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Reduced-Reference Image Quality Assessment Based on Edge Preservation

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Book cover Mobile Multimedia Communications (MobiMedia 2011)

Abstract

Assessing the subjective quality of processed images through an objective quality metric is a key issue in multimedia processing and transmission. In some scenarios, it is also important to evaluate the quality of the received images with minimal reference to the transmitted ones. For instance, for closed-loop optimisation of image and video transmission, the quality measure can be evaluated at the receiver and provided as feedback information to the system controller. The original images - prior to compression and transmission - are not usually available at the receiver side, and it is important to rely at the receiver side on an objective quality metric that does not need reference or needs minimal reference to the original images.

The observation that the human eye is very sensitive to edge and contour information of an image underpins the proposal of our reduced reference (RR) quality metric, which compares edge information between the distorted and the original image.

Results highlight that the metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art reduced reference metric.

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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Martini, M.G., Villarini, B., Fiorucci, F. (2012). Reduced-Reference Image Quality Assessment Based on Edge Preservation. In: Atzori, L., Delgado, J., Giusto, D. (eds) Mobile Multimedia Communications. MobiMedia 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 79. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30419-4_3

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  • DOI: https://doi.org/10.1007/978-3-642-30419-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30418-7

  • Online ISBN: 978-3-642-30419-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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