This article is part of the series Wavelets in Source Coding, Communications, and Networks.

Open Access Research Article

Energy-Efficient Transmission of Wavelet-Based Images in Wireless Sensor Networks

Vincent Lecuire*, Cristian Duran-Faundez and Nicolas Krommenacker

Author Affiliations

Centre de Recherche en Automatique de Nancy (CRAN UMR 7039), Nancy-Université, CNRS, Faculté des Sciences et Techniques, BP 239, Vandoeuvre lès Nancy Cedex 54506, France

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EURASIP Journal on Image and Video Processing 2007, 2007:047345 doi:10.1155/2007/47345


The electronic version of this article is the complete one and can be found online at: http://jivp.eurasipjournals.com/content/2007/1/047345


Received:14 August 2006
Revisions received:15 December 2006
Accepted:22 December 2006
Published:8 January 2007

© 2007 Lecuire et al.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

We propose a self-adaptive image transmission scheme driven by energy efficiency considerations in order to be suitable for wireless sensor networks. It is based on wavelet image transform and semireliable transmission to achieve energy conservation. Wavelet image transform provides data decomposition in multiple levels of resolution, so the image can be divided into packets with different priorities. Semireliable transmission enables priority-based packet discarding by intermediate nodes according to their battery's state-of-charge. Such an image transmission approach provides a graceful tradeoff between the reconstructed images quality and the sensor nodes' lifetime. An analytical study in terms of dissipated energy is performed to compare the self-adaptive image transmission scheme to a fully reliable scheme. Since image processing is computationally intensive and operates on a large data set, the cost of the wavelet image transform is considered in the energy consumption analysis. Results show up to 80% reduction in the energy consumption achieved by our proposal compared to a nonenergy-aware one, with the guarantee for the image quality to be lower-bounded.

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