Abstract
When transmitting compressed video over a data network, one has to deal with how channel errors affect the decoding process. This is particularly a problem with data loss or erasures. In this paper we describe techniques to address this problem in the context of asynchronous transfer mode (ATM) networks. Our techniques can be extended to other types of data networks such as wireless networks. In ATM networks channel errors or congestion cause data to be dropped, which results in the loss of entire macroblocks when MPEG video is transmitted. In order to reconstruct the missing data, the location of these macroblocks must be known. We describe a technique for packing ATM cells with compressed data, whereby the location of missing macroblocks in the encoded video stream can be found. This technique also permits the proper decoding of correctly received macroblocks, and thus prevents the loss of ATM cells from affecting the decoding process. The packing strategy can also be used for wireless or other types of data networks. We also describe spatial and temporal techniques for the recovery of lost macroblocks. In particular, we develop several optimal estimation techniques for the reconstruction of missing macroblocks that contain both spatial and temporal information using a Markov random field model. We further describe a sub-optimal estimation technique that can be implemented in real time
Keywords
Markov processes, asynchronous transfer mode, data compression, decoding, error correction, estimation theory, image reconstruction, video codingATM network, MPEG video streams, Markov random field model, asynchronous transfer mode, channel errors, compressed data, compressed video, congestion, data loss, data network, decoding, error concealment, macroblocks, missing data, optimal estimation, sub-optimal estimation, video stream, wireless networks
