<p>This research presents an innovative method for enhancing the quality of underwater images, which are often degraded by low contrast and reduced clarity. These issues primarily stem from physical phenomena such as absorption, scattering, and reflection, resulting in hazy, blurry visuals and uneven color distribution, where one color channel typically dominates. Addressing these challenges is essential for the effective utilization of underwater imagery. The proposed method integrates contrast-limited adaptive histogram equalization (CLAHE) with a percentile-based enhancement technique to improve image quality. This combination enhances both contrast and detail, producing more visually appealing and informative results. To evaluate the performance of the proposed approach, two metrics—root mean squared error (RMSE) and entropy—are used. Experimental results demonstrate that the method outperforms existing state-of-the-art techniques, offering a reliable and efficient solution for underwater image enhancement. It successfully mitigates the limitations of underwater imaging, delivering clearer, better-balanced visuals suitable for a wide range of applications.</p>