From researching on the universal principle of feature fusion of image, a new algorithm was proposed which based on the 2 dimension principal component analyses (for short 2dpca).
通过对图像特征融合的一般规律的研究，提出了一种基于二维主成分分析(简称2dpca)的图像特征融合算法。
This dissertation mainly studied the image feature fusion based on PCA (principal component analyses) and its application of Small-weak target matching.
本文对基于主成分分析的特征级图像融合及其在弱小目标匹配识别上的应用做了一定的研究和探索。
From researching on the universal principle of feature fusion of image, a new algorithm was proposed which based on the 2 dimension principal component analyses(for short 2DPCA).
针对二维主成分分析（2DPCA）提取的是人脸的全局特征，但局部特征对人脸识别的作用非常大，提出了一种基于局部特征的自适应加权2DPCA。
From researching on the universal principle of feature fusion of image, a new algorithm was proposed which based on the 2 dimension principal component analyses(for short 2DPCA).
针对二维主成分分析（2DPCA）提取的是人脸的全局特征，但局部特征对人脸识别的作用非常大，提出了一种基于局部特征的自适应加权2DPCA。
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