Noise Model

Noise modeling in various applications, from image processing to audio restoration and machine learning, aims to accurately characterize and represent noise characteristics to improve signal processing and data analysis. Current research focuses on developing sophisticated noise models, often incorporating deep learning architectures like convolutional neural networks and normalizing flows, to handle complex noise types and improve the performance of downstream tasks such as denoising and super-resolution. These advancements are crucial for enhancing the quality and reliability of data analysis across diverse fields, impacting areas like medical imaging, audio engineering, and computer vision. The development of more accurate and generalizable noise models is a key area of ongoing research.