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An innovative face image enhancement based on principle component analysis

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Abstract

In this paper, we propose an innovative face hallucination approach based on principle component analysis (PCA) and residue technique. First, the relationship of projection coefficients between high-resolution and low-resolution images using PCA is investigated. Then based on this analysis, a high resolution global face image is constructed from a low resolution one. Next a high-resolution residue is derived based on the similarity between the projections on high and low resolution residue training sets. Finally by combining the global face and residue in high resolution, a high resolution face image is generated. Also the recursive and two-stage methods are proposed, which improve the results of face image enhancement. Extensive experiments validate the proposed approaches.

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Authors and Affiliations

  1. Department of Computing, Curtin University, Perth, WA, Australia

    Xiang Xu, Wanquan Liu & Svetha Venkatesh

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  1. Xiang Xu
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  2. Wanquan Liu
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  3. Svetha Venkatesh
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Correspondence to Wanquan Liu.

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Xu, X., Liu, W. & Venkatesh, S. An innovative face image enhancement based on principle component analysis. Int. J. Mach. Learn. & Cyber. 3, 259–267 (2012). https://doi.org/10.1007/s13042-011-0060-x

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