A Chaotic Lévy flight Approach in Bat and Firefly Algorithm for Gray level image Enhancement

Recently nature inspired metaheuristic algorithms have been applied in image enhancement field to enhance the low contrast images in a control manner. Bat algorithm (BA) and Firefly algorithm (FA) is one of the most powerful metaheuristic algorithms. In this paper these two algorithms have been implemented with the help of chaotic sequence and levy flight. One of them is FA via levy flight where step size of levy flight has been taken from chaotic sequence. In the Bat algorithm the local search has been done via levy flight with chaotic step size. Chaotic sequence shows ergodicity property which helps in better searching. These two algorithms have been applied to optimize parameters of parameterized high boost filter. Entropy, number of edge pixels of the image have been used as objective criterion for measuring goodness of image enhancement. Fitness criterion has been maximized in order to get enhanced image with better contrast. From the experimental results it is clear that BA with chaotic levy outperforms the FA via chaotic levy.

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