NDLI: An innovative face image enhancement based on principle component analysis

Content Provider	Springer Nature Link
Author	Xu, Xiang Liu, Wanquan Venkatesh, Svetha
Copyright Year	2011
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.
Starting Page	259
Ending Page	267
Page Count	9
File Format	PDF
ISSN	18688071
Journal	International Journal of Machine Learning and Cybernetics
Volume Number	3
Issue Number	4
e-ISSN	1868808X
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-12-07
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	PCA Super resolution Face hallucination Control, Robotics, Mechatronics Artificial Intelligence (incl. Robotics) Statistical Physics, Dynamical Systems and Complexity Computational Intelligence Pattern Recognition Systems Biology
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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