Improving resolution by image registration
CVGIP: Graphical Models and Image Processing
LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
ACM Transactions on Mathematical Software (TOMS)
Example-Based Super-Resolution
IEEE Computer Graphics and Applications
Efficient Super-Resolution and Applications to Mosaics
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Super-Resolution Enhancement of Text Image Sequences
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Superresolution-Based Enhancement of Text in Digital Video
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Super-Resolution Reconstruction of Compressed Video Based on Adaptive Quantization Constraint Set
ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
A computationally efficient superresolution image reconstruction algorithm
IEEE Transactions on Image Processing
Super-resolution still and video reconstruction from MPEG-coded video
IEEE Transactions on Circuits and Systems for Video Technology
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The goal of multi-frame image super-resolution is to use information from low-resolution images to construct highresolution images. Existing construction techniques are highly sensitive to prominent large scale artifacts in the low-resolution images. This paper presents a novel, adaptive approach to large scale artifact reduction in multiframe image super-resolution. The proposed method adaptively selects information from the low-resolution images such that prominent large scale artifacts are rejected during the construction of high-resolution images. An efficient super-resolution algorithm that utilizes the proposed technique with an edge-adaptive constraint relaxation is introduced. Experimental results demonstrate that the proposed algorithm improves the visual quality of the constructed high-resolution images when prominent large scale artifacts exist.