  The goal of most subjective studies is to place a set of stimuli on a
perceptual scale. This is mostly done directly by rating, e.g. using single or
double stimulus methodologies, or indirectly by ranking or pairwise comparison.
All these methods estimate the perceptual magnitudes of the stimuli on a scale.
However, procedures such as Maximum Likelihood Difference Scaling (MLDS) have
shown that considering perceptual distances can bring benefits in terms of
discriminatory power, observers' cognitive load, and the number of trials
required. One of the disadvantages of the MLDS method is that the perceptual
scales obtained for stimuli created from different source content are generally
not comparable. In this paper, we propose an extension of the MLDS method that
ensures inter-content comparability of the results and shows its usefulness
especially in the presence of observer errors.
