The problem of error control and concealment in video communication is becoming increasingly important because of the growing interest in video delivery over unreliable channels such as wireless networks and the Internet. This paper reviews the techniques that have been developed for error control and concealment in the past ten to fifteen years. These techniques are described in three categories according to the roles that the encoder and decoder play in the underlying approaches. Forward error concealment includes methods that add redundancy at the source end to enhance error resilience of the coded bit streams. Error concealment by postprocessing refers to operations at the decoder to recover the damaged areas based on characteristics of image and video signals. Finally, interactive error concealment covers techniques that are dependent on a dialog between the source and destination. Both current research activities and practice in international standards are covered.

this paper, we discuss such last-line-of-defense 0018--9219/99$10.00 1999 IEEE PROCEEDINGS OF THE IEEE, VOL. 87, NO. 10, OCTOBER 1999 1707 techniques that can be used to make low bit-rate video coders error resilient. We concentrate on techniques that use acknowledgment information provided by a feedback channel

In this paper we address the problem of robust video transmission in error prone environments. The approach is compatible with the ITU-T video coding standard H.263. Fading situations in mobile networks are tolerated and the image quality degradation due to spatio-temporal error propagation is minimized utilizing a feedback channel between transmitter and receiver carrying acknowledgment information. In a first step, corrupted Group of Blocks (GOBs) are concealed to avoid annoying artifacts caused by decoding of an erroneous bit stream. The GOB and the corresponding frame number are reported to the transmitter via the back channel. The encoder evaluates the negative acknowledgments and reconstructs the spatial and temporal error propagation. A low complexity algorithm for real-time reconstruction of spatio-temporal error propagation is described in detail. Rapid error recovery is achieved by INTRA refreshing image regions (Macroblocks) bearing visible distortion. The feedback channel m...

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.

Abstract—We consider a situation where a video sequence is to be compressed and transmitted over a wireless channel. Our goal is to limit the amount of distortion in the received video sequence, while minimizing transmission energy. To accomplish this goal, we consider error resilience and concealment techniques at the source coding level, and transmission power management at the physical layer. We jointly consider these approaches in a novel framework. In this setting, we formulate and solve an optimization problem that corresponds to minimizing the energy required to transmit video under distortion and delay constraints. Experimental results show that simultaneously adjusting the source coding and transmission power is more energy efficient than considering these factors separately. Index Terms—Error concealment, error resilience, expected distortion, optimal mode selection, power and rate control. I.

Over the last one and a half decades, digital video compression technologies have become an integral part of the way we create, communicate, and consume visual information. In this paper, techniques for video compression are reviewed, starting from basic concepts. The rate-distortion performance of modern video compression schemes is the result of an interaction between motion representation techniques, intra-picture prediction techniques, waveform coding of differences, and waveform coding of various refreshed regions. The paper starts with an explanation of the basic concepts of video codec design and then explains how these various features have been integrated into international standards, up to and including the most recent such standard, known as H.264/AVC.

Multimedia applications involving the transmission of video over communication networks are rapidly increasing in popularity. Such applications can greatly benefit from adapting video coding parameters to network conditions as well as adapting network parameters to better support the application requirements. These two dimensions can both be viewed as allocating source and network resources to improve video quality. In this paper, we highlight recent advances in optimal resource allocation for real-time video communications over unreliable and resource constrained communication channels. More specifically, we focus on point-to-point coding and delivery schemes in which the sequences are encoded on the fly. We present a high-level framework for resource-distortion optimization. The framework can be used for jointly considering factors across network layers, including source coding, channel resource allocation, and error concealment. For example, resources can take the form of transmission energy in a wireless channel, and transmission cost in a DiffServ-based Internet channel. This framework can be used to optimally trade off resource consumption with end-to-end video quality in packet-based video transmission. After giving an overview of this framework, we review recent work in two areas—energy efficient wireless video transmission and resource allocation for Internet-based applications. Keywords—Cross-layer design, energy efficient, error resilience, distortion estimation, internet video, wireless video. I.

Abstract—When transmitting compressed video over a data network, one has to deal with how channel errors affect the decoding process. This is particularly a problem with data loss or erasures. In this paper we describe techniques to address this problem in the context of Asynchronous Transfer Mode (ATM) networks. Our techniques can be extended to other types of data networks such as wireless networks. In ATM networks channel errors or congestion cause data to be dropped, which results in the loss of entire macroblocks when MPEG video is transmitted. In order to reconstruct the missing data, the location of these macroblocks must be known. We describe a technique for packing ATM cells with compressed data, whereby the location of missing macroblocks in the encoded video stream can be found. This technique also permits the proper decoding of correctly received macroblocks, and thus prevents the loss of ATM cells from affecting the decoding process. The packing strategy can also be used for wireless or other types of data networks. We also describe spatial and temporal techniques for the recovery of lost macroblocks. In particular, we develop several optimal estimation techniques for the reconstruction of missing macroblocks that contain both spatial and temporal information using a Markov random field model. We further describe a sub-optimal estimation technique that can be implemented in real time. Index Terms—ATM, cell loss, cell packing, error concealment, motion vectors, Markov random field, spatial reconstruction, temporal reconstruction. I.

In this paper we review error resilience techniques for real-time video transport over unreliable networks. Topics covered include an introduction to today's protocol and network environments and their characteristics, encoder error resilience tools, decoder error concealment techniques, as well as techniques that require cooperation between encoder, decoder and the network. We provide a review of general principles of these techniques as well as specific implementations adopted by the H.263 and MPEG-4 video coding standards. The majority of the paper is devoted to the techniques developed for block-based hybrid coders using motion-compensated prediction and transform coding. A separate section covers error resilience techniques for shape coding in MPEG-4. I. Introduction A. Error Resilience in Video Communications: Importance and Approach A video communications system typically involves five steps, as shown in Figure 1. The video is first compressed by a video encoder to reduce th...

Handling packet loss or delay in the mobile and/or Internet environment is usually a challenging problem for multimedia transmission. Using connection-oriented protocol such as TCP may introduce intolerable time delay in retransmission. Using datagram-oriented protocols such as UDP may cause partial representation in case of packet loss. In this paper, we propose a new method of using our self-authentication-and-recovery images (SARI) to do the error detection and concealment in the UDP environment. The lost information in a SARI image can be approximately recovered based on the embedded watermark, which includes the content-based authentication information and recovery information. Images or video frames are watermarked in a priori such that no additional mechanism is needed in the networking or the encoding process. Because the recovery is not based on adjacent blocks, the proposed method can recover the corrupted area even though the information loss happen in large areas or high variant areas. Our experiments show the advantages of such technique in both transmission time saving and broad application potentials.