feedback free DVC architecture using machine learning

J.L. Martinez, G. Fernandez-Escribano, H. Kalva, W.A.R.J. Weerakkody, W.A.C. Fernando, A. Garrido
2008 2008 15th IEEE International Conference on Image Processing  
Most of the reported Distributed Video Coding (DVC) architectures have a serious limitation that hinders its practical application. The uses of a feedback channel between the encoder and the decoder require an interactive decoding procedure which is a limitation for applications such as offline processing. On the other hand, the decoder needs an efficient way to estimate the probability of error without assuming the availability of the original video at the decoder. In this paper we continue
more » ... h our previous works into a more practical DVC architecture which solves both problems based on the use of machine learning. The proposed approach is based on extracting the relationships that exist between the residual frame and the number of requests over this feedback channel. We apply these concepts to pixel-domain Wyner-Ziv coding demonstrating significant savings in bitrates with a little loss of quality .
doi:10.1109/icip.2008.4711961 dblp:conf/icip/MartinezFKWFG08 fatcat:xtcqjhfrcbfnlatbglxaytn554