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.
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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/ | ||||||
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Document Type: | Article | ||||||
Title: | Multiscale and Multidirectional Multilooking for SAR Image Enhancement | ||||||
Authors: |
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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 - Earth Observation | ||||||
DLR - Research theme (Project): | R - TSX/TDX Mission Operations | ||||||
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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