A Hybrid Approach for Enhancement of Underwater Images Using CLAHE and Percentile-Based Techniques

Underwater images frequently experience issues such as low contrast, uneven shading, and haziness caused by light absorption, scattering, and reflection, making it difficult to capture clear and detailed visuals. These issues hinder the extraction of meaningful information from underwater images, which is critical for applications such as marine research, underwater exploration, and surveillance. This work proposes a novel image enhancement method tailored for underwater environments. By integrating Contrast-Limited Adaptive Histogram Equalization (CLAHE) along with Percentile methodologies, proposed modal aim to significantly improve the visual quality and clarity of underwater photographs. CLAHE prevents the over-amplification of noise while adapting to both dark and bright regions of the underwater scene. The Percentile Enhancement method further refines the image by adjusting overall brightness while preserving essential details. By mapping pixel intensities to specific percentiles (e.g., 1st, 5th, 95th, and 99th), the technique enhances contrast without compromising fine image features. Proposed hybrid modal combines the strengths of CLAHE and percentile enhancement. CLAHE first improves local contrast, followed by percentile-based adjustments that enhance both global and local image features. The result is a more visually balanced and detailed representation of underwater scenes, addressing common challenges such as blurriness, low contrast, and noise.