New methods for L_2-L_0 minimization and their applications to 2D Single-Molecule Localization Microscopy

Arne Bechensteen 1 Laure Blanc-Féraud 1 Gilles Aubert 2
1 MORPHEME - Morphologie et Images
CRISAM - Inria Sophia Antipolis - Méditerranée , IBV - Institut de Biologie Valrose : U1091, Laboratoire I3S - SIS - Signal, Images et Systèmes
Abstract : We present in this paper a biconvex reformulation of an L_2 − L_0 problem composed of a least-square data term plus a sparsity term introduced as a constraint or a penalization. Minimization algorithms are derived and compared with the state of the art in L_2 − L_0 minimization by relaxation or deep learning. Application results are shown on Single-Molecule Localization Microscopy.
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Submitted on : Tuesday, April 23, 2019 - 4:54:34 PM
Last modification on : Thursday, April 25, 2019 - 1:36:55 AM

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Arne Bechensteen, Laure Blanc-Féraud, Gilles Aubert. New methods for L_2-L_0 minimization and their applications to 2D Single-Molecule Localization Microscopy. IEEE International Symposium on Biomedical Imaging 2019, Apr 2019, Venice, Italy. ⟨hal-02107577⟩

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