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Image Quality Assessment Measure Based on Natural Image Statistics in the Tetrolet Domain

  • Abdelkaher Ait Abdelouahad
  • Mohammed El Hassouni
  • Hocine Cherifi
  • Driss Aboutajdine
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7340)

Abstract

This paper deals with a reduced reference (RR) image quality measure based on natural image statistics modeling. For this purpose, Tetrolet transform is used since it provides a convenient way to capture local geometric structures. This transform is applied to both reference and distorted images. Then, Gaussian Scale Mixture (GSM) is proposed to model subbands in order to take account statistical dependencies between tetrolet coefficients. In order to quantify the visual degradation, a measure based on Kullback Leibler Divergence (KLD) is provided. The proposed measure was tested on the Cornell VCL A-57 dataset and compared with other measures according to FR-TV1 VQEG framework.

Keywords

RRIQA Tetrolet transform natural image statistics Gaussian Scale Mixture 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Abdelkaher Ait Abdelouahad
    • 1
  • Mohammed El Hassouni
    • 2
  • Hocine Cherifi
    • 3
  • Driss Aboutajdine
    • 1
  1. 1.LRIT URACUniversity of Mohammed V-AgdalMorocco
  2. 2.DESTEC, FLSHRUniversity of Mohammed V-AgdalMorocco
  3. 3.Le2i-UMR CNRS 5158University of BurgundyDijonFrance

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