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Fuzzy C-means and principal component analysis based GPR image enhancement

机译:基于模糊C均值和主成分分析的GPR图像增强

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In this paper, a ground penetrating radar image enhancement scheme based on fuzzy c-means and principal component analysis is proposed. The original image is decomposed into clutter, noise and target subspaces using principal component analysis. Fuzzy c-means is used to assign weights to different subspaces based on their membership values. Simulation results demonstrate that the proposed scheme can detect (single and multiple) targets, provide better mean square error and peak signal to noise ratio.
机译:提出了一种基于模糊c均值和主成分分析的探地雷达图像增强方案。使用主成分分析将原始图像分解为杂波,噪声和目标子空间。模糊c均值用于根据其子成员关系值将权重分配给不同的子空间。仿真结果表明,该方案可以检测(单个和多个)目标,提供更好的均方误差和峰值信噪比。

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