Riemannian mathematical morphology

被引:9
|
作者
Angulo, Jesus [1 ]
Velasco-Forero, Santiago [2 ]
机构
[1] MINES ParisTech, CMM, F-77305 Fontainebleau, France
[2] Natl Univ Singapore, Dept Math, Singapore 117548, Singapore
关键词
Mathematical morphology; Nonlinear manifold image processing; Riemannian images; Riemannian image embedding; Riemannian structuring function; Morphological processing of surfaces; REGULARIZATION;
D O I
10.1016/j.patrec.2014.05.015
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper introduces mathematical morphology operators for real-valued images whose support space is a Riemannian manifold. The starting point consists in replacing the Euclidean distance in the canonical quadratic structuring function by the Riemannian distance used for the adjoint dilation/erosion. We then extend the canonical case to a most general framework of Riemannian operators based on the notion of admissible Riemannian structuring function. An alternative paradigm of morphological Riemannian operators involves an external structuring function which is parallel transported to each point on the manifold. Besides the definition of the various Riemannian dilation/erosion and Riemannian opening/closing, their main properties are studied. We show also how recent results on Lasry-Lions regularization can be used for non-smooth image filtering based on morphological Riemannian operators. Theoretical connections with previous works on adaptive morphology and manifold shape morphology are also considered. From a practical viewpoint, various useful image embedding into Riemannian manifolds are formalized, with some illustrative examples of morphological processing real-valued 3D surfaces. (C) 2014 Elsevier B. V. All rights reserved.
引用
收藏
页码:93 / 101
页数:9
相关论文
共 50 条
  • [1] Hypercomplex Mathematical Morphology
    Angulo, Jesus
    JOURNAL OF MATHEMATICAL IMAGING AND VISION, 2011, 41 (1-2) : 86 - 108
  • [2] Hypercomplex Mathematical Morphology
    Jesús Angulo
    Journal of Mathematical Imaging and Vision, 2011, 41 : 86 - 108
  • [3] Classification by mathematical morphology
    Pina, P
    Barata, T
    IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES, 2003, : 3516 - 3518
  • [4] Learnable Empirical Mode Decomposition based on Mathematical Morphology
    Velasco-Forero, Santiago
    Pages, R.
    Angulo, Jesus
    SIAM JOURNAL ON IMAGING SCIENCES, 2022, 15 (01): : 23 - 44
  • [5] Quantitative Analysis on Mathematical Morphology
    Wang, Junping
    Pan, Yiping
    Li, Yanbo
    Zhao, Lulu
    PROCEEDINGS OF 2018 12TH IEEE INTERNATIONAL CONFERENCE ON ANTI-COUNTERFEITING, SECURITY, AND IDENTIFICATION (ASID), 2018, : 103 - 106
  • [6] General sweep mathematical morphology
    Shih, FY
    Gaddipati, V
    PATTERN RECOGNITION, 2003, 36 (07) : 1489 - 1500
  • [7] Cartograms via mathematical morphology
    Sagar, B. S. Daya
    INFORMATION VISUALIZATION, 2014, 13 (01) : 42 - 58
  • [8] Compensatory fuzzy mathematical morphology
    Bouchet, Agustina
    Pastore, Juan I.
    Brun, Marcel
    Ballarin, Virginia L.
    SIGNAL IMAGE AND VIDEO PROCESSING, 2017, 11 (06) : 1065 - 1072
  • [9] FUZZY CONNECTIVITY AND MATHEMATICAL MORPHOLOGY
    BLOCH, I
    PATTERN RECOGNITION LETTERS, 1993, 14 (06) : 483 - 488
  • [10] Fuzzy soft mathematical morphology
    Gasteratos, A
    Andreadis, I
    Tsalides, P
    IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING, 1998, 145 (01): : 41 - 49