Multimodal Representation Learning and Set Attention for LWIR In-Scene Atmospheric Compensation

A multimodal generative modeling approach combined with permutation-invariant set attention is investigated in this article to support long-wave infrared (LWIR) in-scene atmospheric compensation. The generative model can produce realistic atmospheric state vectors (T, H 2 O, O 3 ) and their correspo...

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Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing 2021, Vol.14, p.127-140
Hauptverfasser:	Westing, Nicholas, Gross, Kevin C., Borghetti, Brett J., Kabban, Christine M. Schubert, Martin, Jacob, Meola, Joseph
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Atmospheric compensation Atmospheric measurements Atmospheric modeling Atmospheric models Atmospheric waves Compensation Data models Decoding Detection Downwelling Expression vectors generative modeling Hypercubes hyperspectral imagery Infrared analysis Invariants Modelling Neural networks Object detection Ocean circulation Permutations Predictive models Radiance Radiative transfer State vectors Submarine pipelines Target detection Upwelling Vectors
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