1 July 2003 Image resampling and constraint formulation for multiframe superresolution restoration
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Abstract
Multi-frame super-resolution restoration algorithms commonly utilize a linear observation model relating the recorded images to the unknown restored image estimates. Working within this framework, we demonstrate a method for generalizing the observation model to incorporate spatially varying point spread functions and general motion fields. The method utilizes results from image resampling theory which is shown to have equivalences with the multi-frame image observation model used in super-resolution restoration. An algorithm for computing the coefficients of the spatially varying observation filter is developed. Examples of the application of the proposed method are presented.
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Sean Borman, Sean Borman, Robert L. Stevenson, Robert L. Stevenson, } "Image resampling and constraint formulation for multiframe superresolution restoration", Proc. SPIE 5016, Computational Imaging, (1 July 2003); doi: 10.1117/12.483906; https://doi.org/10.1117/12.483906
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