Adaptive anisotropic diffusion for speckle filtering in SAS imagery

F. Maussang, J. Chanussot, S.C. Visan, M. Amate
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引用次数: 3

Abstract

Thanks to their high resolution, the images provided by synthetic aperture sonar (SAS) are of great interest for the detection and classification of underwater mines lying on the sea bed or buried in the sea floor. As with any acoustic imaging systems, SAS data are highly corrupted by a multiplicative noise, called the speckle, which can be very disturbing for the interpretation and the automatic analysis of the images. In order to reduce this noise and smooth the data, the properties of an anisotropic diffusion filter (ADF) are interesting. In this paper, we propose to adapt the setting of this filter parameters thanks the knowledge provided by an other process. This allows to smooth the speckle noise in the background, while the regions likely to contain any object of interest are preserved.
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自适应各向异性扩散在SAS图像中的散斑滤波
合成孔径声呐(SAS)图像分辨率高,对海底或海底埋设水雷的探测和分类具有重要意义。与任何声学成像系统一样,SAS数据被称为散斑的乘法噪声严重损坏,这可能会对图像的解释和自动分析造成非常大的干扰。为了降低噪声并使数据平滑,各向异性扩散滤波器(ADF)的特性引起了人们的关注。在本文中,我们建议利用其他过程提供的知识来调整该滤波器参数的设置。这样可以平滑背景中的斑点噪声,同时保留可能包含任何感兴趣对象的区域。
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