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Finding Endmembers in Hyperspectral Imagery
2016Endmembers, defined as pure signatures, can be used to specify distinct spectral classes of interest in the data, thus providing crucial information in hyperspectral data exploitation. Technically speaking, an endmember is generally considered as a calibrated spectral signature in a data base or spectral library and is not necessarily to be a real data
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Compression of hyperspectral imagery via linear prediction
2006Motta et al., 2003) proposed a Locally Optimal Vector Quantizer (LPVQ) for lossless encoding of hyperspectral data, in particular, Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) images. In this paper we first show how it is possible to improve the baseline LPVQ algorithm via linear prediction techniques, band reordering and least squares ...
FRANCESCO RIZZO +3 more
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Target detection of hyperspectral imagery
Eighth Symposium on Novel Photoelectronic Detection Technology and Applications, 2022Hang Qu, Lei Xiao, Xinghua Hou
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Using satellite imagery to understand and promote sustainable development
Science, 2021Marshall B Burke +2 more
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A review of deep learning methods for semantic segmentation of remote sensing imagery
Expert Systems With Applications, 2021Xiaohui Yuan
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Street view imagery in urban analytics and GIS: A review
Landscape and Urban Planning, 2021Filip Biljecki, Koichi Ito
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Combining satellite imagery and machine learning to predict poverty
Science, 2016Neal Jean +2 more
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Laser–Raman imagery of Earth's earliest fossils
Nature, 2002J William Schopf, Andrew D Czaja
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Object-based cloud and cloud shadow detection in Landsat imagery
Remote Sensing of Environment, 2012Zhe Zhu, Curtis E Woodcock
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