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Quality Assessment of Tensor Images

  • Chapter
Tensors in Image Processing and Computer Vision

Part of the book series: Advances in Pattern Recognition ((ACVPR))

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Abstract

The evaluation of tensor image processing algorithms is an open problem that has not been broadly handled, and specific measures have not been described to assess the quality of tensor images. In this chapter, we propose the adaptation of quality measures that have been defined in the case of conventional scalar images to the tensor case, in order to evaluate the quality of the tensor images that are most frequently used in the image processing field. Special attention is paid to the tensor features that made this extension no straightforward. Some general concepts that should be taken into account for the definition of quality indexes for tensor images based on the well-known measures for conventional scalar images are detailed. Then, some of these measures are adapted to deal with tensor images and their behavior is analyzed by means of some examples. Thus, it is shown that structure based measures outperform point-wise measures, as well as the influence of handling all the tensor components.

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Authors and Affiliations

  1. Laboratory of Image Processing (LPI), University of Valladolid, Spain

    Emma Muñoz-Moreno, Santiago Aja-Fernández & Marcos Martin-Fernandez

Authors
  1. Emma Muñoz-Moreno
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  2. Santiago Aja-Fernández
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  3. Marcos Martin-Fernandez
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Corresponding author

Correspondence to Emma Muñoz-Moreno .

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Editors and Affiliations

  1. Escuela Técnica Superior de Ingenieros de Telecomunicacíon, Universidad de Valladolid, Campus Miguel Delibes, 47011 Valladolid, Spain

    Santiago Aja-Fernández  & Rodrigo de Luis García  & 

  2. Dept. Computing, HongKong Polytechnic University, Hong Kong

    Dacheng Tao

  3. University of London Birkbeck College School of Computer Science & Information Systems, Malet Street, London, WC1E 7HX, UK

    Xuelong Li

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© 2009 Springer-Verlag London Limited

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Muñoz-Moreno, E., Aja-Fernández, S., Martin-Fernandez, M. (2009). Quality Assessment of Tensor Images. In: Aja-Fernández, S., de Luis García, R., Tao, D., Li, X. (eds) Tensors in Image Processing and Computer Vision. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-84882-299-3_4

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  • DOI: https://doi.org/10.1007/978-1-84882-299-3_4

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84882-298-6

  • Online ISBN: 978-1-84882-299-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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