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SSIM-Based Distortion Estimation for Optimized Video Transmission over Inherently Noisy Channels

Author

Listed:
  • Arun Sankisa

    (Northwestern University, Evanston, IL, USA)

  • Katerina Pandremmenou

    (University of Ioannina, Ioannina, Greece)

  • Peshala V. Pahalawatta

    (AT&T, Inc., El Segundo, CA, USA)

  • Lisimachos P. Kondi

    (University of Ioannina, Ioannina, Greece)

  • Aggelos K. Katsaggelos

    (Northwestern University, Evanston, IL, USA)

Abstract

The authors present two methods for examining video quality using the Structural Similarity (SSIM) index: Iterative Distortion Estimate (IDE) and Cumulative Distortion using SSIM (CDSSIM). In the first method, three types of slices are iteratively reconstructed frame-by-frame for three different combinations of packet loss and the resulting distortions are combined using their probabilities to give the total expected distortion. In the second method, a cumulative measure of the overall distortion is computed by summing the inter-frame propagation impact to all frames affected by a slice loss. Furthermore, the authors develop a No-Reference (NR) sparse regression framework for predicting the CDSSIM metric to circumvent the real-time computational complexity in streaming video applications. The two methods are evaluated in resource allocation and packet prioritization schemes and experimental results show improved performance and better end-user quality. The accuracy of the predicted CDSSIM values is studied using standard performance measures and a Quartile-Based Prioritization (QBP) scheme.

Suggested Citation

  • Arun Sankisa & Katerina Pandremmenou & Peshala V. Pahalawatta & Lisimachos P. Kondi & Aggelos K. Katsaggelos, 2016. "SSIM-Based Distortion Estimation for Optimized Video Transmission over Inherently Noisy Channels," International Journal of Multimedia Data Engineering and Management (IJMDEM), IGI Global, vol. 7(3), pages 34-52, July.
    • Handle: RePEc:igg:jmdem0:v:7:y:2016:i:3:p:34-52
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