Perceptual Quality Metric Applied to Wavelet-Based 2D Region of Interest Image Coding

Region of interest ROI image and video compression techniques have been widely used in visual communication applications in an effort to deliver good quality images and videos at limited bandwidths. Foveated imaging exploits the fact that the spatial resolution of the human visual system (HVS) is highest around the point of fixation (foveation point) and decreases dramatically with increasing eccentricity. Exploiting this fact, we have developed an appropriate metric for the assessment of ROI coded images, adapted to foveation image coding based on psychovisual quality optimization tools, which objectively enable to assess the visual quality measurement with respect to the region of interest (ROI) of the human observer. The proposed metric yields a quality factor called foveation probability score (FPS) that correlates well with visual error perception, and demonstrating very good perceptual quality evaluation. Thus, we avoid the traditional subjective criteria called mean opinion score (MOS), which involves human observers, are inconvenient, time-consuming, and influenced by environmental conditions. Widely used pixelwise measures such as the mean square error (MSE) and the peak signal to noise ratio (PSNR) cannot capture the artifacts like blurriness or blockiness. The model therefore called the FoveatedWavelet Visible Difference Predictor FWVDP, is based both on traditional psychometric function and the Daly model visible difference predictor (VDP) and integrates various psychovisual models (foveation, luminance and contrast masking). Experiments show that FWVDP integrates foveation filtering with foveated image coding and demonstrates very good performance in terms of foveated image quality measurement.