DocumentCode :
1439990
Title :
FSIM: A Feature Similarity Index for Image Quality Assessment
Author :
Zhang, Lin ; Zhang, Lei ; Mou, Xuanqin ; Zhang, David
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., Kowloon, China
Volume :
20
Issue :
8
fYear :
2011
Firstpage :
2378
Lastpage :
2386
Abstract :
Image quality assessment (IQA) aims to use computational models to measure the image quality consistently with subjective evaluations. The well-known structural similarity index brings IQA from pixel- to structure-based stage. In this paper, 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 databases demonstrate that FSIM can achieve much higher consistency with the subjective evaluations than state-of-the-art IQA metrics.
Keywords :
image processing; FSIM; IQA; feature similarity index; human visual system; image gradient magnitude; image local quality; image quality assessment; phase congruency; structural similarity index; Feature extraction; Gabor filters; Image color analysis; Indexes; Measurement; Visualization; Gradient; image quality assessment (IQA); low-level feature; phase congruency (PC); Algorithms; Databases, Factual; Humans; Image Processing, Computer-Assisted; Models, Theoretical; Reproducibility of Results; Visual Perception;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2011.2109730
Filename :
5705575
Link To Document :
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