IEEE Trans Image Process - Super-resolution with sparse mixing estimators.

Tópicos

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Resumo

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 logN) algorithm, providing state-of-the-art numerical results.

Resumo Limpo

introduc class invers problem estim comput mix adapt famili linear estim correspond differ prior spars mix weight calcul block coeffici frame provid spars signal represent minim l norm take account signal regular block adapt direct imag interpol comput wavelet frame logn algorithm provid stateoftheart numer result

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