A Lévy Flight Based BAT Optimization Algorithm for Block-based Image Compression

Many metaheuristics have been adopted to solve the codebook generation problem in image processing. In this paper, the Bat algorithm is combined by the Lévy flight distribution to find out the global optimum codebook. The Lévy flight distribution is combined by the local search procedure. Therefore most of the time the bat concentrate on the local area for specific food while it rarely flies to the different parts of the field for better food opportunities. This process strongly guides the bat on the global minimum way and offers better food, then the bat flies to that direction. Consequently, if a bat is captured by a local minimum point accidentally, the Lévy flight step provides a chance to escape from it easily. Numerical results suggest that the proposed Lévy flight based Bat algorithm is better than the classical ones and provides the global optimum codebook for image compression.