Deep Joint Demosaicing and High Dynamic Range Imaging Within a Single Shot

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Deep Joint Demosaicing and High Dynamic Range Imaging Within a Single Shot
Title:
Deep Joint Demosaicing and High Dynamic Range Imaging Within a Single Shot
Other Titles:
IEEE Transactions on Circuits and Systems for Video Technology
Publication Date:
19 November 2021
Citation:
Xu, Y., Liu, Z., Wu, X., Chen, W., Wen, C., & Li, Z. (2022). 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. https://doi.org/10.1109/tcsvt.2021.3129691
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 surpasses the related state-of-the-art methods, and the problem of cumulative errors is solved.
License type:
Publisher Copyright
Funding Info:
This work is supported by the National Natural Science Foundation of China under the research project 61620106012.
Description:
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
ISSN:
1051-8215
1558-2205
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