Adaptive filter theory
Sub-pixel Bayesian estimation of albedo and height
International Journal of Computer Vision
Extraction of high-resolution frames from video sequences
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Superresolution restoration of an image sequence: adaptive filtering approach
IEEE Transactions on Image Processing
Limits on Super-Resolution and How to Break Them
IEEE Transactions on Pattern Analysis and Machine Intelligence
A super-resolution method with EWA
Journal of Computer Science and Technology
Super-resolution reconstruction of image sequence using multiple motion estimation fusion
Journal of Computer Science and Technology
A multimodal approach to time-invariant scene retrieval from single overhead image
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Proceedings of the 2006 international conference on Wireless communications and mobile computing
Optical flow based super-resolution: A probabilistic approach
Computer Vision and Image Understanding
Adaptive outlier rejection in image super-resolution
EURASIP Journal on Applied Signal Processing
Video-to-video dynamic super-resolution for grayscale and color sequences
EURASIP Journal on Applied Signal Processing
Low-cost super-resolution algorithms implementation over a HW/SW video compression platform
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Advances in Signal Processing
2D motion aided sampling and reconstruction
Journal of Visual Communication and Image Representation
Neighbor embedding based super-resolution algorithm through edge detection and feature selection
Pattern Recognition Letters
Video Super Resolution Using Duality Based TV-L1 Optical Flow
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Technical Section: Hyper-Resolution: Image detail reconstruction through parametric edges
Computers and Graphics
Registration errors: are they always bad for super-resolution?
IEEE Transactions on Signal Processing
Coupled Metric Learning for Face Recognition with Degraded Images
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Analysis of multiframe super-resolution reconstruction for image anti-aliasing and deblurring
Image and Vision Computing
Hallucinating face by position-patch
Pattern Recognition
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
High-zoom video hallucination by exploiting spatio-temporal regularities
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Image super-resolution by textural context constrained visual vocabulary
Image Communication
A Comprehensive Survey to Face Hallucination
International Journal of Computer Vision
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In an earlier work, we have introduced the problem of reconstructing a super-resolution image sequence from a given low resolution sequence. We proposed two iterative algorithms, the R-SD and the R-LMS, to generate the desired image sequence. These algorithms assume the knowledge of the blur, the down-sampling, the sequences motion, and the measurements noise characteristics, and apply a sequential reconstruction process. It has been shown that the computational complexity of these two algorithms makes both of them practically applicable. In this paper, we rederive these algorithms as approximations of the Kalman filter and then carry out a thorough analysis of their performance. For each algorithm, we calculate a bound on its deviation from the Kalman filter performance. We also show that the propagated information matrix within the R-SD algorithm remains sparse in time, thus ensuring the applicability of this algorithm. To support these analytical results we present some computer simulations on synthetic sequences, which also show the computational feasibility of these algorithms.