Neighbourhood Based Bi-Level Contrast Adjustment for Underwater Image Enhancement Using Modified Particle Swarm Optimization

This paper presents a neighbourhood based bi-level contrast adjustment algorithm for underwater image enhancement. In this algorithm, at the outset, the histogram of the images is divided into two equal parts. A Modified Particle Swarm Optimization (MPSO) is introduced in the proposed algorithm to find two different points in each part of the histogram such that each part of the histogram can be separately stretched on the basis of these points. The quality of the output images (enhanced images) is visually and quantitatively judged with reference to the best fitness, mean fitness, Peak Signal to Noise Ratio (PSNR), Underwater Image Quality Measure (UIQM), average PSNR and average UIQM values of all test images and Friedman test. The acquired results proves that there is a substantial improvement of the proposed algorithm compared to others.