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Title: Deep joint demosaicing and high dynamic range imaging within a single shot
Authors: Xu, Yilun
Liu, Ziyang
Wu, Xingming
Chen, Weihai
Wen, Changyun
Li, Zhengguo
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Source: Xu, Y., Liu, Z., Wu, X., Chen, W., Wen, C. & Li, Z. (2021). Deep joint demosaicing and high dynamic range imaging within a single shot. IEEE Transactions On Circuits and Systems for Video Technology, 32(7), 4255-4270.
Journal: IEEE Transactions on Circuits and Systems for Video Technology
Abstract: Spatially varying exposure (SVE) is a promising choice for high-dynamic-range (HDR) imaging (HDRI). The SVE-based HDRI, which is called single-shot HDRI, is an efficient solution to avoid ghosting artifacts. However, it is very challenging to restore a full-resolution HDR image from a real-world image with SVE because: a) only one-third of pixels with varying exposures are captured by camera in a Bayer pattern, b) some of the captured pixels are over- and under-exposed. For the former challenge, a spatially varying convolution (SVC) is designed to process the Bayer images carried with varying exposures. For the latter one, an exposure-guidance method is proposed against the interference from over- and under-exposed pixels. Finally, a joint demosaicing and HDRI deep learning framework is formalized to include the two novel components and to realize an end-to-end single-shot HDRI. Experiments indicate that the proposed end-to-end framework avoids the problem of cumulative errors and surpasses the related state-of-the-art methods. Related codes and datasets will be provided at
ISSN: 1051-8215
DOI: 10.1109/TCSVT.2021.3129691
Rights: © 2021 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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