The need for adapting video stream delivery over heterogeneous and unreliable networks requires self-adaptive and error resilient coding. Network bandwidth fluctuations can be handled by means of a video coding scheme which adapts to the channel conditions. However, packet losses which are frequent in wireless networks can cause a mismatch during the reconstruction in the receiver end and result in an accumulation of errors which deteriorates the quality of the delivered video. A combination of multiple description coding in pixel domain and scalable video coding schemes which addresses both video adaptation and robustness to data loss is proposed in this paper. The proposed scheme combines error concealment with spatial video scalability. In order to improve the fidelity of the reconstructed to the original frames in presence of packet loss, a multilayer polyphase spatial decomposition algorithm is proposed. Classical multiple description methods interpolate the missing data which results in smoothing and artifact at object boundaries. The proposed algorithm addresses the quality degradation due to low-pass filtering effect of interpolation methods. We also comparatively analyze the trade-off between robustness to channel errors and coding efficiency. 1. Introduction Several error concealment methods have been proposed to deal with data loss in unreliable networks among which the most important methods are forward error correction [1], intra/intercoding mode selection [2], layered coding [3], and multiple description coding (MDC) [4]. MDC methods are developed for increasing the reliability of data transmission over unreliable networks. In MDC methods, video is decomposed into descriptions which are transmitted over a probably independent network channel [4]. This decomposition can be performed before applying any transform to the video data or after application of the transform and hence to the transform coefficients. The decomposition of data can be done in spatial resolution by assigning pixels to different descriptions [5–7], in temporal resolution by assigning frames to different descriptions [8], and in signal-to-noise ratio (SNR) by transmitting less accurate pixel values in each description [9]. This decomposition should be optimized by minimizing the reconstruction error when one or some of the descriptions are lost and also by minimizing the redundancy in the descriptions. The extreme case in the MDC methods is duplicating data and transmitting identical data at every description. In this case the reconstruction error in presence of a
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