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Quality-aware predictor-based adaptation of still images for the multimedia messaging service

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Abstract

The Multimedia Messaging Service (MMS) allows users with heterogeneous terminals to exchange structured messages composed of text, images, sound, and video. The MMS market is growing rapidly, posing the problem of MMS adaptation, which is necessary to ensure terminal interoperability. Message adaptation involves technological challenges, especially considering the high volume of messages that this service can handle. In this work, we propose novel predictor-based dynamic programming approaches to MMS adaptation, which provide a framework for explicit maximization of the user experience, rather than relying on heuristics to deliver adapted messages satisfactorily. We show that the proposed solutions lead to noticeably superior image quality and faster transcoding times than comparable algorithms offered in products currently on the market and those described in the literature.

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Acknowledgements

This work was funded by Vantrix Corporation and by the Natural Sciences and Engineering Research Council of Canada under the Collaborative Research and Development Program (NSERC-CRD 428942-11).

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Authors and Affiliations

  1. Département d’informatique, Université du Québec à Rimouski, Rimouski, Canada

    Steven Pigeon

  2. Department of Software and IT Engineering, École de Technologie Supérieure, Montreal, Canada

    Stéphane Coulombe

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  1. Steven Pigeon
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  2. Stéphane Coulombe
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Correspondence to Stéphane Coulombe.

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Pigeon, S., Coulombe, S. Quality-aware predictor-based adaptation of still images for the multimedia messaging service. Multimed Tools Appl 72, 1841–1865 (2014). https://doi.org/10.1007/s11042-013-1481-1

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