  This paper presents a full-reference image quality estimator based on SIFT
descriptor matching over reliability-weighted feature maps. Reliability
assignment includes a smoothing operation, a transformation to perceptual color
domain, a local normalization stage, and a spectral residual computation with
global normalization. The proposed method ReSIFT is tested on the LIVE and the
LIVE Multiply Distorted databases and compared with 11 state-of-the-art
full-reference quality estimators. In terms of the Pearson and the Spearman
correlation, ReSIFT is the best performing quality estimator in the overall
databases. Moreover, ReSIFT is the best performing quality estimator in at
least one distortion group in compression, noise, and blur category.
