A new quality metric based on just-noticeable difference, perceptual regions, edge extraction and human vision

Several human visual system (HVS)-based quality metrics have been developed in recent years to measure the quality distortions caused by digital image coding techniques. Because of the complicated nature of the HVS characteristics, these metrics do not provide acceptable correlation with perceptual evaluations of the distortion. Recent studies by the Visual Quality Experts Group (VQEG) also show that the current HVS-based techniques do not provide a clear advantage over a mathematically defined technique such as mean square error (MSE). Therefore, this paper proposes a new quality metric based on just-noticeable-difference threshold characteristics in the perceptual regions (dark, De Vries-Rose, Weber and saturation regions), extraction of visually important edge details and human vision (low-level and high-level vision). Families of perceptual weights that are suitable for digitally compressed images with different distortions are generated, using compressed versions of a gradient image as stimuli and human observers in a subjective test. The simulations show that the proposed metric successfully measures the quality distortion and provides high correlation with both mathematical and HVS-based measures.