Dual-domain Deep Convolutional Neural Networks for Image Demoireing

An Gia Vien, Hyunkook Park, Chul Lee

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

18 Scopus citations

Abstract

We develop deep convolutional neural networks (CNNs) for moiré artifacts removal by exploiting the complex properties of moiré patterns in multiple complementary domains, i.e., the pixel and frequency domains. In the pixel domain, we employ multi-scale features to remove the moiré artifacts associated with specific frequency bands using multi-resolution feature maps. In the frequency domain, we design a network that processes discrete cosine transform (DCT) coefficients to remove moiré artifacts. Next, we develop a dynamic filter generation network that learns dynamic blending filters. Finally, the results from the pixel and frequency domains are combined using the blending filters to yield moiré-free images. In addition, we extend the proposed approach to arbitrary-length burst image demoireing. Specifically, we develop a new attention network to effectively extract useful information from each image in the burst and align them with the reference image. We demonstrate the effectiveness of the proposed demoireing algorithm by evaluating on the test set in the NTIRE 2020 Demoireing Challenge: Track 1 (Single image) and Track 2 (Burst).

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020
PublisherIEEE Computer Society
Pages1934-1942
Number of pages9
ISBN (Electronic)9781728193601
DOIs
StatePublished - Jun 2020
Event2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020 - Virtual, Online, United States
Duration: 14 Jun 202019 Jun 2020

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume2020-June
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Conference

Conference2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020
Country/TerritoryUnited States
CityVirtual, Online
Period14/06/2019/06/20

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