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Hallucinating Faces: Global Linear Modal Based Super-Resolution and Position Based Residue Compensation

  • Xiang Ma
  • Junping Zhang
  • Chun Qi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5716)

Abstract

A learning-based face hallucination method is proposed in this paper for the reconstruction of a high-resolution face image from a low-resolution observation based on a set of high- and low-resolution training image pairs. The proposed global linear modal based super-resolution estimates the optimal weights of all the low-resolution training images and a high-resolution image is obtained by applying the estimated weights to the high-resolution space. Then, we propose a position based local residue compensation algorithm to better recover subtle details of face. Experiments demonstrate that our method has advantage over some established methods.

Keywords

Face hallucination Super-resolution Residue compensation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Xiang Ma
    • 1
  • Junping Zhang
    • 2
  • Chun Qi
    • 1
  1. 1.School of Electronics& Information EngineeringXi’an Jiaotong UniversityXi’anChina
  2. 2.Department of Computer Science and EngineeringFudan UniversityShanghaiChina

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