A Vector Approach for Image Quality Assessment and Some Metrological Considerations

The main purpose of this paper is to present a metrology-based view of the image quality assessment (IQA) field. Three main topics are developed. First, the state of the art in the field of IQA is presented, providing a classification of some of the most important objective and subjective IQA methods. Then, some aspects of the field are analyzed from a metrological point of view, also through a comparison with the software quality measurement area. In particular, a statistical approach to the evaluation of the uncertainty for IQA objective methods is presented, and the topic of measurement modeling for subjective IQA methods is analyzed. Finally, a vector approach for full-reference IQA is discussed, with applications to images corrupted by impulse and Gaussian noise. For these applications, the vector root mean squared error (VRMSE) and fuzzy VRMSE are introduced. These vector parameters provide a possible way to overcome the main limitations of the mean-squared-error-based IQA methods.