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Information Systems Design and Intelligent Applications pp 369–378Cite as

Analysis and Evaluation of Image Quality Metrics

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 340))

Abstract

Image Quality Assessment (IQA) is a very difficult task, yet highly important characteristic for evaluation of the image quality. Widely popular IQA techniques, belonging to objective fidelity, like Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) or subjective fidelity which corresponds to the human visual system (HVS), like, Universal Quality Index (UQI), Structural SIMilarity (SSIM), Feature SIMilarity (FSIM), Feature SIMilarity for color images (FSIMc), Gradient Magnitude Similarity (GSM) have been discussed in this paper. Also quality measured on basis of degradation model and Noise Quality Measure (NQM) has been discussed. Experiments have been conducted on IVC database available online at http://www.irccyn.ec-nantes.fr/ivcdb/ and verified from the CSIQ database and LAR database available online at http://vision.okstate.edu/?loc=csiq and http://www.irccyn.ec-nantes.fr/~autrusse/Databases/LAR/. On the basis of the obtained values judgements about the image distortion and hence the optimum image quality metric has been decided. It has been found from all the experiments conducted that FSIM is the best metric for the JPEG, JPEG2000, blur and LAR whereas UQI failed to give better results for all except JPEG2000.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Kalyani Government Engineering College, Kalyani, Nadia, West Bengal, India

    Tina Samajdar

  2. Department of Information Technology, Kalyani Government Engineering College, Kalyani, Nadia, West Bengal, India

    Md. Iqbal Quraishi

Authors
  1. Tina Samajdar
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  2. Md. Iqbal Quraishi
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Corresponding author

Correspondence to Tina Samajdar .

Editor information

Editors and Affiliations

  1. University of Kalyanai, Kalyanai, West Bengal, India

    J. K. Mandal

  2. Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Vishakapatnam, India

    Suresh Chandra Satapathy

  3. Dean, Faculty of Engineering, Technology, University of Kalyani, Kalyani, West Bengal, India

    Manas Kumar Sanyal

  4. Engineering and Technological Studies, University of Kalyani, Kalyani, West Bengal, India

    Partha Pratim Sarkar

  5. Department Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India

    Anirban Mukhopadhyay

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Samajdar, T., Quraishi, M.I. (2015). Analysis and Evaluation of Image Quality Metrics. In: Mandal, J., Satapathy, S., Kumar Sanyal, M., Sarkar, P., Mukhopadhyay, A. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 340. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2247-7_38

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  • DOI: https://doi.org/10.1007/978-81-322-2247-7_38

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2246-0

  • Online ISBN: 978-81-322-2247-7

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