Video transmission in wireless environments is a challenging task calling for high-compression efficiency as well as a network friendly design. Both have been major goals of the H.264/AVC standardization effort addressing "conversational" (i.e., video telephony) and "nonconversational" (i.e., storage, broadcast, or streaming) applications. The video compression performance of the H.264/AVC video coding layer typically provides a significant improvement. The network-friendly design goal of H.264/AVC is addressed via the network abstraction layer that has been developed to transport the coded video data over any existing and future networks including wireless systems. The main objective of this paper is to provide an overview over the tools which are likely to be used in wireless environments and discusses the most challenging application, wireless conversational services in greater detail. Appropriate justifications for the application of different tools based on experimental results are presented.

Video transport over error-prone channels may result in loss or erroneous decoding of the video. Error concealment is an effective mechanism to reconstruct the video content. In this paper, we review different error concealment methods and introduce a new framework, which we refer to as second-generation error concealment. All the error concealment methods reconstruct the lost video content by making use of some a priori knowledge about the video content. First generation error concealment builds such a priori in a heuristic manner. The proposed second-generation error concealment builds the a priori by modeling the statistics of the video content. Context-based models are trained with the correctly decoded video content, and then used to replenish the lost video content. Trained models capture the statistics of the video content and thus reconstruct the lost video content better than reconstruction by heuristics.

A robust image transmission system incorporating perceptually-based coding and error protection is proposed for wireless channels. The perceptually-based image coder consists of a wavelet transformation, uniform quantization, and variable-length entropy encoding. The coded data is placed in a spatially scalable stream divided into segments of varying perceptual importance and tolerance to transmission errors. A novel unequal error protection system is designed using turbo codes for the wireless channel, neural networks to predict decoder error and calculate erasures, and outer turbo-code concatenation of Reed-Solomon codes at different rates. A model of error tolerance is developed to minimize the added redundancy required to meet the desired throughput performance and visual quality level. The proposed system provides excellent reliability allowing the transmission of high visual quality images at a small additional redundancy and low signal-to-noise ratio (4.5 dB). 1. INTRODUCTION ...

Abstract-Error-resilient variable length codes (VLCs) have been proposed to counter bit errors over error-prone channels. In this work we establish a linkage between channel coding and watermarking by observing that watermark bits are, in effect, intentional bit errors. Using a recently introduced resynchronizing VLC, we have developed a compressed-domain watermarking algorithm where the inherent errorresilient property of the code is exploited to implement lossless, oblivious watermarking. The algorithm is implemented on MPEG-2 video Keywords—watermarking, MPEG-2, error-resilient coding I.

Video streaming over packet-loss networks faces the challenges that the networks are error-prone, transmission bandwidth is limited and fluctuating, the user device capabilities vary, and networks are heterogeneous. These challenges necessitate the need for smart adaptation of the precoded video. The focus of the thesis is error-resilient rate shaping for streaming precoded video over packet-loss networks. Given the packet-loss characteristic of the networks, the precoded video consists of channel-coded as well as source-coded bits. Error-resilient rate shaping is a filtering process that adapts the bit rates of the precoded video, in order to deliver the best video quality given the network condition at the time of delivery. We first illustrate "baseline rate shaping (BRS)" of the proposed error-resilient rate shaping as a baseline. Having introduced BRS with coarse decisions in rate adaptation, more sophisticated error-resilient rate shaping is proposed for layer-coded videos, namely, the enhancement layer video and the base layer video. "Fine-grained rate shaping (FGRS)" is proposed for streaming the enhancement layer video, and "errorconcealment aware rate shaping (ECARS)" is proposed for streaming the base layer video. FGRS and ECARS are formulated as rate-distortion (R-D) optimization problems. A two-stage R-D optimization approach is proposed to solve the R-D optimization problem in a fast and accurate manner. FGRS makes use of the fine granularity property of the MPEG-4 fine-granularityscalability bitstream and outperforms ad-hoc unequal packet-loss protection methods. ECARS takes into account error concealment (EC) performed at the receiver to deliver the part of precoded video that cannot be EC-reconstructed well. Frame dependency due to predictive coding and/...