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Extremely Low-Light Image Enhancement with Scene Text Restoration | IEEE Conference Publication | IEEE Xplore

Extremely Low-Light Image Enhancement with Scene Text Restoration


Abstract:

Deep learning-based methods have made impressive progress in enhancing extremely low-light images - the image quality of the reconstructed images has generally improved. ...Show More

Abstract:

Deep learning-based methods have made impressive progress in enhancing extremely low-light images - the image quality of the reconstructed images has generally improved. However, we found out that most of these methods could not sufficiently recover the image details, for instance, the texts in the scene. In this paper, a novel image enhancement framework is proposed to precisely restore the scene texts, as well as the overall quality of the image simultaneously under extremely low-light conditions. Mainly, we employed a self-regularised attention map, an edge map, and a novel text detection loss. In addition, leveraging the synthetic low-light images is beneficial for image enhancement on the genuine ones in terms of text detection. The quantitative and qualitative experimental results have shown that the proposed model outperforms state-of-the-art methods in image restoration, text detection, and text spotting on See In the Dark and ICDAR15 datasets.
Date of Conference: 21-25 August 2022
Date Added to IEEE Xplore: 29 November 2022
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Conference Location: Montreal, QC, Canada

References

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