Abstract
A new morphological operator, namely RORPO (Ranking Orientation Responses of Path Operators), was recently introduced as a semi-global, morphological alternative to the local, Hessian-based operators for thin structure filtering in 3D images. In this context, a previous study has already provided experimental proof of its relevance by comparison to such differential operators. In this article, we present a methodological study of RORPO, which completes the presentation of this new morphological filter. In particular, we expose the motivations of RORPO with respect to previous morphological strategies; we present algorithmic developments of this filter and the underlying robust path operator; and we discuss computational issues related to parametricity and time efficiency. We conclude this study by a discussion on the methodological and applicative potentiality of RORPO in various fields of image processing and analysis.
This research was funded by the French Agence Nationale de la Recherche (Grant Agreements ANR-10-BLAN-0205 and ANR-12-MONU-0010) and through Programme d’Investissements d’Avenir (LabEx Bézout, ANR-10-LABX-58).
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Merveille, O., Talbot, H., Najman, L., Passat, N. (2015). Ranking Orientation Responses of Path Operators: Motivations, Choices and Algorithmics. In: Benediktsson, J., Chanussot, J., Najman, L., Talbot, H. (eds) Mathematical Morphology and Its Applications to Signal and Image Processing. ISMM 2015. Lecture Notes in Computer Science(), vol 9082. Springer, Cham. https://doi.org/10.1007/978-3-319-18720-4_53
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DOI: https://doi.org/10.1007/978-3-319-18720-4_53
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