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Digital Video Quality Assessment Algorithms

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Handbook of Multimedia for Digital Entertainment and Arts

Abstract

In this chapter we first describe some HVS-based approaches which try to model the visual processing stream described above, since these approaches were originally used to predict visual quality. We then describe recently proposed structural and information-theoretic approaches and feature-based approaches which are commonly used. Further, we describe recent motion-modeling based approaches, and detail performance evaluation and validation techniques for VQA algorithms. Finally, we touch upon some possible future directions for research on VQA and conclude the chapter.

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Notes

  1. 1.

    The receptive field of a neuron is its response to visual stimuli, which may depend on spatial frequency, movement, disparity or other properties. As used here, the receptive field response may be viewed as synonymous with the signal processing term impulse response.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas, USA

    Anush K. Moorthy, Kalpana Seshadrinathan & Alan C. Bovik

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  1. Anush K. Moorthy
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  2. Kalpana Seshadrinathan
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  3. Alan C. Bovik
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Correspondence to Alan C. Bovik .

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  1. Dept. Computer Science &, Florida Atlantic University, Glades Road 777, Boca Raton, 33431, U.S.A.

    Borko Furht

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Moorthy, A.K., Seshadrinathan, K., Bovik, A.C. (2009). Digital Video Quality Assessment Algorithms. In: Furht, B. (eds) Handbook of Multimedia for Digital Entertainment and Arts. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-89024-1_6

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