Flare Removal

Flare removal aims to digitally eliminate lens flares from images, improving visual quality and downstream image processing. Recent research heavily utilizes deep learning, particularly convolutional neural networks and transformers, often employing multi-frequency processing to separate flare artifacts from image content. This work is driven by the need for improved image quality in mobile photography and computer vision applications, with ongoing efforts focused on creating more realistic and diverse datasets for training robust models that handle the complexities of nighttime flares. The development of effective flare removal techniques is crucial for enhancing the performance of various image processing tasks and improving the user experience in mobile and other imaging systems.