Haze Density

Haze density, a measure of atmospheric particulate matter obscuring visibility, is a key challenge in image processing and remote sensing. Current research focuses on developing advanced dehazing algorithms, often employing deep learning architectures like U-Net variations, transformers, and diffusion models, to improve image clarity and accuracy by leveraging techniques such as haze type classification and density map estimation. These advancements aim to overcome limitations of existing methods, particularly in handling diverse haze types and real-world scenarios with uneven haze distribution. Improved dehazing techniques have significant implications for various applications, including autonomous driving, remote sensing, and computer vision.