Screen content image quality assessment using Euclidean distance

Considering that human visual system (HVS) is greatly sensitive to edge, in this study, we design a new full-reference objective quality assessment method for screen content images (SCIs). The key novelty lies in the extracting of the edge information by computing the Euclidean distance of luminance in the SCIs. Since HVS is greatly suitable for extracting structural information, the structure information is incorporated into our proposed model. The extracted information is then used to compute the similarity maps of the reference SCI and its distorted SCI. Finally, we combine the obtained maps by using our designed pooling strategy. Experience results have shown that the designed method get higher correlation with the subjective quality score than state-of-the-art quality assessment models.