Image Enhancement by Using Fuzzy Firefly Optimization and Fuzzy Perceptron Neural Network

Authors

  • Baydaa I. Khaleel
    Affiliation

    Department of Computer Science, College of Computer Science and Mathematics, University of Mosul, Al Majmoaa, Left Coast, 41002 Mosul, Iraq

https://doi.org/10.3311/PPee.20836

Abstract

The image enhancement methods play an important role in digital image processing. And by using a different kinds of image enhancement techniques, such as artificial intelligence techniques methods. The aim of this methods is to enhance the visual appearance of the digital image and to reduce image noise. In this paper, to enhance the corrupted image and de-noise image, we used swarm optimization algorithms such as a firefly algorithm (FA) and also used neural network such as the perceptron neural network algorithm (PNN). And then after we added the fuzzy membership function to these two algorithms, we obtained to a new method called a fuzzy firefly algorithm (FFA) and fuzzy perceptron neural network algorithm (FPNN). And was computed the performance and efficiency measures for all methods, such as RMSE and PSNR. And the FFA method was the best among the other methods used in this paper.

Keywords:

image enhancement, firefly optimization, swarm intelligence, perceptron neural network, gray and colored images

Citation data from Crossref and Scopus

Published Online

2023-01-23

How to Cite

Khaleel, B. I. “Image Enhancement by Using Fuzzy Firefly Optimization and Fuzzy Perceptron Neural Network”, Periodica Polytechnica Electrical Engineering and Computer Science, 67(1), pp. 95–101, 2023. https://doi.org/10.3311/PPee.20836

Issue

Section

Articles