This paper presents an extension to video error resiliency based on distributed source coding. The paper proposes a frequency domain transcoder and a compressed domain transcoder for boosting the error resiliency of pre-encoded video using distributed source coding techniques. In both transcoders it is proposed to identify regions of interest in the pre-encoded video. In the compressed domain transcoder, the regions of interests are retained as is, whilst in the frequency domain transcoder, such regions are reproduced at a lower fidelity by requantization or ideal low pass filtering. Channel coding follows, and the parity bits are transmitted in an error resiliency supplementary bitstream. At the destination, the paper proposes a pre-decoding solution that regenerates the low fidelity ROIs and corrects the received bit stream using the aforementioned supplementary stream. The corrected bitstream is then repacked and sent to the destination decoder. In comparison with traditional FEC techniques, experimental results show robust resiliency against packet losses up to a loss ratio of 15%.

In this paper we consider the problem of efficiently serving multiple uplink video users in a wideband CDMA wireless communication system with mixed voice and video traffic. Very low available video bit rate (<64 kpbs) and multi-user interference are the major limiting factors in the system performance. Our solution is based on video summarization to achieve reasonable video quality at very low bit rate, and multi-user transmission adaptation/scheduling via summarization distortion-rate profile negotiation between base station and mobiles to meet power control constraints and minimize the interference among voice/video users. The simulation results demonstrate the effectiveness of the proposed approach

In this paper, we develop an approach toward joint source-channel coding for motion-compensated DCT-based scalable video coding and transmission. A framework for the optimal selection of the source and channel coding rates over all scalable layers is presented such that the overall distortion is minimized. The algorithm utilizes universal rate distortion characteristics which are obtained experimentally and show the sensitivity of the source encoder and decoder to channel errors. The proposed algorithm allocates the available bit rate between scalable layers and, within each layer, between source and channel coding. We present the results of this rate allocation algorithm for video transmission over a wireless channel using the H.263 Version 2 signal-to-noise ratio (SNR) scalable codec for source coding and rate-compatible punctured convolutional (RCPC) codes for channel coding. We discuss the performance of the algorithm with respect to the channel conditions, coding methodologies, layer rates, and number of layers.

In this paper a novel methodology for temporal scalability within the H.263 video coding standard is presented. Temporal scalability is defined as the transmission of previously dropped frames in the form of a scalable enhancement layer to increase the overall encoded frame rate. The proposed methodology extends the base layer rate control to the enhancement layer and incorporates an adaptive technique for enhancement layer frame selection. Three criteria important in the selection of enhancement frames are identified, allowing us to adaptively choose frames such that the overall temporal resolution of the encoded video sequence is enhanced. Experimental results are provided and compared to a non-adaptive technique where enhancement frames are selected solely on the decay of the enhancement layer buffer.