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模糊方向滤波在SAR图像处理中的应用 被引量：1

Application of Fuzzy Direction Filtering in Processing SAR Image
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摘要 介绍了合成孔径雷达(SAR)成像特点。探讨了基于方向滤波器和模糊逻辑的模糊方向滤波法,此方法首先将图像进行特征平面增强并模糊化,并获得模糊参数,然后根据模糊规则计算隶属度,以具有相应最大隶属度的像素构成最后滤波结果,达到既滤除噪声又保留图像细节的目的。实验表明此方法优于Lee滤波算法、Esafa算法和加权形态滤波算法。 The paper introduces the characters of synthetic aperture radar imaging, and discusses the fuzzy direction filtering method based on direction filter and fuzzy logic. The method aggrandizes characteristic-plane to get fuzzy characteristic-plane and its fuzzy parameter firstly. Then computes credibility according to the designed fuzzy rule. The final filtered image is composed of all the pixels with corresponding maximal credibility. It can not only filter noise but also save image in detail. Experiment proves that the proposed method is better than the Lee＇s filter, the Esafa＇s algorithm and the weighted morphological filter.
作者 张飞猛 顾国华 凌冬冬 周刚锋 陈开生
机构地区 解放军炮兵学院一系 解放军炮兵学院研究生系
出处 《工程图学学报》 CSCD 北大核心 2006年第6期69-73,共5页 Journal of Engineering Graphics
关键词 计算机应用 SAR图像处理 模糊方向滤波 特征平面 隶属度 computer application SAR image processing fuzzy direction filter characteristic-plane credibility
分类号 TN957 [电子电信—信号与信息处理]
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参考文献14

  • 1Lee J S. Speckle suppression and analysis for synthetic aperture radar [J]. Opt. Eng, 1986, 25(5): 636-643.
  • 2Kuan D T, Sawchuk A A, Strand T C, et al. Adaptive restoration of images with speckle [J]. IEEE Trans.Acoust. Speech Signal Processing, 1987, ASSP-35:373-383.
  • 3Frost V S, Stiles J A, Shanmugan K S, et al. A model for radar images and its application to adaptive digital filtering of multiplicative noise [J]. IEEE Trans.Pattern Anal. Machine Intell, 1982, PAMI 4:157-165.
  • 4Tukey J W. Exploratory data analysis [M]. MA:Addison-wesley, 1997.
  • 5Grimmins R. Geometric filter for reducing speckle [J].Opt. Eng, 1986, 25: 652-654.
  • 6Dong Y, Forster B C, Milne A K, et al. Speckle suppression using re. cursive wavelet transform [J]. Int.J. Remote Sensing, 1998, 19(2): 317-310.
  • 7Esafa G Fiouzar. Speckle removal based on mathema-tical morphology [J]. Signal Processing,1989, 16(4): 320-333.
  • 8Sedaaghi M H, Wu Q H. Weighted morphological filter [J]. Electronics Letters, 1999, 34(8): 1566-1567.
  • 9Lee J S, Jurkevich I, Dewalle P, et al. Speckle filtering of synthetic aperture radar images: areview [J].Remote Sensing Rev, 1994, 8(4): 313-340.
  • 10Dewaele P, Wambacq P, Oosterhnck A, et al.Comparison of some speckle reduction techniquesfor SAR images [A]. In: IGRASS' 90 [C]. Maryland,USA: the University of Maryland college Park,2417-2422.

二级参考文献11

  • 1J S Lee. Speckle suppression and analysis for synthetic aperture radar. Opt Eng,vol.25, no.5,pp.636-643,1986.
  • 2D T Kuan, A A Sawchuk, T C Strand, and P Chavel.Adaptive restoration of images with speckle. IEEE Trans Acoust Speech Signal Processing, vol. ASSP-35,pp.373-383,1987.
  • 3V S Frost, J A Stiles, K S Shanmugan, and J C Holtzman. A model for radar images and its application to adaptive digital filtering of multiplicative noise. IEEE Trans. Pattern Anal. Machine Intell, vol. PAMI-4,pp.157-165,1982.
  • 4J W Tukey. Exploratory data analysis. MA:Addison-wesley, 1997.
  • 5T R Grimmins. Geometric filter for reducing speckle.Opt Eng , vol.25, pp.652-654,1986.
  • 6Y Dong, B C Forster, A K Milne, and G A Morgan.Speckle suppression using recursive wavelet transform.Int J Remote Sensing, vol.19, no.2, pp.317-310,1998.
  • 7F Safa, G Fiouzar. Speckle removal based on mathema-tical morphology. Signal Processing, 1989,16(4): 320- 333.
  • 8M H Sedaaghi, Q H Wu. Weighted morphological filter.Electronics Letters, vol.34, no.16,pp.1566-1567.
  • 9J S Lee, I Jurkevich, P Dewalle, P Wambacq, and A Oosterlink. Speckle ffltedng of synthetic aperture radar images: A review. Remote Sensing Rev , vol.8, no.4,pp.313-340,1994.
  • 10Dewaele P , Wambacq P, Oosterlinck A, et al. Comparison of some speckle reduction techniques for SAR Images.IGRASS'90, Maryland, USA:the University of Maryland college Park,2417-2422.

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工程图学学报
2006年 第6期

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