Random adjustment - based Chaotic Metaheuristic algorithms for image contrast enhancement
Abstract: Metaheuristic
algorithm is a powerful optimization method, in which it can solve problems by
exploring the ordinarily large solution search space of these instances, that
are believed to be 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 algorithms 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. In general, the simulation
results show that the proposed methods are better than the original metaheuristic,
chaotic metaheuristic, and metaheuristic by random adjustment.
Author: Vina Ayumi, L.M. Rasdi
Rere, Mohamad Ivan Fanany, Aniati Murni Arymurthy
Journal Code: jptkomputergg170003
