Distributed image compression for sensor networks using correspondence analysis and super-resolution

TLDR: A distributed coding technique for images captured from sensors with overlapping fields of view in a sensor network is outlined and super-resolution techniques are employed at the receiver to reconstruct a high-resolution version of the common block.

Abstract: A distributed coding technique for images captured from sensors with overlapping fields of view in a sensor network is outlined First, images from correlated views are roughly registered (relative to a sensor of primary interest) via a low-bandwidth data-sharing method involving image feature points and feature point correspondence An area of overlap is then identified, and each sensor transmits a low-resolution version of the common image block to the receiver, amortizing the coding cost for that block among the set of sensors Super-resolution techniques are finally employed at the receiver to reconstruct a high-resolution version of the common block We discuss the registration and super-resolution techniques used and present examples of each step in the proposed coding process A numerical analysis illustrating the potential coding benefit follows, and we conclude with a brief discussion of the key issues remaining to be resolved on the path to coder robustness