Document Shadow Removal

Document shadow removal aims to digitally eliminate shadows from scanned documents, improving readability and visual quality. Recent research heavily utilizes deep learning, particularly Transformer-based architectures, often incorporating frequency-aware processing and multi-scale refinement strategies to achieve accurate shadow detection and removal. These advancements are driven by the need for high-resolution, real-time performance, leading to the development of larger, more diverse datasets and more efficient network designs. Improved document shadow removal techniques have significant implications for digital archiving, document processing, and accessibility applications.