Face blind separation using wavelet packet independent component analysis

A novel wavelet packet based approach to Subband decomposition independent component analysis (SDICA) is proposed. The mutual information based on small cumulant is introduced to select the Subband with least dependent components. We present favorable comparisons to the WPSD ICA and other ICA algori...

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Bibliographic Details
Published in2010 International Conference on Image Analysis and Signal Processing pp. 680 - 685
Main Authors Xiaoli Huang, Huanglin Zeng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2010
Subjects
Blind Separation
Computational modeling
Discrete wavelet transforms
Face recognition
Humans
Independent component analysis
Matrix decomposition
Mutual information
Signal processing
Subband Decomposition
Wavelet analysis
Wavelet Independent Component Analysis
Wavelet packets
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Summary:A novel wavelet packet based approach to Subband decomposition independent component analysis (SDICA) is proposed. The mutual information based on small cumulant is introduced to select the Subband with least dependent components. We present favorable comparisons to the WPSD ICA and other ICA algorithm in extensive simulations. We demonstrate consistent performance in terms of accuracy and robustness as well as computational efficiency of WPSD ICA algorithm. Experimental results demonstrate that the proposed method can significantly improve the face recognition performance.
ISBN:1424455545
9781424455546
ISSN:2156-0110
DOI:10.1109/IASP.2010.5476181