文章基本信息

标题：放送品質映像伝送における映像品質の救済
本地全文：下载
作者：Kenichi Arai ; Satoshi Ono
期刊名称：映像情報メディア学会誌
印刷版ISSN：1342-6907
电子版ISSN：1881-6908
出版年度：2005
卷号：59
期号：2
页码：309-317
DOI：10.3169/itej.59.309
出版社：The Institute of Image Information and Television Engineers
摘要：The impact of packet losses on broadcast-quality video transmission through an asynchronous network is discussed based on the quality of the video playback. The main requirements for broadcast-quality video transmission are quality, synchronization, and smooth failover. Therefore, video quality is also related to network quality in an asynchronous network. When video frames that contain network packet losses are decoded, noise-free video cannot be maintained for block noises caused in video playback. One of the most important features of real-time video data transmission through an asynchronous network is the ability to correct and conceal errors. Adding redundant bits to the source information, as in forward error correction and error correcting code, increases the data bandwidth. Adding redundancy, such as by interleaving, lengthens the latency of the video playback. The appropriate redundancy factor, therefore should ensure a real-time response, minimize latency, and maintain video playback quality. Therefore, when selecting an appropriate error correction/concealment code, it is necessary to clarify the impact of successive packet losses on the quality degradation of broadcast-quality video. To clarify the relationship between the broadcast-quality video quality and network packet losses, we analyzed data based on observation of an actual network with the loss window size as a parameter. Next, we discussed the characteristics of the block noises on the video playback using the Markov model. For this purpose, we made an 80, 000-km-long ATM path on the Japan Gigabit Network and examined the peak-signal to noise ratio of the SMPTE-314M.video playback that contained ATM cell losses.
关键词：Broadcast-quality Video Transmission;Asynchronous Network;Japan Gigabit Network;SMPTE-314M video;New Video Platform;Loss Window Size;Markov Model