A New Algorithm for Super-Resolution from Image Sequences
CAIP '01 Proceedings of the 9th International Conference on Computer Analysis of Images and Patterns
Super-resolution reconstruction of image sequence using multiple motion estimation fusion
Journal of Computer Science and Technology
A two-step neural-network based algorithm for fast image super-resolution
Image and Vision Computing
EURASIP Journal on Advances in Signal Processing
Sharpness preserving image enlargement by using self-decomposed codebook and Mahalanobis distance
Image and Vision Computing
A multi-frame image super-resolution method
Signal Processing
Low-power content-based video acquisition for super-resolution enhancement
IEEE Transactions on Multimedia - Special section on communities and media computing
Adaptive large scale artifact reduction in edge-based image super-resolution
SIP '07 Proceedings of the Ninth IASTED International Conference on Signal and Image Processing
Fast MAP-based multiframe super-resolution image reconstruction
Image and Vision Computing
Analysis of multiframe super-resolution reconstruction for image anti-aliasing and deblurring
Image and Vision Computing
Simultaneous enhancement of spatial resolution and dynamic range from multiple images
CGIM '07 Proceedings of the Ninth IASTED International Conference on Computer Graphics and Imaging
Video enhancement using a robust iterative SRR based on Leclerc stochastic estimation
ISCIT'09 Proceedings of the 9th international conference on Communications and information technologies
Robust mean super-resolution for less cooperative NIR iris recognition at a distance and on the move
Proceedings of the 2010 Symposium on Information and Communication Technology
SuperResolution image reconstruction using a hybrid bayesian approach
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Morphable model space based face super-resolution reconstruction and recognition
Image and Vision Computing
Feature-domain super-resolution for iris recognition
Computer Vision and Image Understanding
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In this paper, we propose to improve the POCS-based super-resolution reconstruction (SRR) methods in two ways. First, the discretization of the continuous image formation model is improved to explicitly allow for higher order interpolation methods to be used. Second, the constraint sets are modified to reduce the amount of edge ringing present in the high resolution image estimate. This effectively regularizes the inversion process