A Lightweight Framework for Underwater Image Enhancement with Focus on Color Cast Correction

Underwater imaging plays a vital role in marine biology, underwater archaeology, and environmental monitoring applications. However, the quality of underwater images is often compromised due to color casts caused by light absorption and scattering in the water medium. These challenges hinder image analysis, object recognition, and visual interpretation. This paper presents a computationally efficient framework for enhancing underwater images affected by color casts. The proposed method employs multiscale decomposition and fusion techniques to restore color balance and improve image quality while preserving computational simplicity. Unlike traditional methods that often suffer from over-saturation, incomplete dehazing, or high computational requirements, this approach achieves superior results with minimal artifacts. Experimental evaluations, based on qualitative and quantitative metrics such as UIQM, MDM, and UIConM, demonstrate the method’s effectiveness in comparison with state-of-the-art techniques. The findings highlight the method’s potential for real-time applications in diverse underwater scenarios.