Posterior capsule opacification (PCO) is a common complication in patients who have undergone cataract surgery, occurring in up to 50% of patients by two to three years after the operation. Assessment of PCO has been mainly subjective, making it difficult to understand its progression over time or assess the effectiveness of strategies used for the prevention of PCO. Fully automated PCO assessment systems developed so far offer objective grades. However, they do not provide morphological PCO data useful for an effective analysis of scores. This paper proposes a novel method based on multiscale roughness estimation to detect and quantify the PCO areas. This method is also characterized by its robustness against monotonic illumination variations. Extensive experimentation showcases a distinctive analysis and assessment power of our method compared to other competitive methods. The results show a high correlation of 84.6% with respect to clinical scores.