Zhang等人

利用相位一致性信息的特性，提出了

特征相似性方法(FSIMG) ，选取了相位一致性信息和梯度信息

作为它的两个特征，得到了较好的结果。

-A novel feature similarity

(FSIM) index for full reference IQA is proposed based on the fact that

human visual system (HVS) understands an image mainly according to

its low-level features. Specifically, the phase congruency (PC), which is a

dimensionless measure of the significance of a local structure, is used as the

primary feature in FSIM. Considering that PC is contrast invariant while

the contrast information does affect HVS’ perception of image quality, the

image gradient magnitude (GM) is employed as the secondary feature in

FSIM. PC and GM play complementary roles in characterizing the image

local quality. After obtaining the local quality map, we use PC again as a

weighting function to derive a single quality score. Extensive experiments

performed on six benchmark IQA s demonstrate that FSIM can

achieve much higher consistency with the subjective　uations than

state-of-the-art IQA metrics.