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数据场典型相关分析及其在图像分割中的应用

DOI: 10.16383/j.aas.2015.c130896, PP. 772-784

Keywords: 典型相关分析,数据场,特征提取,图像分割

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Abstract:

?针对数据场环境下多维数据的低维特征提取问题,本文将数据之间的相互作用纳入其相关性求解中,提出一种基于数据场的典型相关分析(Datafieldbasedcanonicalcorrelationanalysis,DFCCA)方法.DFCCA提取的特征具有良好的分布特性,原空间上相隔较远的数据点对的特征聚集在一个较小区域内,而相邻数据点对的特征却有规律地分布在其他点所聚集区域的周围.此特性使得DFCCA具有较好的边界辨识能力,将其应用于图像分割的实验结果表明,DFCCA提取的复杂图像边界具有较好的保真度.

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