# A Review of an Old Dilemma: Demosaicking First, or Denoising First?

arXiv: https://arxiv.org/abs/2004.11577 · HTML: https://mlsanity.com/paper/2004.11577/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Apr 2020.

## Built on by (most cited first, 14 of 14)

- [AP-BSN: Self-Supervised Denoising for Real-World Images via Asymmetric PD and Blind-Spot Network](https://mlsanity.com/paper/2203.11799/) (2022)
- [Joint Denoising and Demosaicking with Green Channel Prior for Real-world Burst Images](https://mlsanity.com/paper/2101.09870/) (2021)
- [Exploring Efficient Asymmetric Blind-Spots for Self-Supervised Denoising in Real-World Scenarios](https://mlsanity.com/paper/2303.16783/) (2023)
- [A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shift](https://mlsanity.com/paper/2203.09294/) (2022)
- [Efficient Unified Demosaicing for Bayer and Non-Bayer Patterned Image Sensors](https://mlsanity.com/paper/2307.10667/) (2023)
- [Joint Demosaicking and Denoising in the Wild: The Case of Training Under Ground Truth Uncertainty](https://mlsanity.com/paper/2101.04442/) (2021)
- [Joint Demosaicing and Denoising with Double Deep Image Priors](https://mlsanity.com/paper/2309.09426/) (2023)
- [How to Best Combine Demosaicing and Denoising?](https://mlsanity.com/paper/2408.06684/) (2024)
- [NM-FlowGAN: Modeling sRGB Noise without Paired Images using a Hybrid Approach of Normalizing Flows and GAN](https://mlsanity.com/paper/2312.10112/) (2023)
- [Toward Accurate and Temporally Consistent Video Restoration from Raw Data](https://mlsanity.com/paper/2312.16247/) (2023)
- [Combining Pre- and Post-Demosaicking Noise Removal for RAW Video](https://mlsanity.com/paper/2410.02572/) (2024)
- [CARD: Correlation Aware Restoration with Diffusion](https://mlsanity.com/paper/2512.05268/) (2025)
- [Physen-Noise2Noise: Physics-Guided Self-Supervised Defocus Deblurring with Bias Correction under Low-Light Conditions](https://mlsanity.com/paper/2605.24590/) (2026)
- [sRGB Real Noise Modeling via Noise-Aware Sampling with Normalizing Flows](https://mlsanity.com/paper/2608.29038/) (2026)

## Abstract (arXiv)

Image denoising and demosaicking are the most important early stages in digital camera pipelines. They constitute a severely ill-posed problem that aims at reconstructing a full color image from a noisy color filter array (CFA) image. In most of the literature, denoising and demosaicking are treated as two independent problems, without considering their interaction, or asking which should be applied first. Several recent works have started addressing them jointly in works that involve heavy weight CNNs, thus incompatible with low power portable imaging devices. Hence, the question of how to combine denoising and demosaicking to reconstruct full color images remains very relevant: Is denoising to be applied first, or should that be demosaicking first? In this paper, we review the main variants of these strategies and carry-out an extensive evaluation to find the best way to reconstruct full color images from a noisy mosaic. We conclude that demosaicking should applied first, followed by denoising. Yet we prove that this requires an adaptation of classic denoising algorithms to demosaicked noise, which we justify and specify.