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

2026-02-02

AI Summary

This work addresses the challenging problem of simultaneously removing moiré patterns and flicker bands in screen-captured images, which often co-occur and cause severe visual degradation. Existing methods typically target only one type of degradation and thus struggle with such compound distortions. To tackle this issue, the authors propose CLEAR, a unified restoration framework that systematically handles both degradations in an integrated manner. They construct a large-scale dataset featuring composite degradations and devise an ISP-based flicker simulation pipeline. A frequency-domain decomposition and recombination module is introduced to disentangle degradation-specific features, and a trajectory alignment loss is proposed to enhance temporal consistency. Extensive experiments demonstrate that CLEAR significantly outperforms state-of-the-art methods across multiple metrics and exhibits superior restoration quality and generalization capability in real-world complex scenarios.

Technology Category

• Computer Vision: Motion & Tracking
• Machine Learning: Multimodal Learning
• Natural Language Processing: Language Grounding & Multi-modal NLP

Application Category

• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• Web Mining and Content Analysis: Web data integration and cleaning
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs

Abstract

Capturing display screens with mobile devices has become increasingly common, yet the resulting images often suffer from severe degradations caused by the coexistence of moir\'e 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 moir\'e 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 moir\'e 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.

Problem

• moiré
• flicker-banding
• screen-captured images
• image degradation
• artifact removal

Innovation

• moire removal
• flicker-banding
• joint restoration
• frequency-domain decomposition
• screen-captured images