An innovative face image enhancement based on principle component analysis

被引:16
作者
Xu, Xiang [1 ]
Liu, Wanquan [1 ]
Venkatesh, Svetha [1 ]
机构
[1] Curtin Univ, Dept Comp, Perth, WA 6845, Australia
关键词
PCA; Super resolution; Face hallucination; HALLUCINATING FACES; SUPERRESOLUTION; RECONSTRUCTION; RECOGNITION; INTERPOLATION; EIGENFACES;
D O I
10.1007/s13042-011-0060-x
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:259 / 267
页数:9
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