Distributed Coding of Random Dot Stereograms with Unsupervised Learning of Disparity

Abstract

Distributed compression is particularly attractive for stereoscopic images since it avoids communication between cameras. Since compression performance depends on exploiting the redundancy between images, knowing the disparity is important at the decoder. Unfortunately, distributed encoders cannot calculate this disparity and communicate it. We consider a… (More)
DOI: 10.1109/MMSP.2006.285257

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Cite this paper

@article{Varodayan2006DistributedCO, title={Distributed Coding of Random Dot Stereograms with Unsupervised Learning of Disparity}, author={David P. Varodayan and Aditya Mavlankar and Markus Flierl and Bernd Girod}, journal={2006 IEEE Workshop on Multimedia Signal Processing}, year={2006}, pages={5-8} }