Fourier transform based scalable image quality measure

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Manish NarwariaLiang-Tien Chia

Abstract

We present a new image quality assessment (IQA) algorithm based on the phase and magnitude of the 2D (twodimensional) Discrete Fourier Transform (DFT). The basic idea is to compare the phase and magnitude of the reference and distorted images to compute the quality score. However, it is well known that the Human Visual Systems (HVSs) sensitivity to different frequency components is not the same. We accommodate this fact via a simple yet effective strategy of nonuniform binning of the frequency components. This process also leads to reduced space representation of the image thereby enabling the reduced-reference (RR) prospects of the proposed scheme. We employ linear regression to integrate the effects of the changes in phase and magnitude. In this way, the required weights are determined via proper training and hence more convincing and effective. Lastly, using the fact that phase usually conveys more information than magnitude, we use only the phase for RR quality assessment. This provides the crucial advantage of further reduction in the required amount of reference image information. The proposed method is therefore further scalable for RR scenarios. We report extensive experimental results using a total of 9 publicly availa...Continue Reading

References

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Citations

Jan 22, 2013·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Feng ShaoThambipillai Srikanthan
Mar 17, 2015·IEEE Transactions on Cybernetics·Ke GuMin Liu
Feb 18, 2017·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Yuming FangZongming Guo
Mar 14, 2017·IEEE Transactions on Neural Networks and Learning Systems·Ke GuWeisi Lin
May 15, 2018·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Ayyoub AharPeter Schelkens
Aug 3, 2017·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society· Ke GuDaniel Thalmann
Sep 11, 2019·Applied Optics·Tobias BirnbaumPeter Schelkens

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