Abstract :
We investigate video compression techniques to address problems that require flexible video decoding. In these, the encoder has access to a number of candidate predictors that allow it to exploit source signal correlation, but only a subset of these predictors will be available at the decoder. Crucially, the encoder does not know which predictors will be available. Flexible decoding is important in a number of applications including frame-by-frame forward and backward video playback, multiview video, bitstreams switching, robust video transmission, etc. The main challenge to support flexible decoding is that the encoder needs to compress a current frame under the uncertainty on the predictor at decoder. An approach based on conventional "closed loop" prediction, e.g., motion-compensated predictive (MCP) coding in the case of video, could be developed by including multiple possible prediction residues in the bitstream, but this would lead to a considerable coding performance penalty, if all possible predictor combinations are supported, or to drifting, if only some combinations are. Moreover, it is not possible in general to guarantee that decoded versions under different prediction scenarios will be identical. In this paper, we propose a distributed source coding (DSC) based algorithm to tackle the problem. The main novelties of the proposed algorithm are that it incorporates different macroblock modes and significance coding within the DSC framework. This, combined with a judicious exploitation of correlation statistics, allows us to achieve competitive coding performance. Using forward/backward video playback as an example, we demonstrate the proposed algorithm can outperform a solution based on MCP coding.
Keywords :
decoding; motion compensation; source coding; video coding; closed loop prediction; distributed source coding; encoder; flexible video decoding; motion-compensated predictive coding; source signal correlation; video compression; Decoding; Image coding; Image processing; Robustness; Signal processing; Source coding; Statistical distributions; Switches; Uncertainty; Video compression;