RRAR: A novel reduced-reference IQA algorithm for facial images

Image Quality Assessment (IQA) aims at automatically predicting the perceptual quality of targets with low computation complexity and high precision. However, it is usually very hard to combine all these merits into one algorithm. In this paper, we propose simple yet efficient facial image quality assessment algorithm - Reduced-Reference Automatic Ranking (RRAR) for face recognition. The RRAR contains a quality control stage and quality ranking stage based on modified structural similarity - Reduced-Reference of SSIM as the reduced reference IQA module. Experimental results show that the proposed algorithm increases the precision of face recognition with low memory consumption and computation complexity and works exceptionally well with face images captured under uncontrolled environment.