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We investigate compression techniques to support flexible video decoding. In these, encoders generate a single compressed bit-stream that can be decoded in several different ways, so that users or decoders can choose among several available decoding paths. Flexible decoding has several advantages, including improved accessibility of the compressed data for emerging applications (e.g., multiview video) and enhanced robustness for video communication. Flexible decoding, however, makes it difficult for compression algorithms to exploit temporal redundancy: when the decoder can choose among different decoding paths, the encoder no longer knows deterministically which previously reconstructed frames will be available for decoding the current frame. Therefore, to support flexible decoding, encoders need to operate under uncertainty on the decoder predictor status. This paper extends our previous work on video compression with decoder predictor uncertainty using distributed source coding (DSC). We present a thorough discussion of flexible decoding, including its theoretical performance. The main advantage of a DSC approach to flexible decoding is that the information communicated from the encoder to the decoder (namely, the parity bits) is independent of a specific predictor. By "decoupling" the compressed information from the predictor, we will demonstrate that, theoretically and experimentally, DSC can lead to a solution that compares favorably to one based on conventional "closed loop" prediction (CLP), where multiple prediction residues are sent, one for each possible predictor available at the decoder. 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. Experimental results using multiview video coding and forward/backward video playback suggest the proposed DSC-based solution can outperform flexible decoding techniques based on CLP coding.