2010-01-20
本文讨论了一种基于核主成分分析的人脸图像去噪方法。首先利用核主成分分析，对训练样本做特征提取，舍弃在特征空间中投影方差小的特征，得到主分量。然后利用主分量按照以特征空间中重构误差最小为原则的降噪算法对模式进行重构,从而达到人脸图像降噪的目的。对算法的实现表明，在最优核参数的条件下，噪声的类型、噪声源的多少对降噪效果影响不大。从而证明了该方法的可操作性和有效性。
中国矿业大学信息与电气工程学院,中国矿业大学信息与电气工程学院,中国矿业大学信息与电气工程学院
Yin Zheng,Bin Shen,Xiaofeng Yang,Wanli Ma,Bao-Di Liu,\Yu-Jin Zhang
Furthermore, Kernel PCA (KPCA) is proposed to capture the nonlinear structure of the data in the projected
2015-01-06
This work was supported by National Nature Science Foundation (NNSF: 61171118) and Specialized Research Fund for the Doctoral Program of Highe（SRFDP-20110002110057）
Department of Electronic Engineering, Tsinghua University, Beijing, China 10084 , Department of Computer Science, Purdue University, West Lafayette, IN, USA, 47907,, Department of Electronic Engineering, Tsinghua University, Beijing, China 10084 , Department of Electronic Engineering, Tsinghua University, Beijing, China 10084 , Department of Electronic Engineering, Tsinghua University, Beijing, China 10084 , Department of Electronic Engineering, Tsinghua University, Beijing, China 10084
Tian Shiyi,Chen Min,Deng Shaoping
(Kernel PCA), Locally linear Embedding (LLE) and Sammon mapping were studied about the data processing
2012-02-10
Specialized Research Fund for the Doctoral Program of Higher Education（No. 200803530002）
School of Food Science and Biotechnology (SFSB), Zhejiang Gongshang University,School of Food Science and Biotechnology (SFSB), Zhejiang Gongshang University,School of Food Science and Biotechnology (SFSB), Zhejiang Gongshang University
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