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Image Demoiréing in RAW and sRGB Domains

  • Shuning Xu
  • , Binbin Song
  • , Xiangyu Chen
  • , Xina Liu
  • , Jiantao Zhou*
  • *Corresponding author for this work
  • University of Macau
  • Shenzhen Institute of Advanced Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Moiré patterns frequently appear when capturing screens with smartphones or cameras, potentially compromising image quality. Previous studies suggest that moiré pattern elimination in the RAW domain offers greater effectiveness compared to demoiréing in the sRGB domain. Nevertheless, relying solely on RAW data for image demoiréing is insufficient in mitigating the color cast due to the absence of essential information required for the color correction by the image signal processor (ISP). In this paper, we propose to jointly utilize both RAW and sRGB data for image demoiréing (RRID), which are readily accessible in modern smartphones and DSLR cameras. We develop Skip-Connection-based Demoiréing Module (SCDM) with Gated Feedback Module (GFM) and Frequency Selection Module (FSM) embedded in skip-connections for the efficient and effective demoiréing of RAW and sRGB features, respectively. Subsequently, we design a RGB Guided ISP (RGISP) to learn a device-dependent ISP, assisting the process of color recovery. Extensive experiments demonstrate that our RRID outperforms state-of-the-art approaches, in terms of the performance in moiré pattern removal and color cast correction by 0.62 dB in PSNR and 0.003 in SSIM. Code is available at https://github.com/rebeccaeexu/RRID.

Original languageEnglish
Title of host publicationComputer Vision - ECCV 2024 - 18th European Conference, Proceedings
EditorsAleš Leonardis, Elisa Ricci, Stefan Roth, Olga Russakovsky, Torsten Sattler, Gül Varol
PublisherSpringer Science and Business Media Deutschland GmbH
Pages108-124
Number of pages17
ISBN (Print)9783031726576
DOIs
StatePublished - 2025
Externally publishedYes
Event18th European Conference on Computer Vision, ECCV 2024 - Milan, Italy
Duration: 29 Sep 20244 Oct 2024

Publication series

NameLecture Notes in Computer Science
Volume15064 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th European Conference on Computer Vision, ECCV 2024
Country/TerritoryItaly
CityMilan
Period29/09/244/10/24

Keywords

  • Image demoiréing
  • Image restoration
  • RAW domain

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