基于镜头切割检测的视频传输预测图像刷新方法

Yu-Hua Ai, Wu Ye, Suili Feng, Wei Zhou
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引用次数: 0

摘要

传统的方法是帧内刷新,以防止误差的传播和重构视频质量的快速下降。提出了一种基于场景-上下文参考图像命名预测图像刷新的抗错方法。并提出了一种新的镜头切割检测方法来实现场景-上下文参考图像,取代了传统的视频分割方法,如像素或直方图差分方法。并且我们的镜头切割检测需要较少的计算量,并且很容易嵌入到H.264/AVC中。在不可靠的无线网络对帧内刷新率要求较高的情况下,与帧内刷新率方法相比,该方法在保持帧内刷新率的同时,可以实现明显的帧位保存效果
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Picture Refresh Based on a Novel Shot Cut Detection Method for Video Transmission
In order to stop the error propagation and the quick of degradation of the reconstructed video quality, the traditional method is intra-frame refresh. This paper proposes a novel error-resilient method which names predictive picture refresh based on scene-context reference picture. And it also proposes a novel shot cut detection to achieve the scene-context reference picture, instead of the traditional video segmentations, such as pixel or histogram difference methods. And our shot cut detection needs less computation and is easily embedded in the H.264/AVC. When the unreliable wireless network requires high intra-frame-refresh rates, compared with the intra-frame-refresh method, our method can achieve apparent saving effect in frame bits while maintaining the similar quality
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