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  • Research Article
  • Open Access

Collaborative Image Coding and Transmission over Wireless Sensor Networks

EURASIP Journal on Advances in Signal Processing20062007:070481

https://doi.org/10.1155/2007/70481

  • Received: 6 February 2006
  • Accepted: 13 August 2006
  • Published:

Abstract

The imaging sensors are able to provide intuitive visual information for quick recognition and decision. However, imaging sensors usually generate vast amount of data. Therefore, processing and coding of image data collected in a sensor network for the purpose of energy efficient transmission poses a significant technical challenge. In particular, multiple sensors may be collecting similar visual information simultaneously. We propose in this paper a novel collaborative image coding and transmission scheme to minimize the energy for data transmission. First, we apply a shape matching method to coarsely register images to find out maximal overlap to exploit the spatial correlation between images acquired from neighboring sensors. For a given image sequence, we transmit background image only once. A lightweight and efficient background subtraction method is employed to detect targets. Only the regions of target and their spatial locations are transmitted to the monitoring center. The whole image can then be reconstructed by fusing the background and the target images as well as their spatial locations. Experimental results show that the energy for image transmission can indeed be greatly reduced with collaborative image coding and transmission.

Keywords

  • Sensor Network
  • Wireless Sensor Network
  • Visual Information
  • Imaging Sensor
  • Target Image

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Authors’ Affiliations

(1)
MAKO Surgical Corporation, Fort Lauderdale, FL 33317, USA
(2)
Department of Electrical and Computer Engineering, Florida Institute of Technology (FIT), Melbourne, FL 32901, USA

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Copyright

© M.Wu and C.W. Chen 2007

This article is published under license to BioMed Central Ltd. 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.

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