In this paper, we propose a no-reference (NR) image quality assess- ment (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 cor- relation 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 im- age. The validation of the NR metric is performed on a variety of challenging IQA databases and the obtained results show good cor- relation with subjective scores. Besides, the obtained performance is highly competitive compared to the top-performing NR IQA met- rics.