# Edge-Aware Image Color Appearance and Difference Modeling

arXiv: https://arxiv.org/abs/2304.10669 · HTML: https://mlsanity.com/paper/2304.10669/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 49 references that are in the map.
- First posted on arXiv 20 Apr 2023.

## Builds on (most cited first, 1 of 1)

- [A Hitchhiker's Guide to Structural Similarity](https://mlsanity.com/paper/2101.06354/) (2021)

## Abstract (arXiv)

The perception of color is one of the most important aspects of human vision. From an evolutionary perspective, the accurate perception of color is crucial to distinguishing friend from foe, and food from fatal poison. As a result, humans have developed a keen sense of color and are able to detect subtle differences in appearance, while also robustly identifying colors across illumination and viewing conditions. In this paper, we shall briefly review methods for adapting traditional color appearance and difference models to complex image stimuli, and propose mechanisms to improve their performance. In particular, we find that applying contrast sensitivity functions and local adaptation rules in an edge-aware manner improves image difference predictions.