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Weighted Feature Similarity – A Nonlinear Combination of Gradient and Phase Congruency for Full-Reference Image Quality Assessment

  • Krzysztof Okarma
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 184)

Summary

In the paper the modified Feature Similarity metric has been discussed which is based on the nonlinear combination of two elements being the basics of the recently developed Feature Similarity metric for full-reference image quality assessment. Nevertheless, the influence of the gradient magnitude and phase congruency, used as two main elements of the metric, on the perceived quality is not necessarily equal. For this reason some experiments have been conducted in order to propose the weighting coefficients, applied as the local exponents, increasing the rank order correlation coefficients with subjective quality evaluations. The verification of the obtained results has been conducted using 5 ”state-of-the-art” benchmark databases and the obtained weighted FSIM metric’s performance results are better for all of them.

Keywords

Mean Opinion Score Image Quality Assessment Subjective Score Greyscale Image Image Quality Metrics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Faculty of Electrical Engineering, Department of Signal Processing and Multimedia EngineeringWest Pomeranian University of Technology, SzczecinSzczecinPoland

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