Approximation by Shepard type pseudo-linear operators and applications to Image Processing

Barnabás Bede, Emil Daniel Schwab, Hajime Nobuhara, I. Rudas

Research output: Article

9 Citations (Scopus)

Abstract

Recently, it has been shown that sum and product are not the only operations that can be used in order to define concrete approximation operators. Several other operations provided by fuzzy sets theory can be used. In the present paper, pseudo-linear approximation operators are investigated from the practical point of view in Image Processing. We study max-min, max-product Shepard type approximation operators together with Shepard operators based on pseudo-operations generated by an increasing continuous generator. It is shown that in several cases these outperform classical approximation operators based on sum and product operations.

Original languageEnglish
Pages (from-to)21-36
Number of pages16
JournalInternational Journal of Approximate Reasoning
Volume50
Issue number1
DOIs
Publication statusPublished - jan. 2009

Fingerprint

Approximation Operators
Fuzzy set theory
Linear Operator
Mathematical operators
Image Processing
Image processing
Concretes
Approximation
Linear Approximation
Fuzzy Set Theory
Min-max
Generator
Operator

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Theoretical Computer Science
  • Applied Mathematics

Cite this

Approximation by Shepard type pseudo-linear operators and applications to Image Processing. / Bede, Barnabás; Schwab, Emil Daniel; Nobuhara, Hajime; Rudas, I.

In: International Journal of Approximate Reasoning, Vol. 50, No. 1, 01.2009, p. 21-36.

Research output: Article

Bede, Barnabás ; Schwab, Emil Daniel ; Nobuhara, Hajime ; Rudas, I. / Approximation by Shepard type pseudo-linear operators and applications to Image Processing. In: International Journal of Approximate Reasoning. 2009 ; Vol. 50, No. 1. pp. 21-36.
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