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

Lim B.-G.Woo J.-C.Kim Y.-S.

首页> 外文期刊>Geoscience and Remote Sensing Letters, IEEE >Noniterative Super-Resolution Technique Combining SVA With Modified Geometric Mean Filter

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

机译：SVA与改进的几何均值滤波器相结合的非迭代超分辨率技术

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摘要

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 $sim$40% compared to SVA and phase-extension inverse filtering.

机译：我们提出了一种超分辨率算法，该算法将空间变异变迹（SVA）与改进的几何均值滤波器相结合，以提高合成孔径雷达（SAR）图像的分辨率并同时减少旁瓣。此方法不需要迭代计算。通过使用点目标进行仿真以及在真实SAR图像的实验中验证了所提算法的有效性。与SVA和相位扩展逆滤波相比，所提出的方法将分辨率提高了$ sim $ 40％。

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来源
《Geoscience and Remote Sensing Letters, IEEE》 |2010年第4期|p.713-717|共5页
作者
Lim B.-G.Woo J.-C.Kim Y.-S.;
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作者单位

DivisionofElectricalandComputerEngineering,PohangUniversityofScienceandTechnology,Pohang,Korea;

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原文格式 PDF
正文语种 eng
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关键词
Geometric mean filter (GMF); spatially variant apodization (SVA); super-resolution; synthetic aperture radar (SAR);

机译：几何均值滤波器（GMF）;空间变迹（SVA）;超分辨率;合成孔径雷达（SAR）;

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

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