# Beyond Fixed Luminance: Towards Panchromatic and Orthochromatic Image Colorization

arXiv: https://arxiv.org/abs/2608.10798 · HTML: https://mlsanity.com/paper/2608.10798/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 21 of its 44 references that are in the map.
- First posted on arXiv 11 Aug 2026.

## Builds on (most cited first, 21 of 21)

- [ImageNet Large Scale Visual Recognition Challenge](https://mlsanity.com/paper/1409.0575/) (2014)
- [DINOv2: Learning Robust Visual Features without Supervision](https://mlsanity.com/paper/2304.07193/) (2023)
- [BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models](https://mlsanity.com/paper/2301.12597/) (2023)
- [Adding Conditional Control to Text-to-Image Diffusion Models](https://mlsanity.com/paper/2302.05543/) (2023)
- [Large Scale GAN Training for High Fidelity Natural Image Synthesis](https://mlsanity.com/paper/1809.11096/) (2018)
- [Colorful Image Colorization](https://mlsanity.com/paper/1603.08511/) (2016)
- [FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space](https://mlsanity.com/paper/2506.15742/) (2025)
- [COCO-Stuff: Thing and Stuff Classes in Context](https://mlsanity.com/paper/1612.03716/) (2016)
- [Colorization Transformer](https://mlsanity.com/paper/2102.04432/) (2021)
- [Instance-aware Image Colorization](https://mlsanity.com/paper/2005.10825/) (2020)
- [ChromaGAN: Adversarial Picture Colorization with Semantic Class Distribution](https://mlsanity.com/paper/1907.09837/) (2019)
- [Towards Vivid and Diverse Image Colorization with Generative Color Prior](https://mlsanity.com/paper/2108.08826/) (2021)
- [DDColor: Towards Photo-Realistic Image Colorization via Dual Decoders](https://mlsanity.com/paper/2212.11613/) (2022)
- [BigColor: Colorization using a Generative Color Prior for Natural Images](https://mlsanity.com/paper/2207.09685/) (2022)
- [Control Color: Multimodal Diffusion-based Interactive Image Colorization](https://mlsanity.com/paper/2402.10855/) (2024)
- [Time-Travel Rephotography](https://mlsanity.com/paper/2012.12261/) (2020)
- [Diffusing Colors: Image Colorization with Text Guided Diffusion](https://mlsanity.com/paper/2312.04145/) (2023)
- [Improved Diffusion-based Image Colorization via Piggybacked Models](https://mlsanity.com/paper/2304.11105/) (2023)
- [Focusing on Persons: Colorizing Old Images Learning from Modern Historical Movies](https://mlsanity.com/paper/2108.06515/) (2021)
- [MultiColor: Image Colorization by Learning from Multiple Color Spaces](https://mlsanity.com/paper/2408.04172/) (2024)
- [ColorNet -- Estimating Colorfulness in Natural Images](https://mlsanity.com/paper/1908.08505/) (2019)

## Abstract (arXiv)

Most image colorization systems operate in Lab space by predicting chroma (ab) while preserving an input-derived luminance channel (L). While effective on standard benchmarks, this fixed-luminance design restricts brightness changes and becomes unreliable when grayscale formation deviates from natural-image luminance, as in historical orthochromatic photography. We propose a luminance-agnostic colorization framework that formulates colorization as full-RGB image editing using a foundation image-editing model. To bridge modern panchromatic and historical orthochromatic conditions, we introduce a mixed grayscale objective that trains the model under both standard luminance grayscale and a red-insensitive grayscale formation. Experiments on COCO, ImageNet, and a multi-instance benchmark show that our method is competitive on standard grayscale inputs and substantially more robust under orthochromatic inputs, with qualitative comparisons and a human study indicating fewer visible color artifacts.