DocPure: Prompt-Free Unified Document Restoration via Degradation-Aware Structure-Guided Wavelet Modulation

2026-08-10

AI Summary

This work addresses the degradation of document image quality caused by blur, noise, compression artifacts, and shadows during acquisition and transmission by proposing the first unified restoration framework that operates without task-specific prompts. The method employs a degradation-aware structural autoencoder to predict a clean structural prior and introduces a structure-guided wavelet interaction mechanism that bridges frequency-domain representations and spatial semantics for high-fidelity recovery. Key innovations include degradation-aware routing regularization and a cross-band adaptive modulation strategy, which effectively integrate low-frequency structural cues to guide high-frequency detail reconstruction. Extensive experiments demonstrate that the proposed approach consistently outperforms state-of-the-art methods across diverse degradation scenarios, exhibiting superior generalization capability and restoration performance.

Abstract

High-quality document images are pivotal for information archiving and downstream automatic processing. However, they are frequently compromised by diverse degradations during uncontrolled acquisition and transmission. While unified document restoration techniques have been proposed to restore images from multiple degradations, they often struggle with training multiple degradation-specific models, reliance on manual task-specific prompts, or cross-task data pairing. To address these limitations, we propose DocPure, a prompt-free unified framework that achieves degradation-aware document restoration. We design a degradation-aware structure auto-encoder with degradation-informed routing regularization to predict clean structural priors from degraded inputs. The model is prompt-free at inference, and degradation labels are only used as auxiliary supervision for the routing regularization during training. Furthermore, we introduce a structure-guided wavelet interaction mechanism to bridge frequency-domain features and spatial semantics. Within the structure-guided wavelet interaction mechanism, a cross-frequency adaptive modulation utilizes low-frequency sub-bands to modulate high-frequency recovery, ensuring structural consistency. Extensive experiments demonstrate that DocPure achieves strong performance compared with state-of-the-art methods across various tasks, including deblurring, denoising, compression artifact reduction, and deshadowing.

Problem

• document restoration
• unified framework
• degradation-aware
• prompt-free
• multiple degradations

Innovation

• prompt-free
• degradation-aware
• structure-guided wavelet modulation
• unified document restoration
• routing regularization