Distance-Oriented Cuckoo Search enabled optimal histogram for underwater image enhancement: a novel quality metric analysis

Abstract

The major problem in underwater image processing involves light attenuation. In order to overcome such light incorporation and dispersion issues, this paper proposes a new underwater image enhancement model that includes certain phases like contrast correction and colour correction. Here, two processes are worked out in contrast correction namely (i) global contrast correction and (ii) local contrast correction. Furthermore, as the histogram evaluation is the major part of any image enhancement, it is very important to choose the optimal limits of the histogram. To solve this optimization problem, this paper introduces a new optimization model namely Distance Oriented Cuckoo Search (DOCS) algorithm that also satisfies the objective function defined in this paper. The major process of this model focusses on Integrated Global and Local Contrast Correction (IGLCC). Finally, the proposed model compares its performance over other methods.