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2006
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Distributed Sampling and Compression of Scenes with Finite Rate of Innovation in Camera Sensor Networks

9 years 11 months ago
Distributed Sampling and Compression of Scenes with Finite Rate of Innovation in Camera Sensor Networks
We study the problem of distributed sampling and compression in sensor networks when the sensors are digital cameras that acquire a 3-D visual scene of interest from different viewing positions. We assume that sensors cannot communicate among themselves, but can process their acquired data and transmit it to a common central receiver. The main task of the receiver is then to reconstruct the best possible estimation of the original scene and the natural issue, in this context, is to understand the interplay in the reconstruction between sampling and distributed compression. In this paper, we show that if the observed scene belongs to the class of signals that can be represented with a finite number of parameters, we can determine the minimum number of sensors that allows perfect reconstruction of the scene. Then, we present a practical distributed coding approach that leads to a rate-distortion behaviour at the decoder that is independent of the number of sensors, when this number incr...
Nicolas Gehrig, Pier Luigi Dragotti
Added 25 Dec 2009
Updated 25 Dec 2009
Type Conference
Year 2006
Where DCC
Authors Nicolas Gehrig, Pier Luigi Dragotti
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