  While intuitive for humans, the concept of visual complexity is hard to
define and quantify formally. We suggest adopting the multi-scale structural
complexity (MSSC) measure, an approach that defines structural complexity of an
object as the amount of dissimilarities between distinct scales in its
hierarchical organization. In this work, we apply MSSC to the case of visual
stimuli, using an open dataset of images with subjective complexity scores
obtained from human participants (SAVOIAS). We demonstrate that MSSC correlates
with subjective complexity on par with other computational complexity measures,
while being more intuitive by definition, consistent across categories of
images, and easier to compute. We discuss objective and subjective elements
inherently present in human perception of complexity and the domains where the
two are more likely to diverge. We show how the multi-scale nature of MSSC
allows further investigation of complexity as it is perceived by humans.
