LSD2 -- Joint Denoising and Deblurring of Short and Long Exposure Images with CNNs
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Abstract (arXiv)
The paper addresses the problem of acquiring high-quality photographs with handheld smartphone cameras in low-light imaging conditions. We propose an approach based on capturing pairs of short and long exposure images in rapid succession and fusing them into a single high-quality photograph. Unlike existing methods, we take advantage of both images simultaneously and perform a joint denoising and deblurring using a convolutional neural network. A novel approach is introduced to generate realistic short-long exposure image pairs. The method produces good images in extremely challenging conditions and outperforms existing denoising and deblurring methods. It also enables exposure fusion in the presence of motion blur.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 Nov 2018.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 2.
4 papers.
- 2024Bracket Diffusion: HDR Image Generation by Consistent LDR Denoisingcited by 15
- 2022D2HNet: Joint Denoising and Deblurring with Hierarchical Network for Robust Night Image Restorationcited by 14
- 2022SJ-HD^2R: Selective Joint High Dynamic Range and Denoising Imaging for Dynamic Scenescited by 2
- 2024Modeling Dual-Exposure Quad-Bayer Patterns for Joint Denoising and Deblurringcited by 2
- 2024Modeling Dual-Exposure Quad-Bayer Patterns for Joint Denoising and Deblurring10 Dec 2024
- 2024Bracket Diffusion: HDR Image Generation by Consistent LDR Denoising23 May 2024
- 2022D2HNet: Joint Denoising and Deblurring with Hierarchical Network for Robust Night Image Restoration7 Jul 2022
- 2022SJ-HD^2R: Selective Joint High Dynamic Range and Denoising Imaging for Dynamic Scenes20 Jun 2022