Full-Reference Calibration-Free Image Quality Assessment

TL;DR

This paper introduces new full-reference image quality assessment techniques that are inherently linearly correlated with human scores without requiring calibration, improving comparability across different systems and viewing conditions.

Contribution

The paper presents calibration-free FR IQA methods rooted in estimation theory and psycho-physical principles, applicable to various image degradations and related to viewing distance.

Findings

High linear correlation with human scores

Effective across different image degradations

Comparable or superior to calibration-based methods

Abstract

One major problem of objective Image Quality Assessment (IQA) methods is the lack of linearity of their quality estimates with respect to scores expressed by human subjects. For this reason, usually IQA metrics undergo a calibration process based on subjective quality examples. However, example-based training makes generalization problematic, hampering result comparison across different applications and operative conditions. In this paper, new Full Reference (FR) techniques, providing estimates linearly correlated with human scores without using calibration are introduced. To reach this objective, these techniques are deeply rooted on principles and theoretical constraints. Restricting the interest on the IQA of the set of natural images, it is first recognized that application of estimation theory and psycho physical principles to images degraded by Gaussian blur leads to a so-called canonical IQA method, whose estimates are not only highly linearly correlated to subjective scores, but are also straightforwardly related to the Viewing Distance (VD). Then, it is shown that mainstream IQA methods can be reconducted to the canonical method applying a preliminary metric conversion based on a unique specimen image. The application of this scheme is then extended to a significant class of degraded images other than Gaussian blur, including noisy and compressed images. The resulting calibration-free FR IQA methods are suited for applications where comparability and interoperability across different imaging systems and on different VDs is a major requirement. A comparison of their statistical performance with respect to some conventional calibration prone methods is finally provided.