Relationship between colour themes and perceived aesthetic quality in colour images: an exploratory study

Computational image aesthetics aims at determining what makes an image look pleasing. Assessing image aesthetics usually relies on the extraction of suitable image features related, for instance, to image composition (e.g. rule of third, depth of field), texture, shape and colour. It is widely accepted that colour, in particular, plays a major role in this context. The objective of this study was to investigate potential relationships between the most significant colours in an image (the colour theme, or palette) and the aesthetic rating. To this end we defined a procedure for colour palette extraction and its characterisation by a set of 21 hand-crafted features. Rank-based correlations between the features and manually-assigned aesthetic ratings were assessed by Spearman’s correlation coefficient. Experimenting on a total of 4,647 images from the public dataset EVA we found that 12 features were significantly associated with image aesthetics, although the overall correlation strength was at best weak. In particular, perceived aesthetic rating correlated positively with saturation (indicating a slight preference for colourfulness) and negatively with colour temperature (suggesting a slight preference for warm colours). A significant positive correlation (but again weak) also emerged between perceived aesthetic and harmonic colour schemes.