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  An image transform based on temporal decomposition

Cremer, F., Urbazaev, M., Berger, C., Mahecha, M. D., Schmullius, C., & Thiel, C. (2018). An image transform based on temporal decomposition. IEEE Geoscience and Remote Sensing Letters, 15(4), 537-541. doi:10.1109/LGRS.2018.2791658.

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BGC2841.pdf (Verlagsversion), 3MB
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 Urheber:
Cremer, Felix, Autor
Urbazaev, Mikhail, Autor
Berger, Christian, Autor
Mahecha, Miguel D.1, Autor           
Schmullius, Christiane, Autor
Thiel, Christian, Autor
Affiliations:
1Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1938312              

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 Zusammenfassung: Today, very dense synthetic aperture radar (SAR) time series are available through the framework of the European Copernicus Programme. These time series require innovative processing and preprocessing approaches including novel speckle suppression algorithms. Here we propose an image transform for hypertemporal SAR image time stacks. This proposed image transform relies on the temporal patterns only, and therefore fully preserves the spatial resolution. Specifically, we explore the potential of empirical mode decomposition (EMD), a data-driven approach to decompose the temporal signal into components of different frequencies. Based on the assumption that the high-frequency components are corresponding to speckle, these effects can be isolated and removed. We assessed the speckle filtering performance of the transform using hypertemporal Sentinel-1 data acquired over central Germany comprising 53 scenes. We investigated speckle suppression, ratio images, and edge preservation. For the latter, a novel approach was developed. Our findings suggest that EMD features speckle suppression capabilities similar to that of the Quegan filter while preserving the original image resolution.

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 Datum: 20182018-04
 Publikationsstatus: Erschienen
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 Identifikatoren: Anderer: BGC2841
DOI: 10.1109/LGRS.2018.2791658
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Titel: IEEE Geoscience and Remote Sensing Letters
  Andere : IEEE Geosci. Remote Sens. Lett.
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: Piscataway, NJ : Institute of Electrical and Electronics Engineers
Seiten: - Band / Heft: 15 (4) Artikelnummer: - Start- / Endseite: 537 - 541 Identifikator: ISSN: 1545-598X
CoNE: https://pure.mpg.de/cone/journals/resource/954925491886