On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems
Theoretical Computer Science
Example-Based Super-Resolution
IEEE Computer Graphics and Applications
Limits on Super-Resolution and How to Break Them
IEEE Transactions on Pattern Analysis and Machine Intelligence
Is Super-Resolution with Optical Flow Feasible?
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Super-Resolution from Image Sequences - A Review
MWSCAS '98 Proceedings of the 1998 Midwest Symposium on Systems and Circuits
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Face Hallucination: Theory and Practice
International Journal of Computer Vision
Example-Based Learning for Single-Image Super-Resolution
Proceedings of the 30th DAGM symposium on Pattern Recognition
Principal Component Analysis Based on L1-Norm Maximization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example-based image super-resolution with class-specific predictors
Journal of Visual Communication and Image Representation
Video Super Resolution Using Duality Based TV-L1 Optical Flow
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Image super-resolution via sparse representation
IEEE Transactions on Image Processing
Extraction of high-resolution frames from video sequences
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
A progressively predictive image pyramid for efficient lossless coding
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Fast and robust multiframe super resolution
IEEE Transactions on Image Processing
An Example-Based Face Hallucination Method for Single-Frame, Low-Resolution Facial Images
IEEE Transactions on Image Processing
From Local Pixel Structure to Global Image Super-Resolution: A New Face Hallucination Framework
IEEE Transactions on Image Processing
A survey of face hallucination
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
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In this paper, we propose a face-hallucination method, namely face hallucination based on sparse local-pixel structure. In our framework, a high resolution (HR) face is estimated from a single frame low resolution (LR) face with the help of the facial dataset. Unlike many existing face-hallucination methods such as the from local-pixel structure to global image super-resolution method (LPS-GIS) and the super-resolution through neighbor embedding, where the prior models are learned by employing the least-square methods, our framework aims to shape the prior model using sparse representation. Then this learned prior model is employed to guide the reconstruction process. Experiments show that our framework is very flexible, and achieves a competitive or even superior performance in terms of both reconstruction error and visual quality. Our method still exhibits an impressive ability to generate plausible HR facial images based on their sparse local structures.