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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), pp. 5117-5134. IEEE - Institute of Electrical and Electronics Engineers. DOI: 10.1109/TGRS.2016.2555624 ISSN 0196-2892

Full text not available from this repository.

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

Abstract

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.

Item URL in elib:https://elib.dlr.de/106189/
Document Type:Article
Title:Multiscale and Multidirectional Multilooking for SAR Image Enhancement
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Schmitt, AndreasAndreas.Schmitt (at) dlr.deUNSPECIFIED
Date:September 2016
Journal or Publication Title:IEEE Transactions on Geoscience and Remote Sensing
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:54
DOI :10.1109/TGRS.2016.2555624
Page Range:pp. 5117-5134
Publisher:IEEE - Institute of Electrical and Electronics Engineers
Series Name:Transactions on Geoscience and Remote Sensing
ISSN:0196-2892
Status:Published
Keywords: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 - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - TSX/TDX Misson operation
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface
Deposited By: Schmitt, Andreas
Deposited On:12 Oct 2016 10:17
Last Modified:08 Mar 2018 18:34

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