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Super-Resolution With Sparse Mixing Estimators | IEEE Journals & Magazine | IEEE Xplore

Super-Resolution With Sparse Mixing Estimators


Abstract:

We introduce a class of inverse problem estimators computed by mixing adaptively a family of linear estimators corresponding to different priors. Sparse mixing weights ar...Show More

Abstract:

We introduce a class of inverse problem estimators computed by mixing adaptively a family of linear estimators corresponding to different priors. Sparse mixing weights are calculated over blocks of coefficients in a frame providing a sparse signal representation. They minimize an l1 norm taking into account the signal regularity in each block. Adaptive directional image interpolations are computed over a wavelet frame with an O(N log N) algorithm, providing state-of-the-art numerical results.
Published in: IEEE Transactions on Image Processing ( Volume: 19, Issue: 11, November 2010)
Page(s): 2889 - 2900
Date of Publication: 06 May 2010

ISSN Information:

PubMed ID: 20457549

References

References is not available for this document.