Contribution to a conference proceedings/Contribution to a book FZJ-2017-03727

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Matrix-Valued Levelings for Colour Images

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2017
Springer International Publishing Cham
ISBN: 978-3-319-57239-0 (print), 978-3-319-57240-6 (electronic)

Mathematical Morphology and Its Applications to Signal and Image Processing / Angulo, Jesús (Editor) ; Cham : Springer International Publishing, 2017, Chapter 24 ; ISSN: 0302-9743=1611-3349 ; ISBN: 978-3-319-57239-0=978-3-319-57240-6
13th International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing, ISMM 2017, FontainebleauFontainebleau, France, 15 May 2017 - 17 May 20172017-05-152017-05-17
Cham : Springer International Publishing, Lecture Notes in Computer Science 10225, 296 - 308 () [10.1007/978-3-319-57240-6_24]

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Abstract: Morphological levelings represent a useful tool for the decomposition of an image into cartoon and texture components. Moreover, they can be used to construct a morphological scale space. However, the classic construction of levelings is limited to the use of grey scale images, since an ordering of pixel values is required.In this paper we propose an extension of morphological levelings to colour images. To this end, we consider the formulation of colour images as matrix fields and explore techniques based on the Loewner order for formulating morphological levelings in this setting. Using the matrix-valued colours we study realisations of levelings relying on both the completely discrete construction and the formulation using a partial differential equation. Experimental results confirm the potential of our matrix-based approaches for analysing texture in colour images and for extending the range of applications of levelings in a convenient way to colour image processing.

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Contributing Institute(s):
  1. Jülich Supercomputing Center (JSC)
Research Program(s):
  1. 511 - Computational Science and Mathematical Methods (POF3-511) (POF3-511)

Appears in the scientific report 2017
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NationallizenzNationallizenz ; SCOPUS
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 Record created 2017-05-22, last modified 2021-01-29


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