AMPLIFYING AQUATIC VISUALS

Abstract

Our proposed fusion-based approach aims to combat the degradation of underwater images, addressing issues such as diminished colors and indistinguishable objects. Leveraging contrast stretching and Auto White Balance, the technique significantly improves contrast and color, offering a straightforward yet effective solution to enhance visibility in aquatic images, crucial for applications like video surveillance in outdoor computer vision systems. This straightforward approach plays a pivotal role in enhancing image visibility, contributing significantly to applications like video surveillance and other outdoor computer vision systems. Our dehazing process builds upon two essential statistical observations related to haze-free images and haze. By applying dark channel prior and guided filter to the decomposed image, we effectively estimate atmosphere light, resulting in a dehazed output. This method tackles the intricacies of haze, contributing to the generation of high-quality images with improved details and clarity. Beyond image enhancement, our approach showcases versatility by extending into object classification, demonstrating the broader impact and potential of our method in the realm of outdoor computer vision systems.