Image Restoration Using Deep Learning
Supervisors: Florian Kleber, Christian Stippel Status: open Problem Statement Historical images, such as digitized photographs, manuscripts, maps, or scientific records, often suffer from degradation due to aging, storage conditions, or limitations in early imaging technologies. Common degradations include noise, fading, blur, physical damage, and low resolution. These artifacts hinder the readability, analysis, and digital preservation … Continue reading Image Restoration Using Deep Learning