A simple modification to the inference process of Murray’s (2020) MIR improves the model’s performance

Murray (2020) recently introduced a novel computational lightness model, Markov Illuminance and Reflectance (MIR), a Bayesian observer model that represents input information and prior assumption with conditional random field (CRF) and that can account for many lightness illusions and phenomena. In the original MIR’s inference process, however, it did not utilize all the links in its CRF. Thus, this letter reports that a simple modification to the original MIR’s inference process improves its performance. MIR is a highly extensible model, so I recommend future research use the proposed version to attain further sophistication.