Detail publikačního výsledku

Multi-purpose Image Filter Evolution Using Cellular Automata and Function-Based Conditional Rules

BIDLO, M.; SARANOVÁ, I.

Originální název

Multi-purpose Image Filter Evolution Using Cellular Automata and Function-Based Conditional Rules

Anglický název

Multi-purpose Image Filter Evolution Using Cellular Automata and Function-Based Conditional Rules

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

A variant of Evolution Strategy is applied to design transition functions for cellular automata using a newly proposed representation denominated as function-based conditional rules. The goal is to train the cellular automata to eliminate various types of noise from digital images using a single evolved function. The proposed method allowed us to design high-quality filters working with 5-pixel neighbourhood only which is substantially more efficient than 9 or even 25 pixels used by most of the existing filters. We show that salt-and-pepper noise and random noise of several tens of percentages intensity may successfully be treated. Moreover, the resulting filters have also shown an ability to filter impulse-burst noise for which they were not trained explicitly. Finally we demonstrate that our filters are capable to tackle with up to 40\% random noise where most of existing filters fail.

Anglický abstrakt

A variant of Evolution Strategy is applied to design transition functions for cellular automata using a newly proposed representation denominated as function-based conditional rules. The goal is to train the cellular automata to eliminate various types of noise from digital images using a single evolved function. The proposed method allowed us to design high-quality filters working with 5-pixel neighbourhood only which is substantially more efficient than 9 or even 25 pixels used by most of the existing filters. We show that salt-and-pepper noise and random noise of several tens of percentages intensity may successfully be treated. Moreover, the resulting filters have also shown an ability to filter impulse-burst noise for which they were not trained explicitly. Finally we demonstrate that our filters are capable to tackle with up to 40\% random noise where most of existing filters fail.

Klíčová slova

cellular automaton, image filter, evolutionary algorithm, conditionally matching rule

Klíčová slova v angličtině

cellular automaton, image filter, evolutionary algorithm, conditionally matching rule

Autoři

BIDLO, M.; SARANOVÁ, I.

Vydáno

18.04.2025

Nakladatel

Springer Nature Switzerland AG

Místo

Trieste

ISBN

978-3-031-90064-8

Kniha

Applications of Evolutionary Computation: 28th European Conference, EvoApplications 2025, Held as Part of EvoStar 2025, Trieste, Italy, April 23-25, 2025, Proceedings, Part II

Edice

Lecture Notes in Computer Science

Svazek

15613

Strany od

457

Strany do

472

Strany počet

16

URL

https://link.springer.com/chapter/10.1007/978-3-031-90065-5_28

BibTex

@inproceedings{BUT193304,
  author="Michal {Bidlo} and Ivana {Saranová}",
  title="Multi-purpose Image Filter Evolution Using Cellular Automata and Function-Based Conditional Rules",
  booktitle="Applications of Evolutionary Computation: 28th European Conference, EvoApplications 2025, Held as Part of EvoStar 2025, Trieste, Italy, April 23-25, 2025, Proceedings, Part II",
  year="2025",
  series="Lecture Notes in Computer Science",
  volume="15613",
  pages="457--472",
  publisher="Springer Nature Switzerland AG",
  address="Trieste",
  doi="10.1007/978-3-031-90065-5\{_}28",
  isbn="978-3-031-90064-8",
  url="https://link.springer.com/chapter/10.1007/978-3-031-90065-5_28"
}