A Fuzzification of Morphological Wavelets Based on Fuzzy Relational Calculus and its Application to Image Compression/Reconstruction

Hajime Nobuhara, Kaoru Hirota

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

A new style of fuzzy wavelets is proposed by the fuzzification of morphological wavelets. Due to the correspondence of the morphological wavelets operations and fuzzy relational ones, wavelets analysis/synthesis schemes can be formulated based on fuzzy relational calculus. To enable efficient image compression/reconstruction, the concept of the alpha-band which is an alpha-cut generalization, is also proposed for thresholding wavelets. In an image compression/reconstruction experiment using test images extracted from the Standard Image DataBAse (SIDBA), it is confirmed that the root mean square error (RMSE) of the proposed soft thresholding is decreased to 87.3% of conventional hard thresholding, when the original image is “Lenna.”

Original languageEnglish
Pages (from-to)373-378
Number of pages6
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Volume8
Issue number4
DOIs
Publication statusPublished - Jul 2004
Externally publishedYes

Keywords

  • fuzzy relation
  • image compression/reconstruction
  • morphological wavelets
  • ordered structure

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