# Deep White-Balance Editing

arXiv: https://arxiv.org/abs/2004.01354 · HTML: https://mlsanity.com/paper/2004.01354/

## Key facts

- Cited by 54 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Apr 2020.

## Built on by (most cited first, 30 of 54)

- [You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction](https://mlsanity.com/paper/2205.14871/) (2022)
- [Harmonizer: Learning to Perform White-Box Image and Video Harmonization](https://mlsanity.com/paper/2207.01322/) (2022)
- [SSH: A Self-Supervised Framework for Image Harmonization](https://mlsanity.com/paper/2108.06805/) (2021)
- [Lighting up NeRF via Unsupervised Decomposition and Enhancement](https://mlsanity.com/paper/2307.10664/) (2023)
- [StarEnhancer: Learning Real-Time and Style-Aware Image Enhancement](https://mlsanity.com/paper/2107.12898/) (2021)
- [Auto White-Balance Correction for Mixed-Illuminant Scenes](https://mlsanity.com/paper/2109.08750/) (2021)
- [Semi-Supervised Raw-to-Raw Mapping](https://mlsanity.com/paper/2106.13883/) (2021)
- [Progressive Joint Low-light Enhancement and Noise Removal for Raw Images](https://mlsanity.com/paper/2106.14844/) (2021)
- [Beyond the Pixel: a Photometrically Calibrated HDR Dataset for Luminance and Color Prediction](https://mlsanity.com/paper/2304.12372/) (2023)
- [Lumina-OmniLV: A Unified Multimodal Framework for General Low-Level Vision](https://mlsanity.com/paper/2504.04903/) (2025)
- [Taming Lookup Tables for Efficient Image Retouching](https://mlsanity.com/paper/2403.19238/) (2024)
- [Computational Optics for Mobile Terminals in Mass Production](https://mlsanity.com/paper/2305.05886/) (2023)
- [Time-Aware Auto White Balance in Mobile Photography](https://mlsanity.com/paper/2504.05623/) (2025)
- [Unifying Color and Lightness Correction with View-Adaptive Curve Adjustment for Robust 3D Novel View Synthesis](https://mlsanity.com/paper/2602.18322/) (2026)
- [Exposure Correction Model to Enhance Image Quality](https://mlsanity.com/paper/2204.10648/) (2022)
- [Modeling the Lighting in Scenes as Style for Auto White-Balance Correction](https://mlsanity.com/paper/2210.09090/) (2022)
- [Revisiting Image Fusion for Multi-Illuminant White-Balance Correction](https://mlsanity.com/paper/2503.14774/) (2025)
- [DRL-ISP: Multi-Objective Camera ISP with Deep Reinforcement Learning](https://mlsanity.com/paper/2207.03081/) (2022)
- [Deep Metric Learning for Unsupervised Remote Sensing Change Detection](https://mlsanity.com/paper/2303.09536/) (2023)
- [Discovering an Image-Adaptive Coordinate System for Photography Processing](https://mlsanity.com/paper/2501.06448/) (2025)
- [Color Matching Using Hypernetwork-Based Kolmogorov-Arnold Networks](https://mlsanity.com/paper/2503.11781/) (2025)
- [CHROMA: Consistent Harmonization of Multi-View Appearance via Bilateral Grid Prediction](https://mlsanity.com/paper/2507.15748/) (2025)
- [After the Party: Navigating the Mapping From Color to Ambient Lighting](https://mlsanity.com/paper/2508.02168/) (2025)
- [High-resolution Photo Enhancement in Real-time: A Laplacian Pyramid Network](https://mlsanity.com/paper/2510.11613/) (2025)
- [FWB-Net:Front White Balance Network for Color Shift Correction in Single Image Dehazing via Atmospheric Light Estimation](https://mlsanity.com/paper/2101.08465/) (2021)
- [Multi-color balance for color constancy](https://mlsanity.com/paper/2105.10228/) (2021)
- [Deterministic Neural Illumination Mapping for Efficient Auto-White Balance Correction](https://mlsanity.com/paper/2308.03939/) (2023)
- [Unified-EGformer: Exposure Guided Lightweight Transformer for Mixed-Exposure Image Enhancement](https://mlsanity.com/paper/2407.13170/) (2024)
- [CleAR: Robust Context-Guided Generative Lighting Estimation for Mobile Augmented Reality](https://mlsanity.com/paper/2411.02179/) (2024)
- [Leveraging Multispectral Sensors for Color Correction in Mobile Cameras](https://mlsanity.com/paper/2512.08441/) (2025)

## Abstract (arXiv)

We introduce a deep learning approach to realistically edit an sRGB image's white balance. Cameras capture sensor images that are rendered by their integrated signal processor (ISP) to a standard RGB (sRGB) color space encoding. The ISP rendering begins with a white-balance procedure that is used to remove the color cast of the scene's illumination. The ISP then applies a series of nonlinear color manipulations to enhance the visual quality of the final sRGB image. Recent work by [3] showed that sRGB images that were rendered with the incorrect white balance cannot be easily corrected due to the ISP's nonlinear rendering. The work in [3] proposed a k-nearest neighbor (KNN) solution based on tens of thousands of image pairs. We propose to solve this problem with a deep neural network (DNN) architecture trained in an end-to-end manner to learn the correct white balance. Our DNN maps an input image to two additional white-balance settings corresponding to indoor and outdoor illuminations. Our solution not only is more accurate than the KNN approach in terms of correcting a wrong white-balance setting but also provides the user the freedom to edit the white balance in the sRGB image to other illumination settings.