Doc-Former: A transformer-based document shadow denoising network
Shengchang Pei, Jun Liu, Niannian Yi, Yun Zhang, Zhengtao Liu, Z. Chen · 2023
The existence of shadows makes the visual perception and readability of document images poor, so how to remove the shadows in these document images is an urgent problem to be solved in the industry. Currently, only a few methods are specifically designed for shadow removal of document images. Among them, some algorithms are heuristic algorithms based on experience or direct observation. These algorithms only heuristically denoise the image from the perspective of light or color, and do not take into account the specific characteristics of the shadow of the document. So we propose a transformer-based document shadow denoising algorithm, and the experimental comparison proves that it has achieved state-of-the-art excellence in its performance.