Multi-Scale Fusion Underwater Image Enhancement Based on HSV Color Space Equalization

Abstract

Meeting the escalating demand for high-quality underwater imagery poses a significant challenge due to light absorption and scattering in water, resulting in color distortion and reduced contrast. This study presents an innovative approach for enhancing underwater images, combining color correction, HSV color space equalization, and multi-scale fusion techniques. Initially, automatic contrast adjustment and improved white balance corrected color bias; this was followed by saturation and value equalization in the HSV space to enhance brightness and saturation. Gaussian and Laplacian pyramid methods extracted multi-scale features that were fused to augment image details and edges. Extensive subjective and objective evaluations compared our method with existing algorithms, demonstrating its superior performance in UCIQE (0.64368) and information entropy (7.8041) metrics. The proposed method effectively improves overall image quality, mitigates color bias, and enhances brightness and saturation.