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Random adjustment - based Chaotic Metaheuristic algorithms for image contrast enhancement

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 10 No. 2 (2017) · pp. 67–76

DOI
10.21609/jiki.v10i2.375
ISSN
2502-9274, 2088-7051
Published
2017-06-30
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

Metaheuristic algorithm is a powerful optimization method, in which it can solve problemsby exploring the ordinarily large solution search space of these instances, that are believed tobe hard in general. However, the performances of these algorithms signicantly depend onthe setting of their parameter, while is not easy to set them accurately as well as completelyrelying on the problem's characteristic. To ne-tune the parameters automatically, manymethods have been proposed to address this challenge, including fuzzy logic, chaos, randomadjustment and others. All of these methods for many years have been developed indepen-dently for automatic setting of metaheuristic parameters, and integration of two or more ofthese methods has not yet much conducted. Thus, a method that provides advantage fromcombining chaos and random adjustment is proposed. Some popular metaheuristic algo-rithms are used to test the performance of the proposed method, i.e. simulated annealing,particle swarm optimization, dierential evolution, and harmony search. As a case study ofthis research is contrast enhancement for images of Cameraman, Lena, Boat and Rice. Ingeneral, the simulation results show that the proposed methods are better than the originalmetaheuristic, chaotic metaheuristic, and metaheuristic by random adjustment.

Keywords

Collaboration network of the authors

37 authors · 86 co-authorship links · 40 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • University of Indonesia
  • Mercu Buana University
  • University of Reading
  • Universitas Gadjah Mada
  • Universitas Stikubank
  • RWTH Aachen University
  • University of Auckland
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Ida NurhaidaMercu Buana University4
Remmy A. M. ZenMercu Buana University3
Ruli ManurungAffiliation unknown2
Hong WeiUniversity of Reading2
Agus HarjokoUniversitas Gadjah Mada2
Edi WinarkoUniversitas Gadjah Mada2
Edy WinarnoUniversitas Stikubank2
Devi FitrianahMercu Buana University2
Edward CitrahadiAffiliation unknown1
Tieta AntarestiUniversity of Indonesia1
Yohanes GultomUniversity of Indonesia1
Rian Josua MasikomeRWTH Aachen University1
Muhamad SolehUniversity of Indonesia1
Sesa WigunaUniversity of Auckland1
Adila Alfa KrisnadhiUniversity of Indonesia1
Ken SasongkoUniversity of Indonesia1
Yuni ArtiUniversity of Indonesia1
Hans Timothy WijayaUniversity of Indonesia1
Juan Thomas WijayaUniversity of Indonesia1
Yohanes Fridolin HestrioUniversity of Indonesia1
Bayu Satria PersadaUniversity of Indonesia1
Frederic Morado SaragihUniversity of Indonesia1
Muhammad Yusuf KardawiUniversity of Indonesia1
Wisnu Aryo JatmikoUniversity of Indonesia1
Herwanto HerwantoAffiliation unknown1
Handrie NoprissonMercu Buana University1
Hong WeiUniversity of Reading1
Achmad Nizar HidayantoUniversity of Indonesia1
Hisyam FahmiUniversitas Islam Negeri Maulana Malik Ibrahim1
Pang‐Ning TanMichigan State University1
Fitri YakubUniversity of Technology Malaysia1
Inge DhamantiLa Trobe University1
Benny TjahjonoCoventry (United Kingdom)1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://jiki.cs.ui.ac.id/index.php/jiki/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Random adjustment - based Chaotic Metaheuristic algorithms for image contrast enhancement</dc:title>
	<dc:creator>Ayumi, Vina</dc:creator>
	<dc:creator>Rere, L.M. Rasdi</dc:creator>
	<dc:creator>Fanany, Mohamad Ivan</dc:creator>
	<dc:creator>Arymurthy, Aniati Murni</dc:creator>
	<dc:subject xml:lang="en-US">metaheuristic</dc:subject>
	<dc:subject xml:lang="en-US">chaos</dc:subject>
	<dc:subject xml:lang="en-US">random adjustment</dc:subject>
	<dc:subject xml:lang="en-US">image contrast enhancement</dc:subject>
	<dc:description xml:lang="en-US">Metaheuristic algorithm is a powerful optimization method, in which it can solve problemsby exploring the ordinarily large solution search space of these instances, that are believed tobe hard in general. However, the performances of these algorithms signicantly depend onthe setting of their parameter, while is not easy to set them accurately as well as completelyrelying on the problem's characteristic. To ne-tune the parameters automatically, manymethods have been proposed to address this challenge, including fuzzy logic, chaos, randomadjustment and others. All of these methods for many years have been developed indepen-dently for automatic setting of metaheuristic parameters, and integration of two or more ofthese methods has not yet much conducted. Thus, a method that provides advantage fromcombining chaos and random adjustment is proposed. Some popular metaheuristic algo-rithms are used to test the performance of the proposed method, i.e. simulated annealing,particle swarm optimization, dierential evolution, and harmony search. As a case study ofthis research is contrast enhancement for images of Cameraman, Lena, Boat and Rice. Ingeneral, the simulation results show that the proposed methods are better than the originalmetaheuristic, chaotic metaheuristic, and metaheuristic by random adjustment.</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2017-06-30</dc:date>
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	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/375</dc:identifier>
	<dc:identifier>10.21609/jiki.v10i2.375</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 10 No. 2 (2017): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 67-76</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v10i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/375/373</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2017 Jurnal Ilmu Komputer dan Informasi</dc:rights>
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