LACC-RCE: A Local Adaptive Color Correction and Rayleigh-Based Contrast Enhancement Method for Underwater Image Enhancement

Abstract

Underwater images are inherently degraded by color distortion, contrast reduction, and uneven brightness, primarily due to light absorption and scattering in water. To mitigate these challenges, a novel enhancement approach is proposed, integrating Local Adaptive Color Correction (LACC) with contrast enhancement based on adaptive Rayleigh distribution stretching and CLAHE (LACC-RCE). Conventional color correction methods predominantly employ global adjustment strategies, which are often inadequate for handling spatially varying color distortions. In contrast, the proposed LACC method incorporates local color analysis, tone-weighted control, and spatially adaptive adjustments, allowing for region-specific color correction. This approach effectively enhances color fidelity and perceptual naturalness, addressing the limitations of global correction techniques. For contrast enhancement, the proposed method leverages the global mapping characteristics of the Rayleigh distribution to improve overall contrast, while CLAHE is employed to adaptively enhance local regions. A weighted fusion strategy is then applied to synthesize high-quality underwater images. Experimental results indicate that LACC-RCE surpasses conventional methods in color restoration, contrast optimization, and detail preservation, thereby enhancing the visual quality of underwater images. This improvement facilitates more reliable inputs for underwater object detection and recognition tasks.