Automatic image quality assessment technique incorporating higher level perceptual factors

We present an objective image quality assessment technique which is based on the properties of the human visual system (HVS). It consists of two major components: an early vision model (multi-channel and designed specifically for complex natural images), and a visual attention model which indicates regions of interest in a scene through the use of Importance Maps. Visible errors are then weighted, depending on the perceptual importance of the region in which they occur. We show that this technique produces a high correlation with subjective test data (0.93), compared to only 0.65 for PSNR. This technique is particularly useful for images coded with spatially varying quality.