A natural image quality evaluation metric

Reduced-reference (RR) image quality assessment (IQA) metrics evaluate the quality of a distorted (or degraded) image by using some, not all, information of the original (reference) image. In this paper, we propose a novel RR IQA metric based on hybrid wavelets and directional filter banks (HWD). With HWD as a pre-processing stage, the newly proposed metric mainly focuses on subbands coefficients of the distorted and original images. It performs well under low data rate, because only a threshold and several proportion values are recorded from the original images and transmitted. Experiments are carried out upon well recognized data sets and the results demonstrate advantages of the metric compared with existing ones. Moreover, a separate set of experiments shows that this proposed metric has good consistency with human subjective perception.