Introducing BAT inspired algorithm to improve fractal image compression

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.

KEYWORDS:

• Fractal image compression
• natural heuristics
• BAT inspired algorithm
• image quality

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.