Improving image resolution using subpixel motion
Pattern Recognition Letters
Improving resolution by image registration
CVGIP: Graphical Models and Image Processing
Is Super-Resolution with Optical Flow Feasible?
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Image Mosaicing and Super-Resolution (Cphc/Bcs Distinguished Dissertations.)
Image Mosaicing and Super-Resolution (Cphc/Bcs Distinguished Dissertations.)
Superresolution of License Plates in Real Traffic Videos
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Image Processing
Fast and robust multiframe super resolution
IEEE Transactions on Image Processing
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Human-centred multimedia applications are a set of activities that human directly interact with multimedia, which consists of different forms. Within all multimedia, video is an ultimate resource, by which people could obtain sensory information. Since limitations on the capacity of imaging devices as well as shooting conditions, we cannot usually acquire high quality video records that desired. This problem could be addressed by super-resolution. We propose a novel scheme in the present paper for super-resolution problem, and make three contributions: (1) on the stage of image registration according to previous approaches, the reference image is picked out through observing or randomly. We utilise a simple but efficient method to select the base image; (2) a median-value image, rather than the average image used previously, is adopted as the initialization for estimate of super-resolution; (3) we adapt the traditional Cross Validation (CV) to a weighted version in the process of learning parameters from input observations. Experiments on synthetic and real data are provided to illustrate the effectiveness of our approach.