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Regularization preserving localization of close edges

Abstract : In this letter, we address the problem of the influence of neighbor edges and their effect on the edge delocalization while extracting a neighbor contour by a derivative approach. The properties to be fulfilled by the regularization operators to minimize or suppress this side effect are deduced, and the best detectors are pointed out. The study is carried out in 1-D for discrete signal. We show that among the derivative filters, one of them can correctly detect our model edges without being influenced by a neighboring transition, whatever their separation distance is and their respective amplitude is. A model of contour and close transitions is presented and used throughout this letter. The noise effect on the edge delocalization is recalled through one of the Canny criteria. Different derivative filters are applied onto synthetic images, and their performances are compared.
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Soumis le : samedi 16 avril 2011 - 07:29:10
Dernière modification le : vendredi 5 août 2022 - 14:54:00



Olivier Laligant, Frederic Truchetet, Fabrice Meriaudeau. Regularization preserving localization of close edges. IEEE Signal Processing Letters, 2007, 14 (3), pp.185-188. ⟨10.1109/LSP.2006.884030⟩. ⟨hal-00586481⟩



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