基于局部属性分析和离散不可分剪切波变换的SAR图像去噪

Ye Yuan, Liangzhuo Xie, Yewen Zhu, Sheng Wang, Zhemin Zhuang
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引用次数: 1

摘要

提出了一种利用SAR图像局部特性分析和离散不可分离剪切波变换(DNST)的SAR图像去噪方法。根据局部属性分析方法,将SAR图像分为均匀区域、非均匀区域和目标区域。均匀区采用平均滤波器去噪。非均匀区域采用DNST变换去噪,直接保留目标区域。实验结果表明,该方法能有效地降低散斑噪声,提高图像的边缘保持能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SAR image de-noising using local properties analysis and discrete non-separable shearlet transform
A new SAR image de-noising approach that uses the local properties analysis of SAR image and the discrete nonseparable shearlet transform (DNST) is proposed in this paper. According to the local properties analysis method, the SAR image is divided into homogeneous region, non-homogeneous region and target region. The homogeneous region uses the average filter to de-noising. The non-homogeneous region uses the DNST transform to de-noising and target region is reserved directly. The experimental results show that the proposed approach can efficiently reduce the speckle noises and improve the edge-preserving ability.
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