Statistical analysis of image quality measures

In this paper we conduct a statistical analysis of the sensitivity and consistency behavior of objective image quality measures. We categorize the quality measures and compare them for still image compression applications. The measures have been categorized into pixel difference-based, correlation-based, edge-based, spectral-based, context-based and HVS-based (Human Visual System-based) measures. The mutual relationships between the measures are visualized by plotting their Kohonen maps. Their consistency and sensitivity to coding as well as additive noise and blur are investigated via ANOVA analysis of their scores. It has been found that measures based on HVS, on phase spectrum and on multiresolution mean square error are most discriminative to coding artifacts.