Distributed Successive Refinement of Multiview Images Using Broadcast Advantage
In environmental monitoring applications, having multiple cameras focus on common scenery increases robustness of the system. To save energy based on user demand, successive refinement image coding is important, as it allows us to progressively request better image quality. By exploiting the broadcast nature and correlation between multiview images, we investigate a two-camera setup and propose a novel two-encoder successive refinement scheme which imitates a ping-pong game. For the bivariate Gaussian case, we prove that this scheme is successively refinable on the theoretical rate-distortion limit of distributed coding (Wagner surface) under arbitrary settings. For stereo-view images, we develop a practical successive refinement coding algorithm using the same idea. The simulation results show that this scheme operates close to the distributed coding bound.