Detection and estimation of supra-threshold distortion levels of pictures based on just-noticeable difference
Kaifang Yang, Shuai Wan, Hong Ren Wu, Weisi Lin, Damian M. Tan, Yanchao Gong, Leyi Xie · 2016
A subjective assessment method is described to determine picture quality levels in the supra-threshold region for processed images, with reference to their original counterparts, based on just-noticeable difference (JND) detection experiment. It has been found that the range of JND levels is dependent on picture contents and can be predicted as a function of texture masking factor computed in the pixel domain. The experimental data obtained also reveal that relationship of JND levels in the supra-threshold region and the MSE (mean squared error) can be approximated by a linear function whose slope is modeled as a function of edge and texture contrast masking factors. The model is devised to predict JND levels which provide subjective picture quality rating discernible by human viewers and can be used for visual quality regulated image/video coding, as well as evaluating the capacity of existing objective metrics in predicting picture quality and/or distortion relative to JND based quality/distortion rating categories.