Gradient-Based Structural Similarity for Image Quality Assessment

Objective quality assessment has been widely used in image processing for decades and many researchers have been studying the objective quality assessment method based on human visual system (HVS). Recently the structural similarity (SSIM) is proposed, under the assumption that the HVS is highly adapted for extracting structural information from a scene, and simulation results have proved that it is better than PSNR (or MSE), By deeply studying the SSIM, we find it fails in measuring the badly blurred images. Based on this, we develop an improved method which is called gradient-based structural similarity (GSSIM). Experiment results show that GSSIM is more consistent with HVS than SSIM and PSNR especially for blurred images.