P-BiC: Ultra-High-Definition Image Moiré Patterns Removal via Patch Bilateral Compensation
Zeyu Xiao, Zhihe Lu, Xinchao Wang
Abstract
People nowadays use smartphones to capture photos from multimedia platforms. The presence of moire patterns resulting from spectral aliasing can significantly degrade the visual quality of images, particularly in ultra-high-definition (UHD) images. However, existing demoireing methods have mostly been designed for low-definition images, making them unsuitable for handling moire patterns in UHD images due to their substantial memory requirements. In this paper, we propose a novel patch bilateral compensation network (P-BiC) for the demoire pattern removal in UHD images, which is memory-efficient and prior-knowledge-based. Specifically, we divide the UHD images into small patches and perform patch-level demoireing to maintain the low memory cost even for ultra-large image sizes. Moreover, a pivotal insight, namely that the green channel of an image remains relatively less affected by moire patterns, while the tone information in moire images is still well-retained despite color shifts, is directly harnessed for the purpose of bilateral compensation. The bilateral compensation is achieved by two key components in our P-BiC, i.e., a green-guided detail transfer (G2DT) module that complements distorted features with the intact content, and a style-aware tone adjustment (STA) module for the color adjustment. We quantitatively and qualitatively evaluate the effectiveness of P-BiC with extensive experiments. The code is publicly available at: https://github.com/zeyuxiao1997/P-BiC.
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Install the CLIlune papers get e476b1c2-6abd-42f4-a4db-e68ab460d814Cited by top-tier papers2
- From Zero to Detail: Deconstructing Ultra-High-Definition Image Restoration from Progressive Spectral PerspectiveChen Zhao, Zhizhou Chen, Yunzhe Xu, Enxuan Gu et al.CVPR 2025
- Exploiting Blurry Representations for Event-guided Video Super-ResolutionZeyu Xiao, Xinchao WangAAAI 2026
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