology, the data no longer maintain a Gaussian distribution; this is due to increased material diversity in the scene, i.e., clutter. This causes many statistical assumptions about the data — and subsequently, the...
Spectral anomaly detection in hyperspectral imagery is concerned with identifying unusual spectra that occur infrequently within the image. The modelappliedinthis paper is based on the idea that background pixels reside on, or near, lower dimensional manifolds (surfaces) in the higher-dimensional spectral space. Using a similarity graph to approximate the theoretical background manifold(s), we investigate...
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