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Image Reconstruction Through Polyfiltered Variation Minimization, Michael Hagen

Master's Theses and Doctoral Dissertations

There has been considerable interest in reconstruction of remotely sensed imagery from incomplete frequency measurements for some time now. Given the nature of the collection process, it may be that portions of the spectrum are either missing or corrupted such that one is left with an incomplete representation of the original image. The advances in both the theory and available software for sparse signal reconstruction through function minimization make it an attractive approach for recreating the missing frequency data. It is the aim of this thesis to generalize the reconstruction technique known as Total Variation (TV) minimization from a signal …