Super-Resolution for Facial Images Based on Local Similarity Preserving-Reference-Cited by-同舟云学术

Super-Resolution for Facial Images Based on Local Similarity Preserving

Published:2012 Issue:3 Volume:E95-D Page:892-896
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

HE Jin-Ping¹,SU Guang-Da¹,CHEN Jian-Sheng¹

Affiliation:

1. Department of Electronic Engineering, Tsinghua University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

http://www.jstage.jst.go.jp/article/transinf/E95.D/3/E95.D_3_892/_pdf

Reference13 articles.

1. [1] J. Pu, J. Zhang, and H. Huang, “A survey of super-resolution algorithms,” J. Shandong University, vol.39, no.1, pp.27-32, 2009.

2. [2] W.T. Freeman and E.C. Pasztor, “Learning low-level vision,” ICCV, pp.1182-1189, Corfu. Greece, 1999.

3. [3] S. Baker and T. Kanade, “Hallucinating faces,” Pennsylvania, Pittsburg: The Robotics Institute, pp.1-52, Carnegie Mellon University Press, 1999.

4. Limits on super-resolution and how to break them

5. Hallucinating Face by Eigentransformation

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