# LSD2 -- Joint Denoising and Deblurring of Short and Long Exposure Images with CNNs

arXiv: https://arxiv.org/abs/1811.09485 · HTML: https://mlsanity.com/paper/1811.09485/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Nov 2018.

## Built on by (most cited first, 4 of 4)

- [Bracket Diffusion: HDR Image Generation by Consistent LDR Denoising](https://mlsanity.com/paper/2405.14304/) (2024)
- [D2HNet: Joint Denoising and Deblurring with Hierarchical Network for Robust Night Image Restoration](https://mlsanity.com/paper/2207.03294/) (2022)
- [SJ-HD^2R: Selective Joint High Dynamic Range and Denoising Imaging for Dynamic Scenes](https://mlsanity.com/paper/2206.09611/) (2022)
- [Modeling Dual-Exposure Quad-Bayer Patterns for Joint Denoising and Deblurring](https://mlsanity.com/paper/2412.07256/) (2024)

## 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.