Error-Mask-Adaptive Dynamic Filtering for Image Inpainting

A novel error-mask-adaptive dynamic filtering (EMDF) algorithm is proposed in this paper, which uses a continuous error mask to inpaint an image adaptively and faithfully. In an EMDF layer, we determine a spatially varying filter adaptively according to an error mask and perform separable dynamic fi...

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Main Authors: Keunsoo Ko, Seunggyun Woo, Chang-Su Kim
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10845789/
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author Keunsoo Ko
Seunggyun Woo
Chang-Su Kim
author_facet Keunsoo Ko
Seunggyun Woo
Chang-Su Kim
author_sort Keunsoo Ko
collection DOAJ
description A novel error-mask-adaptive dynamic filtering (EMDF) algorithm is proposed in this paper, which uses a continuous error mask to inpaint an image adaptively and faithfully. In an EMDF layer, we determine a spatially varying filter adaptively according to an error mask and perform separable dynamic filtering. Meanwhile, we update the error mask by modeling the error propagation during the filtering. Through several EMDF layers, we predict an inpainting result. Finally, we refine it to reconstruct a more faithful image. Experimental results on diverse datasets show that the proposed EMDF algorithm outperforms existing inpainting algorithms significantly. The source codes are available at <uri>https://github.com/keunsoo-ko/EMDF</uri>.
format Article
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issn 2169-3536
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publishDate 2025-01-01
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spelling doaj-art-66b721064c0d45ef83fa8103557df0d72025-01-31T00:02:06ZengIEEEIEEE Access2169-35362025-01-0113184031841710.1109/ACCESS.2025.353144010845789Error-Mask-Adaptive Dynamic Filtering for Image InpaintingKeunsoo Ko0https://orcid.org/0000-0003-0203-4530Seunggyun Woo1https://orcid.org/0009-0002-0722-2290Chang-Su Kim2https://orcid.org/0000-0002-4276-1831Department of Artificial Intelligence, The Catholic University of Korea, Bucheon, South KoreaSchool of Electrical Engineering, Korea University, Seoul, South KoreaSchool of Electrical Engineering, Korea University, Seoul, South KoreaA novel error-mask-adaptive dynamic filtering (EMDF) algorithm is proposed in this paper, which uses a continuous error mask to inpaint an image adaptively and faithfully. In an EMDF layer, we determine a spatially varying filter adaptively according to an error mask and perform separable dynamic filtering. Meanwhile, we update the error mask by modeling the error propagation during the filtering. Through several EMDF layers, we predict an inpainting result. Finally, we refine it to reconstruct a more faithful image. Experimental results on diverse datasets show that the proposed EMDF algorithm outperforms existing inpainting algorithms significantly. The source codes are available at <uri>https://github.com/keunsoo-ko/EMDF</uri>.https://ieeexplore.ieee.org/document/10845789/Image inpaintingdynamic filteringmask-adaptive filteringconvolutional neural networks
spellingShingle Keunsoo Ko
Seunggyun Woo
Chang-Su Kim
Error-Mask-Adaptive Dynamic Filtering for Image Inpainting
IEEE Access
Image inpainting
dynamic filtering
mask-adaptive filtering
convolutional neural networks
title Error-Mask-Adaptive Dynamic Filtering for Image Inpainting
title_full Error-Mask-Adaptive Dynamic Filtering for Image Inpainting
title_fullStr Error-Mask-Adaptive Dynamic Filtering for Image Inpainting
title_full_unstemmed Error-Mask-Adaptive Dynamic Filtering for Image Inpainting
title_short Error-Mask-Adaptive Dynamic Filtering for Image Inpainting
title_sort error mask adaptive dynamic filtering for image inpainting
topic Image inpainting
dynamic filtering
mask-adaptive filtering
convolutional neural networks
url https://ieeexplore.ieee.org/document/10845789/
work_keys_str_mv AT keunsooko errormaskadaptivedynamicfilteringforimageinpainting
AT seunggyunwoo errormaskadaptivedynamicfilteringforimageinpainting
AT changsukim errormaskadaptivedynamicfilteringforimageinpainting