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Multiscale and Multidirectional Multilooking for SAR Image Enhancement

Schmitt, Andreas (2016) Multiscale and Multidirectional Multilooking for SAR Image Enhancement. IEEE Transactions on Geoscience and Remote Sensing, 54 (9), Seiten 5117-5134. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/TGRS.2016.2555624. ISSN 0196-2892.

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Offizielle URL: http://ieeexplore.ieee.org/document/7469812/metrics

Kurzfassung

With the steadily increasing spatial resolution of synthetic aperture radar images, the need for a consistent, but locally adaptive image enhancement rises considerably. Numerous studies already showed that adaptive multi-looking, able to adjust the degree of smoothing locally to the size of the targets, is superior to uniform multi-looking. This study introduces a novel approach of multi-scale and multi-directional multi-looking based on intensity images exclusively, but applicable to an arbitrary number of image layers. A set of two-dimensional circular and elliptical filter kernels in different scales and orientations (named Schmittlets) is derived from hyperbolic functions. The original intensity image is transformed into the Schmittlet coefficient domain where each coefficient measures the existence of Schmittlet-like structures in the image. By estimating their significance via the perturbation-based noise model, the best-fitting Schmittlets are selected for image reconstruction. On the one hand, the index image indicating the locally best-fitting Schmittlets is utilized to consistently enhance further image layers, e.g. multi-polarized, multi-temporal, or multi-frequency layers, and on the other hand, it provides an optimal description of spatial patterns valuable for further image analysis. The final validation proves the advantages of the Schmittlets over six contemporary speckle reduction techniques in six different categories (preservation of the mean intensity, equivalent number of looks, and preservation of edges and local curvature both in strength and in direction) by the help of four test sites on three resolution levels. The additional value of the Schmittlet index layer for automated image interpretation, though obvious, still is subject to further studies.

elib-URL des Eintrags:https://elib.dlr.de/106189/
Dokumentart:Zeitschriftenbeitrag
Titel:Multiscale and Multidirectional Multilooking for SAR Image Enhancement
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Schmitt, AndreasAndreas.Schmitt (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:September 2016
Erschienen in:IEEE Transactions on Geoscience and Remote Sensing
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:54
DOI:10.1109/TGRS.2016.2555624
Seitenbereich:Seiten 5117-5134
Verlag:IEEE - Institute of Electrical and Electronics Engineers
Name der Reihe:Transactions on Geoscience and Remote Sensing
ISSN:0196-2892
Status:veröffentlicht
Stichwörter:Adaptive filters, Digital filters, Image analysis, Image edge analysis, Image enhancement, Image reconstruction, Image representations, Synthetic aperture radar, Schmittlets, Multi-scale, Multi-directional, Multi-looking
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - TSX/TDX Missionsbetrieb
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum > Landoberfläche
Hinterlegt von: Schmitt, Andreas
Hinterlegt am:12 Okt 2016 10:17
Letzte Änderung:31 Okt 2023 07:33

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