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Color Image Quality Assessment Based on Gradient Similarity and Distance Transform

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Advanced Concepts for Intelligent Vision Systems (ACIVS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9386))

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Abstract

In this paper, a new full-reference image quality assessment (IQA) metric is proposed. It is based on a Distance transform (DT) and a gradient similarity. The gradient images are sensitive to image distortions. Consequently, investigations have been carried out using the global variation of the gradient and the image skeleton for computing an overall image quality prediction. First, color image is transformed to YIQ space. Secondly, the gradient images and DT are identified from Y component. Thirdly, color distortion is computed from I and Q components. Then, the maximum DT similarity of the reference and test images is defined. Finally, combining the previous metrics the difference between test and references images is derived. The obtained results have shown the efficiency of the suggested measure.

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Author information

Authors and Affiliations

  1. Faculty ST, ICOSI Lab., Khenchela University, BP 1252 El Houria, 40004, Khenchela, Algeria

    Zianou Ahmed Seghir

  2. Laboratoire dAutomatique et de Robotique, Université des fréres Mentouri Constantine, Constantine, Algeria

    Fella Hachouf

Authors
  1. Zianou Ahmed Seghir
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  2. Fella Hachouf
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Corresponding author

Correspondence to Zianou Ahmed Seghir .

Editor information

Editors and Affiliations

  1. Dipartimento di Matematica e Informatica, Università di Catania, Catania, Catania, Italy

    Sebastiano Battiato

  2. Arcueil CX, France

    Jacques Blanc-Talon

  3. Catania, Italy

    Giovanni Gallo

  4. Gent, Belgium

    Wilfried Philips

  5. CSIRO, Sydney, New South Wales, Australia

    Dan Popescu

  6. Vision Lab., University of Antwerp, Antwerpen, Belgium

    Paul Scheunders

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Seghir, Z.A., Hachouf, F. (2015). Color Image Quality Assessment Based on Gradient Similarity and Distance Transform. In: Battiato, S., Blanc-Talon, J., Gallo, G., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2015. Lecture Notes in Computer Science(), vol 9386. Springer, Cham. https://doi.org/10.1007/978-3-319-25903-1_51

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  • DOI: https://doi.org/10.1007/978-3-319-25903-1_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25902-4

  • Online ISBN: 978-3-319-25903-1

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