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    Prediction-compensated polyphase multiple description image coding with adaptive redundancy control

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    In this paper, a novel multiple description coding (MDC) system is proposed, consisting of two thrust contributions: 1) a new polyphase MDC scheme, called the prediction-compensated polyphase MDC (PCP-MDC); and 2) an adaptive redundancy control (ARC) scheme for yielding optimal tradeoff between coding efficiency and error resilience. The PCP-MDC partitions each quincunx-downsampled description into two subdescriptions, called the primary subdescription (PS) and dual subdescription (DS). The PS is encoded by the H.264/AVC intra coding, while the DS is subject to prediction coding based on the reconstructed PS. For prediction, the mode-guided directional prediction algorithm is developed to conduct a fast and accurate prediction for the DS. For the second thrust contribution, two fundamental issues regarding the inserted redundancy are addressed in the proposed ARC scheme: quality and quantity. For the quality issue, the residuals of cross prediction are inserted into each description. For the quantity issue, the amount of redundancy bits allocated to each description is determined according to the network condition; for that, the probability of channel failure is incorporated into mathematical formulation on the derivation of optimal redundancy allocation condition. To implement the derived optimal condition, a fast estimation algorithm of the rate-distortion function is then developed, followed by exploiting successive approaching algorithm to identify the optimal partition of the target bitrate between the primary part of the description and its complementary part (i.e., the redundancy part). We also develop a post-processing filter, called the switching Gaussian filter, to remove the granular artifacts that tend to occur in any polyphase MDC approach when two descriptions are received and encoded at low bitrates. Extensive simulation results have consistently shown that the proposed MDC system significantly outperforms other state-of-the-art MDC methods on coding- performance with much lower computational complexity
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