Perceptual quality assessment of digital images and videos are important for various image-processing applications.
For assessing the image quality, researchers have often used the idea of visual masking (or distortion
visibility) to design image-quality predictors specifically for the near-threshold distortions. However, it is still
unknown that while assessing the quality of natural images, how the local distortion visibilities relate with the
local quality scores. Furthermore, the summing mechanism of the local quality scores to predict the global quality
scores is also crucial for better prediction of the perceptual image quality. In this paper, the local and global
qualities of six images and six distortion levels were measured using subjective experiments. Gabor-noise target
was used as distortion in the quality-assessment experiments to be consistent with our previous study [Alam,
Vilankar, Field, and Chandler, Journal of Vision, 2014], in which the local root-mean-square contrast detection
thresholds of detecting the Gabor-noise target were measured at each spatial location of the undistorted images.
Comparison of the results of this quality-assessment experiment and the previous detection experiment shows
that masking predicted the local quality scores more than 95% correctly above 15 dB threshold within 5% subject
scores. Furthermore, it was found that an approximate squared summation of local-quality scores predicted the
global quality scores suitably (Spearman rank-order correlation 0:97).