Visibility Enhancement

Visibility enhancement research aims to improve the quality of images degraded by poor weather conditions (haze, rain, low light) or lighting effects (glare, floodlights). Current efforts focus on developing sophisticated neural networks, often incorporating attention mechanisms and multi-scale fusion techniques, to process both visible and infrared imagery, achieving real-time performance for applications like autonomous navigation and intelligent transportation systems. These advancements leverage techniques like layer decomposition, light-effects suppression, and physically-based simulation to produce more accurate and visually appealing results. The impact of this research extends to improved safety and efficiency in various sectors, including maritime navigation, autonomous driving, and surveillance systems.