Flare Free Image

Flare-free image generation aims to computationally remove lens flare artifacts from photographs, improving image quality and the performance of computer vision systems. Current research heavily utilizes deep learning models, often employing multi-frequency decomposition or adaptive focus mechanisms to selectively remove flares while preserving image details, with a strong emphasis on handling nighttime flares and diverse light sources. The development of comprehensive datasets, including both synthetic and real-world images, is crucial for training robust and generalizable models, ultimately impacting various applications such as photography, autonomous driving, and other computer vision tasks.