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Predicting Filtered Image Quality Using Transfer Learning on Sentinel-1 Speckle Noise with DenseNet-121

Speckle noise inherent to synthetic aperture radar (SAR) imagery degrades image quality and complicates automated analysis in Earth observation applications. Quantitative assessment of despeckling results requires computing quality metrics against reference images, which are unavailable in operation...

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Bibliographische Detailangaben
Datum:	2025
Hauptverfasser:	Al-Senaikh, Raed, Rubel, Oleksii
Format:	Artikel
Sprache:	Englisch
Veröffentlicht:	Scientific Centre for Aerospace Research of the Earth Institute of Geological Science National Academy of Sciences of Ukraine, Kyiv, Ukraine 2025
Schlagworte:	Speckle noise Sentinel-1 image quality metrics DenseNet-121 transfer learning
Online Zugang:	https://ujrs.org.ua/ujrs/article/view/293
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!
Назва журналу:	Ukrainian Journal of Remote Sensing of the Earth

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Ukrainian Journal of Remote Sensing of the Earth

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