Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images
@article{Elad1997RestorationOA, title={Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images}, author={Michael Elad and Arie Feuer}, journal={IEEE transactions on image processing : a publication of the IEEE Signal Processing Society}, year={1997}, volume={6 12}, pages={ 1646-58 }, url={https://api.semanticscholar.org/CorpusID:1724361} }
A hybrid method combining the simplicity of theML and the incorporation of nonellipsoid constraints is presented, giving improved restoration performance, compared with the ML and the POCS approaches.
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Topics
Superresolution Restoration (opens in a new tab)Projection Onto Convex Sets (opens in a new tab)Blurring (opens in a new tab)Optimization Problem (opens in a new tab)Downsampling (opens in a new tab)Super-Resolution (opens in a new tab)Under-sampling (opens in a new tab)Maximum Likelihood (opens in a new tab)
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