Improving resolution by image registration
CVGIP: Graphical Models and Image Processing
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
A multi-frame image super-resolution method
Signal Processing
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
A super-resolution reconstruction algorithm for surveillance images
Signal Processing
Generalizing the Nonlocal-means to super-resolution reconstruction
IEEE Transactions on Image Processing
Informed Choice of the LMS Parameters in Super-Resolution Video Reconstruction Applications
IEEE Transactions on Signal Processing
Statistical Analysis of the LMS Algorithm Applied to Super-Resolution Image Reconstruction
IEEE Transactions on Signal Processing
Hallucinating face by eigentransformation
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Eigenface-domain super-resolution for face recognition
IEEE Transactions on Image Processing
Recursive high-resolution reconstruction of blurred multiframe images
IEEE Transactions on Image Processing
A Computationally Efficient Super-Resolution Algorithm for Video Processing Using Partition Filters
IEEE Transactions on Circuits and Systems for Video Technology
A Robust and Computationally Efficient Simultaneous Super-Resolution Scheme for Image Sequences
IEEE Transactions on Circuits and Systems for Video Technology
Face hallucination based on morphological component analysis
Signal Processing
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In this study, a new video super-resolution (SR) reconstruction approach using a mobile search strategy and adaptive patch size is proposed. Based on the modified nonlocal-means (NLM) SR algorithm, a mobile search strategy for motion estimation and adaptive patch size are proposed to reduce the computational complexity of the proposed approach and improve the visual quality of the final video SR reconstruction results, respectively. Based on the experimental results obtained in this study, the performance (visual quality and PSNR values) of the proposed approach is better than those of three comparison approaches.