Abstract: People are nowadays using smartphones to capture photos from multimedia platfroms. The presence of moir\'e patterns resulting from spectral aliasing can significantly degrade the visual quality of images, particularly in ultra-high-definition (UHD) images. However, existing demoir\'eing methods have mostly been designed for low-definition images, making them unsuitable for handling moir\'e 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 demoir\'e 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 demoir\'eing 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 moir\'e patterns, while the tone information in moir\'e 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 (G$^2$DT) 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.
Primary Subject Area: [Content] Media Interpretation
Secondary Subject Area: [Experience] Multimedia Applications
Relevance To Conference: This work contributes to multimedia and multimodal processing by addressing the challenge of demoiré pattern removal in ultra-high-definition (UHD) images, commonly captured using smartphones and multimedia platforms. Moiré patterns resulting from spectral aliasing can severely degrade image quality, particularly in UHD images. Through quantitative and qualitative evaluations, we demonstrate the effectiveness of P-BiC in removing moiré patterns, thus enhancing the visual quality of UHD images in multimedia applications.
Supplementary Material: zip
Submission Number: 2733
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