Blind image quality assessment in the complex frequency domain

Abstract

In this paper, we propose a no-reference (NR) image quality assessment (IQA) metric that operates in the complex frequency domain. A set of features are developed to model the natural scene statistics without depending on any specific visual distortion. The proposed approach relies on a statistical analysis of the transformed image, involving the importance of the phase and magnitude provided by the underlying complex coefficients. We further investigate the correlation between the different image spatial-frequency resolutions, i.e., representations under different scales and orientations in order to extract the directional features and energy distributions of an image. The validation of the NR metric is performed on a variety of challenging IQA databases and the obtained results show good correlation with subjective scores. Besides, the obtained performance is highly competitive compared to the top-performing NR IQA metrics.