Combined Flicker-banding and Moire Removal for Screen-Captured Images
Libo Zhu, Zihan Zhou, Zhiyi Zhou, Yiyang Qu, Weihang Zhang, Keyu Shi, Yifan Fu, Yulun Zhang

TL;DR
This paper introduces CLEAR, a unified framework for removing combined moiré patterns and flicker-banding from screen-captured images, supported by a large dataset and novel training techniques, significantly improving restoration quality.
Contribution
The paper presents the first joint removal method for moiré and flicker artifacts, including a new dataset, an ISP-based simulation pipeline, and a frequency-domain restoration module.
Findings
Outperforms existing methods on multiple metrics
Effective in complex real-world scenarios
Supports large-scale training with a new dataset
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…
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Taxonomy
TopicsImage Enhancement Techniques · Advanced Optical Imaging Technologies · Image and Video Quality Assessment
