We present a new passive autofocusing algorithm based on fuzzy transforms. In a previous work (Roh et al., 2016) a localized variation of the variance operator is proposed based on the concept of fuzzy subspaces of the image: Fuzzy C-Means and Conditional Fuzzy C-Means algorithms are applied for detecting the fuzzy subspaces as clusters. The direct fuzzy transform is used for extracting the mean values of the pixels in a fuzzy subspace. We propose a new approach based on the Fuzzy Generalized Fuzzy C-Means algorithm where the number of fuzzy subspaces is obtained by using the Partition Coefficient and Exponential Separation validity index. We show that the proposed method has major robustness with respect to other algorithms known in literature.

PASSIVE IMAGE AUTOFOCUS BY USING DIRECT FUZZY TRANSFORM

ferdinando di martino;salvatore sessa
2019

Abstract

We present a new passive autofocusing algorithm based on fuzzy transforms. In a previous work (Roh et al., 2016) a localized variation of the variance operator is proposed based on the concept of fuzzy subspaces of the image: Fuzzy C-Means and Conditional Fuzzy C-Means algorithms are applied for detecting the fuzzy subspaces as clusters. The direct fuzzy transform is used for extracting the mean values of the pixels in a fuzzy subspace. We propose a new approach based on the Fuzzy Generalized Fuzzy C-Means algorithm where the number of fuzzy subspaces is obtained by using the Partition Coefficient and Exponential Separation validity index. We show that the proposed method has major robustness with respect to other algorithms known in literature.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/692569
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 1
social impact