Flare Artifact

Flare artifacts, unwanted light patterns in images or spectra, hinder data analysis across diverse fields, from astronomy to photography. Current research focuses on developing sophisticated algorithms, including convolutional neural networks and support vector machines, to detect and remove these artifacts, often employing multi-frequency processing or leveraging machine learning for improved accuracy and efficiency. These advancements are crucial for enhancing image quality, improving the reliability of scientific measurements (e.g., in solar flare analysis and exoplanet studies), and enabling more accurate predictions in applications like space weather forecasting.