A joint image quality assessment method based on global phase coherence and structural similarity

Abstract

Structural similarity (SSIM) is one image quality assessment metric that focuses on the statistic information in the spatial domain. It cannot reflect the small details of the contrast and the changing of texture, which can be perceived by human visual system, because SSIM cannot detect the distortion image with aliasing and blur effectively. This paper proposes a new image quality assessment metric called structural similarity based on global phase coherence (GPC-SSIM), which considers both the structural information in the spatial domain and the phase characteristics in the frequency domain. Through experiments, as the level of blur and aliasing of an image gets more and more serious, the dynamic range of the results obtained through SSIM is 0.6~1, while the ones through the new assessment index GPC_SSIM is 0~1. Thus GPC-SSIM is more sensitive to the blur and aliasing of image and can give more accurate assessment results for various kinds of degraded images than SSIM.