IEEE Trans Image Process - Generalized higher degree total variation (HDTV) regularization.

Tópicos

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Resumo

We introduce a family of novel image regularization penalties called generalized higher degree total variation (HDTV). These penalties further extend our previously introduced HDTV penalties, which generalize the popular total variation (TV) penalty to incorporate higher degree image derivatives. We show that many of the proposed second degree extensions of TV are special cases or are closely approximated by a generalized HDTV penalty. Additionally, we propose a novel fast alternating minimization algorithm for solving image recovery problems with HDTV and generalized HDTV regularization. The new algorithm enjoys a tenfold speed up compared with the iteratively reweighted majorize minimize algorithm proposed in a previous paper. Numerical experiments on 3D magnetic resonance images and 3D microscopy images show that HDTV and generalized HDTV improve the image quality significantly compared with TV.

Resumo Limpo

introduc famili novel imag regular penalti call general higher degre total variat hdtv penalti extend previous introduc hdtv penalti general popular total variat tv penalti incorpor higher degre imag deriv show mani propos second degre extens tv special case close approxim general hdtv penalti addit propos novel fast altern minim algorithm solv imag recoveri problem hdtv general hdtv regular new algorithm enjoy tenfold speed compar iter reweight major minim algorithm propos previous paper numer experi d magnet reson imag d microscopi imag show hdtv general hdtv improv imag qualiti signific compar tv

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