An optimization method for underwater images enhancement

Underwater images suffer from absorption and scattering of light, so underwater images are blurry, while contrast, clarity, and lighting are low. To improve the quality of underwater images, a method based on the new metaheuristic algorithm, the CHIO algorithm, was proposed. In our work, we first read the images and convert the color system from RGB to HSV. Subsequently, apply the CHIO algorithm to the image, and finally convert the color system from HSV to RGB. Experiments on the standard benchmark dataset for underwater image optimization proved the effectiveness of the method, while the performance of our algorithm is better than that of the standard optimization algorithms.