| 改进的FastICA在盲图像分离中的应用 |
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| 引用本文： | 赵伟,陈伟杰,黄秀节.改进的FastICA在盲图像分离中的应用[J].国外电子测量技术,2010,29(5):70-72. |
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| 作者姓名： | 赵伟 陈伟杰 黄秀节 |
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| 作者单位： | 集美大学诚毅学院,厦门,361021 |
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| 摘 要： | 盲源分离（BSS）是信号处理领域的一个热点问题。独立分量分析（ICA）是一种基于高阶统计量的信号分析方法，它可以找到隐含在数据中的独立分量，已广泛应用于信号处理领域。为了有效地对混合图像进行盲源分离，介绍了一种基于改进的快速固定点算法（FastlCA），对经过随机线性混合后的模糊图像进行盲源分离。仿真结果显示，该算法可以很有效地对线性混合图像进行盲源分离。
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| 关 键 词： | 独立分量分析 盲源分离 快速固定点算法 |
Application of blind image separation based on improved FastICA algorithm |
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| Zhao Wei,Chen Weijie,Huang Xiujie.Application of blind image separation based on improved FastICA algorithm[J].Foreign Electronic Measurement Technology,2010,29(5):70-72. |
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| Authors: | Zhao Wei Chen Weijie Huang Xiujie |
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| Affiliation: | Zhao Wei Chen Weijie Huang Xiujie (Chengyi College of Jimei University, Xiamen 361021, China) |
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| Abstract: | Blind source separation（BSS）was a hot point of signal processing. Independent component analysis （IGA） was widely used in signal processing, which is a signal analysis method based on signal＇s high order cumulants, it can lind out the latent independent components in data. This paper introduce an improved fast fixed-point independent component analysis algorithm（FastlCA）, used to separate random mixed images. As the final, a good result was obtained through emulating with MATLAB. |
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| Keywords: | independent component analysis blind source separation fast fixed-point ICA |
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