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Single image shadow removal using 2D signed distance field.

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Title: Single image shadow removal using 2D signed distance field.
Authors: Fu, Yanping1 (AUTHOR), Zhang, Yuting1 (AUTHOR), Sun, Dengdi1 (AUTHOR), Zhang, Shaojie1 (AUTHOR), Zhao, Haifeng1 (AUTHOR) senith@163.com
Source: Visual Computer. Jul2025, Vol. 41 Issue 9, p6387-6399. 13p.
Subjects: Fast Fourier transforms, Algorithms
Abstract: Due to substantial fluctuations in brightness at shadow boundaries, existing shadow removal algorithms often struggle to accurately eliminate these boundaries. This challenge is further compounded by the reliance on binary mask representations for shadow regions. Therefore, we propose a novel approach to shadow removal using 2D Signed Distance Field (SDF), which serves as a smooth weight prior to handle shadow boundaries more effectively. First, we introduce a fast Fourier transform (FFT) framework to capture both global frequency and local spatial features, enhancing the overall quality of shadow removal. Additionally, we propose an information interaction module (IIM) to fuse local spatial information with global frequency information obtained from the FFT, thereby improving the precision of shadow boundary handling. Second, we specially design a boundary refinement module (BRM) for shadow boundaries, leveraging the characteristics of the SDF to ensure smoother and more natural elimination of shadow boundaries. Finally, we introduce a global feature modulation technique to combine features from SDF, FFT, and non-shadow regions, further enhancing the overall shadow removal results. Extensive experiments demonstrate that our method is comparable to state-of-the-art approaches, particularly in effectively removing shadow boundaries and achieving high-quality results. [ABSTRACT FROM AUTHOR]
Copyright of Visual Computer is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 186469271
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PubType: Academic Journal
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  Data: Due to substantial fluctuations in brightness at shadow boundaries, existing shadow removal algorithms often struggle to accurately eliminate these boundaries. This challenge is further compounded by the reliance on binary mask representations for shadow regions. Therefore, we propose a novel approach to shadow removal using 2D Signed Distance Field (SDF), which serves as a smooth weight prior to handle shadow boundaries more effectively. First, we introduce a fast Fourier transform (FFT) framework to capture both global frequency and local spatial features, enhancing the overall quality of shadow removal. Additionally, we propose an information interaction module (IIM) to fuse local spatial information with global frequency information obtained from the FFT, thereby improving the precision of shadow boundary handling. Second, we specially design a boundary refinement module (BRM) for shadow boundaries, leveraging the characteristics of the SDF to ensure smoother and more natural elimination of shadow boundaries. Finally, we introduce a global feature modulation technique to combine features from SDF, FFT, and non-shadow regions, further enhancing the overall shadow removal results. Extensive experiments demonstrate that our method is comparable to state-of-the-art approaches, particularly in effectively removing shadow boundaries and achieving high-quality results. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Visual Computer is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s00371-025-03940-7
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: Algorithms
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      – TitleFull: Single image shadow removal using 2D signed distance field.
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              M: 07
              Text: Jul2025
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              Y: 2025
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