arXiv:2602.01559cs.CVeess.IV2026-02被引 2

首次系统解决屏幕拍摄中摩尔纹与闪烁条纹共现问题

Combined Flicker-banding and Moire Removal for Screen-Captured Images

论文配图:Combined Flicker-banding and Moire Removal for Screen-Captured Images
图 1 · 摘自论文原文
  • 构建统一框架CLEAR,联合建模两种图像退化
  • 在真实数据上显著优于现有方法,多指标领先
  • 适合移动端屏幕图像修复与视觉质量提升场景

用手机拍摄显示屏幕已成常态,但图像常因摩尔纹与闪烁条纹共存而严重劣化。由于二者在真实成像中强耦合,针对单一退化的现有方法无法泛化到复合场景。本文首次系统研究屏幕拍摄图像中摩尔纹与闪烁条纹的联合去除,提出统一恢复框架CLEAR。为支持该任务,构建包含两类退化的大型数据集,并引入基于ISP的闪烁模拟流水线以稳定训练并扩展退化分布。设计频域分解与重构模块及轨迹对齐损失,增强对复合退化的建模能力。大量实验表明,所提方法在多个评估指标上持续优于现有图像恢复方法,验证了其在复杂真实场景中的有效性。

原文摘要 · Abstract (English)

Capturing display screens with mobile devices has become increasingly common, yet the resulting images often suffer from severe degradations caused by the coexistence of moiré patterns and flicker-banding, leading to significant visual quality degradation. Due to the strong coupling of these two artifacts in real imaging processes, existing methods designed for single degradations fail to generalize to such compound scenarios. In this paper, we present the first systematic study on joint removal of moiré patterns and flicker-banding in screen-captured images, and propose a unified restoration framework, named CLEAR. To support this task, we construct a large-scale dataset containing both moiré patterns and flicker-banding, and introduce an ISP-based flicker simulation pipeline to stabilize model training and expand the degradation distribution. Furthermore, we design a frequency-domain decomposition and re-composition module together with a trajectory alignment loss to enhance the modeling of compound artifacts. Extensive experiments demonstrate that the proposed method consistently. outperforms existing image restoration approaches across multiple evaluation metrics, validating its effectiveness in complex real-world scenarios.

图像修复摩尔纹闪烁条纹屏幕拍摄

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