Underwater Image Enhancement With Optimal Histogram Using Hybridized Particle Swarm and Dragonfly. (28th May 2021)

• Record Type: Journal Article
• Authors: Prasath, R; Kumanan, T
• Is Part Of: Computer journal. Volume 64:Number 10(2021)
• Page Start: 1494
• Page End: 1513
• Publication Date: 2021-05-28
• Subjects: underwater image -- color correction -- contrast correction -- optimization -- Dragonfly Algorithm; Computers -- Periodicals; 005.1
• DOI: 10.1093/comjnl/bxab056
• Languages: English
• ISSNs: 0010-4620

Abstract

Abstract: Typically, underwater image processing is mainly concerned with balancing the color change distortion or light scattering. Various researches have been processed under these issues. This proposed model incorporates two phases, namely, contrast correction and color correction. Moreover, two processes are involved within the contrast correction model, namely: (i) global contrast correction and (ii) local contrast correction. For the image enhancement, the main target is on the histogram evaluation, and therefore, the optimal selection of histogram limit is very essential. For this optimization purpose, a new hybrid algorithm is introduced namely, swarm updated Dragonfly Algorithm, which is the hybridization of Particle Swarm Optimization (PSO) and Dragonfly Algorithm (DA). Further, this paper mainly focused on Integrated Global and Local Contrast Correction (IGLCC). The proposed model is finally distinguished over the other conventional models like Contrast Limited Adaptive Histogram, IGLCC, dynamic stretching IGLCC-Genetic Algorithm, IGLCC-PSO, IGLCC- Firefly and IGLCC-Cuckoo Search, IGLCC-Distance-Oriented Cuckoo Search and DA, and the superiority of the proposed work is proved.