Title: Pattern Spectra from Partition Pyramids and Hierarchies
Citation: Mathematical Morphology and Its Application to Signal and Image Processing - ISBN 978-3-642-21568-1, ISSN 0302-9743 vol. 6671 p. 108-119
Publisher: Springer Verlag
Publication Year: 2011
JRC N°: JRC62785
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC62785
DOI: 10.1007/978-3-642-21569-8_10
Type: Articles in periodicals and books
Abstract: Pattern spectra are image histograms that feature the distribution of image details with respect to some attribute measure. They are typically computed from granulometries which provide the necessary set of conditions to ensure a notion of order. In this paper we investigate means of describing order in the absence of operators and thus granulometries. We provide a case study on the multi-scale segmentation transform of the image domain to sets of single linkage connected components based on some dissimilarity measure. The nesting of consequent partitions, computed along the dissimilarity measure range, leads to the notion of partition pyramids. These are multi-scale partition representation structures characterised by large redundancies due to component replicas at various scales. We constrain this to the compact representation of partition hierarchies based on which we can compute efficiently pattern spectra and other filtering/segmentation transforms.
JRC Directorate:Space, Security and Migration

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