Leveraging Contrast Information for Efficient Document Shadow Removal
Journal:
arXiv
Published Date:
Apr 1, 2025
Abstract
Document shadows are a major obstacle in the digitization process. Due to the
dense information in text and patterns covered by shadows, document shadow
removal requires specialized methods. Existing document shadow removal methods,
although showing some progress, still rely on additional information such as
shadow masks or lack generalization and effectiveness across different shadow
scenarios. This often results in incomplete shadow removal or loss of original
document content and tones. Moreover, these methods tend to underutilize the
information present in the original shadowed document image. In this paper, we
refocus our approach on the document images themselves, which inherently
contain rich information.We propose an end-to-end document shadow removal
method guided by contrast representation, following a coarse-to-fine refinement
approach. By extracting document contrast information, we can effectively and
quickly locate shadow shapes and positions without the need for additional
masks. This information is then integrated into the refined shadow removal
process, providing better guidance for network-based removal and feature
fusion. Extensive qualitative and quantitative experiments show that our method
achieves state-of-the-art performance.
