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access icon free Regularity of spectral residual for reduced reference image quality assessment

  • Author(s): Delei Liu 1 ; Fuzhong Li 1 ; Houbing Song 2
    • View affiliations
  • Source: Volume 11, Issue 12, December 2017, p. 1135 – 1141
    DOI:  10.1049/iet-ipr.2016.0593 , Print ISSN 1751-9659, Online ISSN 1751-9667
© The Institution of Engineering and Technology
Received 30/07/2016, Accepted 19/03/2017, Revised 14/01/2017, Published 28/03/2017

Inspired by the facts that visual saliency captures more attention and spectral residual (SR) can indicate the saliency of the image, a novel reduced-reference image quality assessment metric is proposed based on the regularity of the SR. The orientation and frequency components of an image are first extracted in wavelet domain. Then SR is obtained to represent the saliency of the component. Next fractal dimension is adopted to encode SR and concatenated as the image features. Finally, the feature differences between reference image and distorted one are pooled as the quality score. The proposed metric is evaluated on four largest image databases (TID2013, TID2008, CSIQ, and LIVE databases), and experimental results confirm that the proposed metric has a good performance.

Inspec keywords: wavelet transforms; image coding; feature extraction

Other keywords: reduced reference image quality assessment metric; spectral residual regularity; visual saliency; orientation components; wavelet domain; SR encoding; image databases; frequency components; image features; quality score; fractal dimension

Subjects: Integral transforms; Image recognition; Image and video coding; Integral transforms; Computer vision and image processing techniques

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