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Energy-efficient wavelet image compression in Wireless Sensor Network

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4 Author(s)
Mohsen Nasri ; Laboratoire de Micro-Optoélectronique et Nanostructures(LMON), Faculté des Sciences de Monastir / Institut Supérieur d'Informatique et de Mathématiques de Monastir, Tunisia ; Abdelhamid Helali ; Halim Sghaier ; Hassen Maaref

In the recent years, the wireless technology would have known an exponential growth, which has an impact on developing and improving the field of telecommunications beyond the means of transmission wire to the radio frequency communication. The Wireless Sensor Network (WSN) is enrolled in this context. It's a collection of component (nodes) organized into a cooperative network. The main components of this network are tiny battery powered cameras with wireless communication capability. Therefore, image transfer in WSNs presents major challenge which raises issues related to its representation, its storage and its transmission. However, communication of image content has several bottlenecks, including limited bandwidth of cellular networks, restricted computational power, limited storage capability, and battery constraints of the appliances. In this paper, we address the energy, system lifetime and bandwidth bottlenecks of image communication. We present an efficient adaptive compression scheme that can significantly minimize the energy required for wireless image communication while meeting bandwidth constraints of wireless network and image quality. Based on Discrete Wavelet Transform, we propose an efficient image compression scheme, enabling significant reduction in computation energy needed with minimal degradation of image quality. Simulation results are done with C++ and show that the proposed scheme optimizes network lifetime, reduces significantly the amount of required memory and minimizes both (i) computation energy, by reducing the computation needed to compress an image and (ii) communication energy, consumed by the RF component which is proportional to the number of transmitted bits.

Published in:

2010 International Conference on Wireless and Ubiquitous Systems

Date of Conference:

8-10 Oct. 2010