Passive image autofocus by using direct fuzzy transform
by Ferdinando Di Martino; Salvatore Sessa
International Journal of Computational Science and Engineering (IJCSE), Vol. 20, No. 2, 2019

Abstract: We present a new passive autofocusing algorithm based on fuzzy transforms. In a previous work (Roh et al., 2016) a localised 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 generalised 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.

Online publication date: Fri, 29-Nov-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Science and Engineering (IJCSE):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com