Abstract
Fractal image compression (FIC) is an auspicious technique for encoding images. It is based on fractals that can be found in an image and the generation of duplicating blocks based on mathematical transformations. The method appears exciting in both theory and application but has a disadvantage in encoding time due to the great resources needed when encoding big data. On another side, heuristics represent a set of approaches used to resolve hard optimization tasks with lucid resources consumption. They are branded with their fast convergence and reduction of research difficulty. In this paper, we apply and for the first time, a new study about the performance of the Bat Inspired Algorithm (BIA) as a natural inspired metaheuristic to improve FIC. Results show the improvement of such algorithm under different aspects (encoding time, compression ratio (CR), peak signal to noise ratio (PSNR), and mean square error (MSE)). Furthermore, a comparison with some of the current methods underlines this gain.
Disclosure statement
No potential conflict of interest was reported by the authors.
ORCID
Rafik Menassel http://orcid.org/0000-0003-3412-2551
Additional information
Notes on contributors
Rafik Menassel
Dr. Rafik Menassel, PhD, is Associate professor in computer science in the Department of Mathematics and Computer Science, Larbi Tebessi University, Tebessa, Algeria.
Idriss Gaba
Idris Gaba received Master degree in computer science In the Department of Mathematics and Computer Science, Larbi Tebessi University, Tebessa, Algeria.
Khalil Titi
Khalil Titi received Master degree in computer science, in the Department of Mathematics and Computer Science, Larbi Tebessi University, Tebessa, Algeria.