首页> 外文会议>MIPPR 2007: Multispectral Image Processing; Proceedings of SPIE-The International Society for Optical Engineering; vol.6787 >Speckle reduction for target extraction in synthetic aperture radar images using adaptive space separation based on independent component analysis
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Speckle reduction for target extraction in synthetic aperture radar images using adaptive space separation based on independent component analysis

机译:基于独立分量分析的自适应空间分离减少合成孔径雷达图像中的目标斑点

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摘要

Proposed is a novel approach based on independent component analysis (ICA) for speckle reduction and target extraction of SAR (synthetic aperture radar) images using adaptive space separation with weighted information entropy incorporated. First the basis and the independent components are respectively obtained by ICA technique, and Weighted Information Entropy of the image is computed, then based on the threshold computed from function T-WIE (Threshold VS. Weighted-Information-Entropy), independent components are adaptively separated and the basis are classified accordingly. Thus, the image space is separated into two subspaces -'clean' and 'noise'. Then, a proposed nonlinear operator 'ABO' is applied on each component of the 'clean' subspace for further optimization. Finally, recovery image is obtained reconstructing this subspace and target is easily extracted with binarisation. Note that here T-WIE is an interpolated function based on several representative target SAR images using proposed space separation algorithm.
机译:提出了一种基于独立成分分析(ICA)的新方法,该方法利用自适应空间分离并结合了加权信息熵来减少SAR(合成孔径雷达)图像的斑点和目标。首先通过ICA技术分别获得基础分量和独立分量,然后计算图像的加权信息熵,然后根据函数T-WIE(阈值VS.加权信息熵)计算出的阈值,自适应地自适应独立分量。分开,并据此对基础进行分类。因此,图像空间被分为两个子空间-“干净”和“噪声”。然后,将拟议的非线性算子“ ABO”应用于“干净”子空间的每个组件,以进行进一步优化。最后,获得重建该子空间的恢复图像,并通过二值化轻松提取目标。请注意,此处的T-WIE是使用提议的空间分离算法基于几个代表性目标SAR图像的插值函数。

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