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Wireless Video Adaptation

coding channel error scalable

Definition: Wireless streaming requires video coding to be robust to channel impairments and adaptable to the network and diverse scenarios; wireless video adaptation deals with rate adaptation and robustness adaptation.

With the rapid growth of wireless communications and the advance of video codingtechniques, wireless video streaming is expected to be widely deployed in the near future. However, due to the characteristics of wireless networks such as high error rate, limited bandwidth, time-varying channel conditions, limited battery power of wireless devices and the diversity of wireless access networks and devices, wireless video streaming face many challenges. In particular, from the coding point of view, wireless streaming requires video coding to be robust to channel impairments and adaptable to the network and diverse scenarios. Traditional media coding standards such as MPEG-2 and MPEG-4 are not suitable any more since they are targeted to a particular range of bit rates and a particular type of applications. Therefore, the needs for video adaptation have becoming more important as the advance of the wireless video has become widespread. With regard to wireless video streaming, there are generally two issues in video adaptation: rate adaptation and robustness adaptation. These issues are further elaborated in the following.

The objective of rate adaptation is to intelligently remove some information from the video signal itself so that end-to-end resource requirement can be reduced. Generally, video rate adaptation can be implemented in three ways. The first approach is to store many non-scalable bitstreams for each video sequence. Each bitstream is coded at different formats or different spatial/temporal/SNR (signal-to-noise ratio) resolutions. When a user requests to access the video sequence, the server can send the bitstream which is closet to the user’s requirements. Although this method usually costs more storage spaces in the video server and the chosen bitstream may not satisfy the user’s requirement exactly, it is widely used in practical systems due to its simplicity. Recent research works have focused on the how to efficiently switch among multiple non-scalable bitstreams in order to dynamically adapt to the time-varying network conditions.

The second approach is a popular scheme based on video transcoding including decreasing the spatial resolution, reducing the SNR, or down sampling the temporal frame rate through re-encoding, re-quantization, frame dropping and etc. Although transcoding is very flexible and does not require extra storage space, it needs complex extra processes and is not suitable for large-scale diverse users. The third approach is to use scalable video coding which has inherent ability to adapt video to different requirements. Scalable video coding schemes aim at encoding a video once and decode it at multiple reduced rates and resolutions to provide simple and flexible adaptability. However, since scalable video coding intends to cover a broad range of applications, the complexity of scalable video coding is typically very high, which may limit its usage on real-time wireless video applications.

The second important issue in wireless video adaptation is the robustness adaptation, for which we try to add controlled redundancy in video bitstreams for reliable transmission over wireless channels. Robust video adaptation can be generally implemented in two ways. The first approach is to build error resilience features into the coding scheme itself. Typical error resilience features for coding include the use of resynchronization markers to recover from decoding errors and intra-coded blocks to miinimize error propagation. The second approach is to use the joint source-channel coding techniques which involve both source coding and channel coding to combat possible channel errors. We have seen extensive studies on FEC (forward error correction) based joint source-channel coding for robust video transmission. The common idea of most joint source-channel coding schemes is unequal error protection, i.e., the more important information is given more protection How to define and protect the important video information has been the main research focus in joint source-channel coding.

Besides the traditional low level video adaptation, recent advance in video content analysis has introduced new space for wireless video adaptation such as semantic event based adaptation, structural-level adaptation, and video skimming . For example, object-based video transcoding can be used to transmit a subset of objects for adaptive content delivery. On the other, recent advance in wireless network QoS supports has also brought in new challenges in wireless video adaptation such as cross-layer video adaptation.

Wischnitzer, Rachel Bernstein (1885–1989) - Jewish Architectural History [next] [back] Wireless Video - Introduction, Rate Constraints, Energy Constraints, Encoding Complexity and Encoder Power Consumption

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