We want to integrate colourfulness in an image quality evaluation framework. This quality framework is meant to evaluate the perceptual impact of a compression algorithm or an error prone communication channel on the quality of an image. The image might go through various enhancement or compression algorithms, resulting in a different -- but not necessarily worse -- image. In other words, we will measure quality but not fidelity to the original picture.While modern colour appearance models are able to predict the perception of colourfulness of simple patches on uniform backgrounds, there is no agreement on how to measure the overall colourfulness of a picture of a natural scene. We try to quantify the colourfulness in natural images to perceptually qualify the effect that processing or coding has on colour. We set up a psychophysical category scaling experiment, and ask people to rate images using 7 categories of colourfulness. We then fit a metric to the results, and obtain a correlation of over 90% with the experimental data. The metric is meant to be used real time on video streams. We ignored any issues related to hue in this paper.