A novel enhanced cuckoo search algorithm for contrast enhancement of gray scale images - Kamoona, Ammar Mansoor; Patra, Jagdish Chandra (Applied soft computing, 2019)
A good contrast image has a significant role in different image processing applications and computer vision algorithms. One of the most common contrast enhancement approaches is histogram equalization (HE) that enhances the contrast of an image globally. However, it gives rise to some over-enhanced regions, loss of detail information, and enhancement of noise. In order to improve the performance of the HE algorithm, local HE and adaptive HE algorithms have been proposed but with limited success. Recently, an evolutionary algorithm named cuckoo search (CS) algorithm has been employed for automatic image contrast enhancement showing promising performance. In this paper, we propose a novel enhanced cuckoo search (ECS) algorithm for image contrast enhancement. In addition, we propose a new range of search space for the parameters of the local/global enhancement (LGE) transformation that need to be optimized. The proposed ECS algorithm is applied to several low contrast test images and its performance is compared with that of the CS algorithm. Next, we compare the performance of the ECS algorithm with artificial bee colony algorithm using the proposed LGE transformation and a global transformation. In the last stage of performance evaluation, the ECS algorithm is compared with several image enhancement algorithms, namely, HE, CLAHE, Particle Swarm Optimization (PSO), CS, modified CS and CS-PSO algorithms. In all cases, we have shown the superiority of the ECS algorithm in terms of several performance measures. [Display omitted] •A novel enhanced cuckoo search algorithm is proposed by enhancing the intensification of the standard CS algorithm.•The proposed algorithm is employed to enhance the contrast of gray images using the local/global enhancement transformation.•A new parameters range for the enhancement transformation is proposed which shows superior results compared to the literature.•Another two parameters ranges are also proposed to show how these ranges affect the performance of the ECS-based contrast enhancement algorithm.•The algorithm is compared with other algorithms and shows a good results in most cases.