Spatially variant morphological restoration and skeleton representation

Nidhal Bouaynaya, Mohammed Charif-Chefchaouni, Dan Schonfeld

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

The theory of spatially variant (SV) mathematical morphology is used to extend and analyze two important image processing applications: morphological image restoration and skeleton representation of binary images. For morphological image restoration, we propose the SV alternating sequential filters and SV median filters. We establish the relation of SV median filters to the basic SV morphological operators (i.e., SV erosions and SV dilations). For skeleton representation, we present a general framework for the SV morphological skeleton representation of binary images. We study the properties of the SV morphological skeleton representation and derive conditions for its invertibility. We also develop an algorithm for the implementation of the SV morphological skeleton representation of binary images. The latter algorithm is based on the optimal construction of the SV structuring element mapping designed to minimize the cardinality of the SV morphological skeleton representation. Experimental results show the dramatic improvement in the performance of the SV morphological restoration and SV morphological skeleton representation algorithms in comparison to their translation-invariant counterparts.

Original languageEnglish (US)
Pages (from-to)3579-3591
Number of pages13
JournalIEEE Transactions on Image Processing
Volume15
Issue number11
DOIs
StatePublished - Nov 2006
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design

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