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Hybrid Objective Metric for Image Quality Assessment

Journal: International Journal of Science and Research (IJSR) (Vol.2, No. 4)

Publication Date:

Authors : ; ; ;

Page : 323-327

Keywords : Image quality assessment; phase congruency; gradient; low-level feature;

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Image Quality Assessment (IQA) goal is to use computational models to measure the image quality consistently with subjective evaluations. In this paper, a peculiar feature-similarity (FSIM) index for full reference IQA is proposed based on the fact that human visual system (HVS) perceives an image mainly according to its low-level features. Specifically, the phase congruency (PC), which is a dimension less measure of significance of a local structure, is used as the primary feature. Considering that PC is unaffected by contrast, while the contrast information does affect the HVS� perception of image quality, the image gradient magnitude is employed as the secondary feature in FSIM. After obtaining the local quality map, we use PC again as a weighting function to derive single quality score. Extensive experiments performed on TID2008, a widely using bench mark IQA database demonstrated that FSIM can achieve much higher consistency with the subjective evaluations than state-of- the -art IQA metrics.

Last modified: 2021-06-30 20:15:34