Unveiling Relationships between Regions of Interest and Image Fidelity Metrics

This paper presents the results of two computational experiments designed to investigate whether the success of recent image fidelity metrics can be attributed to the fact that these metrics implicitly incorporate region-of-interest information. Modified versions of four metrics (PSNR, WSNR, SSIM, and VIF) were created by incorporating spatially varying weights chosen to maximize correlation between each metric and subjective ratings of fidelity for images from the LIVE image database. The results reveal that all metrics can benefit from spatially varying weights, especially when the regions are hand-chosen based upon the objects in an image. However, the results suggest that PSNR and VIF would benefit the most from spatial weighting in which the weights are determined based on region of interest information. Additionally, the results show that object based regions follow an intuitive weighting pattern.