Sparsity and morphological diversity for hyperspectral data analysis [PDF]
, 2010 Recently morphological diversity and sparsity have emerged as new and effective sources of diversity for Blind Source Separation. Based on these new concepts, novelmethods such as Generalized Morphological Component Analysis have been put forward ...
Bobin, J. +3 more
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Linking goniometer measurements to hyperspectral and multi-sensor imagery for retrieval of beach properties and coastal characterization [PDF]
, 2012 In June 2011, a multi-sensor airborne remote sensing campaign was flown at the Virginia Coast Reserve Long Term Ecological Research site with coordinated ground and water calibration and validation (cal/val) measurements.
Abelev, Andrei +21 more
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Spectral Feature Selection from the Hyperspectral Dataset to Identify Pistachio Leaves Infected by Psylla [PDF]
Journal of Agricultural Machinery, 2022 IntroductionPistachio production has been adversely affected by Psylla, which is a devastating insect. The primary goal of this study was to select sensitive spectral bands to distinguish pistachio leaves infected by Psylla from healthy leaves. Diagnosis
A Moghimi, A Sazgarnia, M. H Aghkhani
doaj +1 more source
Quality criteria benchmark for hyperspectral imagery [PDF]
, 2005 Hyperspectral data appear to be of a growing interest over the past few years. However, applications for hyperspectral data are still in their infancy as handling the significant size of the data presents a challenge for the user community. Efficient
Christophe, Emmanuel +2 more
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Hyperspectral Data Analysis and Visualization [PDF]
, 2011 Electro-Optical (EO) imaging sensors are widely used for a range of tasks, e.g. for TargetAcquisition (TA: detection, recognition and identification of (military) relevant objects) or visual search. These tasks can be performed by a human observer, by an algorithm (Automatic Target Recognition) or by both (Aided Target Recognition). In the past decades,
Hogervorst, M.A., Schwering, P.B.W.
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A low-cost hyperspectral scanner for natural imaging and the study of animal colour vision above and under water [PDF]
, 2019 Hyperspectral imaging is a widely used technology for industrial and scientific purposes, but the high cost and large size of commercial setups have made them impractical for most basic research.
Baden, T, Nevala, N E
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An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery [PDF]
, 2020 Hyperspectral image sensing can be used to effectively detect the distribution of harmful cyanobacteria. To accomplish this, physical- and/or model-based simulations have been conducted to perform an atmospheric correction (AC) and an estimation of ...
Baek, Sangsoo +10 more
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Remote Sensing, 2020 Methane (CH4) is one of important greenhouse gases that affects the global radiative balance after carbon dioxide (CO2). Previous studies have demonstrated the detection of known sources of CH4 emission using the hyperspectral technology based on in situ
Chunlei Xiao +4 more
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Spectral Similarity Measures for In Vivo Human Tissue Discrimination Based on Hyperspectral Imaging
Diagnostics, 2023 Problem: Similarity measures are widely used as an approved method for spectral discrimination or identification with their applications in different areas of scientific research.
Priya Pathak +10 more
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Informational Clustering of Hyperspectral Data
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014 Hyperspectral remote sensing is recognized as a powerful tool for mineralogical mapping of exposed surfaces on Earth and planets, as well. It allows for more rigorous discrimination among materials than multispectral imaging. Nevertheless, the huge data volume that comes with single observations results in severe limitations to successful data ...
POMPILIO, Loredana +3 more
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