Open Access
ARTICLE
The Implementation of Optimization Methods for Contrast Enhancement
Ahmet Elbir1,∗, Hamza Osman Ilhan1, Nizamettin Aydin1
1 Department of Computer Engineering, Faculty of Electrical and Electronics Engineering, Yildiz Technical University, Istanbul, Turkey
* Corresponding Author: E-mail:
Computer Systems Science and Engineering 2019, 34(2), 101-107. https://doi.org/10.32604/csse.2019.34.101
Abstract
The performances of the multivariate techniques are directly related to the variable selection process, which is time consuming and requires resources
for testing each possible parameter to achieve the best results. Therefore, optimization methods for variable selection process have been proposed in the
literature to find the optimal solution in short time by using less system resources. Contrast enhancement is the one of the most important and the parameter
dependent image enhancement technique. In this study, two optimization methods are employed for the variable selection for the contrast enhancement
technique. Particle swarm optimization (PSO) and artificial bee colony (ABC) optimization methods are implemented to the histogram stretching technique
in parameter selection process. The results of the optimized histogram stretching technique are compared with one of the parameter independent contrast
enhancement technique; histogram equalization. The results show that the performance of the optimized histogram stretching is better not only in distorted
images but also in original images. Histogram equalization degraded the original images while the optimized histogram stretching has no effect due to
being an adaptive solution.
Keywords
Cite This Article
A. Elbir, H. Osman Ilhan and N. Aydin, "The implementation of optimization methods for contrast enhancement,"
Computer Systems Science and Engineering, vol. 34, no.2, pp. 101–107, 2019.
Citations