首页> 外文会议>PIAGENG 2009;International conference on photonics and image in agriculture engineering >Despeckling SAR Images Using Adaptive Bandelet Transform and Bayesian Maximum a Posteriori Estimation
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Despeckling SAR Images Using Adaptive Bandelet Transform and Bayesian Maximum a Posteriori Estimation

机译:使用自适应Bandelet变换和贝叶斯最大值后验估计对SAR图像进行去斑

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Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the coherent nature of scattering phenomena. This paper presents a despeckling method for SAR images based on adaptive bandelet transform. Bayesian maximum a posteriori (MAP) estimation is applied to adaptive bandelet transform coefficients to achieve more satisfying results. The performances of adaptive bandelet transform and wavelet thresholding for despeckling SAR images are compared through an experiment. Experiment results clearly demonstrated the capability of the proposed scheme in SAR image speckle reduction especially for SAR images possessing detailed textures.
机译:合成孔径雷达(SAR)图像固有地受到倍增斑点噪声的影响,这是由于散射现象的相干性质所致。提出了一种基于自适应bandelet变换的SAR图像去斑方法。贝叶斯最大后验(MAP)估计应用于自适应bandelet变换系数以获得更令人满意的结果。通过实验比较了自适应去斑带变换和小波阈值去斑SAR图像的性能。实验结果清楚地证明了该方案在减少SAR图像斑点方面的能力,特别是对于具有详细纹理的SAR图像而言。

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