An innovative face image enhancement based on principle component analysis
|dc.identifier.citation||Xu, X. and Liu, W. and Venkatesh, S. 2012. An innovative face image enhancement based on principle component analysis. International Journal of Machine Learning and Cybernetics. 3 (4): pp. 259-267.|
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.
|dc.title||An innovative face image enhancement based on principle component analysis|
|dcterms.source.title||International Journal of Machine Learning and Cybernetics|
|curtin.department||Department of Computing|
|curtin.accessStatus||Fulltext not available|