A Lightweight Quality Assessment of Screen Content Images using Directional Derivative Filters

In this paper, we present a lightweight visual quality assessment of screen content image (SCI) based on the local luminance edge directions and gradient magnitude. First, we use directional derivative filters (DDFs) to extract the edge direction feature which is one of the main characteristics of SCIs. To obtain the perceptual quality measures, we separately extract the edge direction and gradient magnitude for the similarity computation between the reference and distorted SCIs. Finally, considering the computational complexity, we incorporate the DDF-based feature map with the gradient magnitude map together to generate a new visual quality metric. Experimental results have demonstrated that the proposed method is able to adapt better to the human visual system than 12 representative methods based on the screen image quality assessment database (SIQAD)
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