Noniterative Super-Resolution Technique Combining SVA With Modified Geometric Mean Filter

We propose a super-resolution algorithm that combines spatially variant apodization (SVA) with a modified geometric mean filter to improve the resolution of synthetic aperture radar (SAR) images and reduce sidelobes simultaneously. This method does not require iterative calculation. The efficacy of...

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Veröffentlicht in:IEEE geoscience and remote sensing letters 2010-10, Vol.7 (4), p.713-717
Hauptverfasser: Lim, Byoung-Gyun, Woo, Jae-Choon, Kim, Young-Soo
Format: Artikel
Sprache:eng
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Zusammenfassung:We propose a super-resolution algorithm that combines spatially variant apodization (SVA) with a modified geometric mean filter to improve the resolution of synthetic aperture radar (SAR) images and reduce sidelobes simultaneously. This method does not require iterative calculation. The efficacy of the proposed algorithm is verified by simulation with point targets and in experiments with a real SAR image. The proposed method improved resolution by 40% compared to SVA and phase-extension inverse filtering.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2010.2046877