# Joint Defogging and Demosaicking

arXiv: https://arxiv.org/abs/1602.02885 · HTML: https://mlsanity.com/paper/1602.02885/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Feb 2016.

## Built on by (most cited first, 3 of 3)

- [Deep Joint Demosaicing and High Dynamic Range Imaging within a Single Shot](https://mlsanity.com/paper/2111.07281/) (2021)
- [Lightweight HDR Camera ISP for Robust Perception in Dynamic Illumination Conditions via Fourier Adversarial Networks](https://mlsanity.com/paper/2204.01795/) (2022)
- [FujinSplat: Seeing Through Smoke with RAW-Domain Gaussian Splatting](https://mlsanity.com/paper/2609.06017/) (2026)

## Abstract (arXiv)

Image defogging is a technique used extensively for enhancing visual quality of images in bad weather condition. Even though defogging algorithms have been well studied, defogging performance is degraded by demosaicking artifacts and sensor noise amplification in distant scenes. In order to improve visual quality of restored images, we propose a novel approach to perform defogging and demosaicking simultaneously. We conclude that better defogging performance with fewer artifacts can be achieved when a defogging algorithm is combined with a demosaicking algorithm simultaneously. We also demonstrate that the proposed joint algorithm has the benefit of suppressing noise amplification in distant scene. In addition, we validate our theoretical analysis and observations for both synthesized datasets with ground truth fog-free images and natural scene datasets captured in a raw format.