Authors:
Abdu Rahiman V.
and
Jiji C. V.
Affiliation:
College of Engineering, University of Kerala, India
Keyword(s):
Face Hallucination, Principal Component Analysis, Wavelets, Eigen Images.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Enhancement and Restoration
;
Image Formation and Preprocessing
;
Image Quality
Abstract:
The term face hallucination stands for recognition based super resolution of face images to improve the spatial resolution. In this paper, we propose two face hallucination algorithms based on principal component analysis (PCA) in the wavelet transform domain. In the spatial domain, the PCA based super resolution algorithm; a low resolution (LR) observation is represented as the linear combination of LR images in an image database. Super resolved image is obtained as the linear combination of the corresponding high resolution (HR) images in the database. In the first approach proposed in this paper, PCA based hallucination algorithm is applied to the wavelet coefficients of face image. The hallucinated face image is reconstructed from the super resolved wavelet coefficients. In second method, face image is split in to four sub images and the first method is separately applied to three textured regions. Fourth region, which is relatively smooth, is interpolated using standard interpol
ation techniques. We compare the performance of the two proposed algorithms with their spatial domain counter parts. The proposed method shows significant improvement over the spatial domain approaches.
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