A New Image Quality Metric using System Visual Human Characteristics

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 the dynamic characteristics and on the just-noticeable-difference threshold characteristics introduced by Weber's law: the relative weighted Peak to Signal Noise Ratio. Our experiments on various image distortion types indicate that our metric performs significantly better than the widely used distortion metric Mean Squared Error. We should that the rwPSNR correlates with human perception of image quality.