Reduced reference image quality assessment using regularity of phase congruency

• We propose a powerful model SPCRM for RR-IQA.
• SPCRM is via fractal analysis on the regularity of the phase congruency.
• SPCRM is evaluated on seven public benchmark datasets.
• The performance of SPCRM is much better than those of state-of-the-art approaches.

In this paper, a reduced-reference image quality assessment metric is proposed, which measures the difference of the regularity of the phase congruency (PC) between the reference image and the distorted image. The proposed model adopts a three-stage approach. The PC of the image is first extracted, then the fractal dimensions are computed on PC as the image features that characterize the image structures from the view of the spatial distribution. Finally the image features are pooled as the quality score using ℓ1 distance. The proposed approach is evaluated on seven public benchmark databases. Experimental results have demonstrated the excellent performance of the proposed approach.