Distributed compression of the plenoptic function
In this paper, we consider the problem of distributed compression in camera sensor networks. Due to the spatial proximity of the different cameras, acquired images can be highly dependent. The correlation in the visual information retrieved is related to the structure of the plenoptic function and can be estimated using geometrical information such as the position of the cameras and some bounds on the location of the objects. We propose a distributed compression scheme that takes advantage of this geometrical information in order to reduce the overall transmission rate from the sensors to a common central receiver. This new approach allows for a flexible repartition of the transmission bit-rates amongst the encoders and is optimal in many cases. Moreover, we show that our coding scheme can be made resilient to a fixed number of occlusions and that perfect reconstruction and interpolation are possible at the receiver.