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Poster
EFFICIENT FUSION OF DEPTH INFORMATION FOR DEFOCUS DEBLURRING
- DOI:
- 10.60864/34xr-1g03
- Citation Author(s):
- Submitted by:
- Jucai Zhai
- Last updated:
- 28 March 2024 - 11:15pm
- Document Type:
- Poster
- Document Year:
- 2024
- Event:
- Presenters:
- ZHAI JUCAI
- Paper Code:
- IVMSP-P9.8
- Categories:
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Defocus deblurring is a classic problem in image restoration tasks. The formation of its defocus blur is related to depth. Recently, the use of dual-pixel sensor designed according to depth-disparity characteristics has brought great improvements to the defocus deblurring task. However, the difficulty of real-time acquisition of dual-pixel images brings difficulties to algorithm deployment. This inspires us to remove defocus blur by single image with depth information. We propose a single-image depth-enhanced defocus deblurring network, which uses a depth map estimated by the monocular depth estimation network to guide the network defocus deblurring. We design a deep information fusion unit, which greatly improves the effect of deblurring. Experiments show that on the single image defocus deblurring task, the experimental results demonstrate the superiority of our method.
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