Performance analysis of chaotic lévy bat algorithm and chaotic cuckoo search algorithm for gray level image enhancement

Abstract

Dark images can be enhanced in a controlled manner with the help of nature inspired metaheuristic algorithm. In this case image enhancement has been taken as a nonlinear optimization problem. Bat algorithm (BA) and Cuckoo Search (CS) algorithm is one of the most powerful metaheuristic algorithms. In this paper these two algorithms have been modified by chaotic sequence and lévy flight. In BA lévy flight with chaotic step size helps to do intensification. In CS algorithm the random walk has been done via chaotic sequence. Entropy and edge information has been used as objective function. From quantitative and visual analysis it is clear that chaotic lévy BA outperforms the chaotic CS algorithm.