【作者】 卢佳佳；

【导师】 蔡坚勇；

【作者基本信息】 福建师范大学 ， 光学工程， 2008， 硕士

【摘要】 随着现代化信息技术的迅猛发展,远程视频监控广泛应用于各个领域。传统的监控常常采用有线传输的方法,受到地理环境工作内容等客观条件的限制,并不能灵活机动地根据需要变更监控点。因此,基于无线传输的监控设备被认为是远程监控很好的解决方案。H.264作为新一代的视频压缩编码标准,采用了多模式的的帧内预测、整数变换与量化、基于上下文自适应的熵编码、多参考帧的预测、高精度亚像素预测、去块滤波器以及抗误码力等技术,使得视频压缩的码率得以大幅降低,非常适合作为基于无线传输的视频压缩编码方案。考虑到监控对于实时性的高要求而无线信道本身存在带宽有限、带宽波动,误码率高等情况,源端采集的原始视频序列若不经过有效的码率控制,根本无法满足无线信道中实时传输的需要。另一方面由于无线信道的不稳定性,监测信道质量反馈参数也被认为是视频编码模式选择的一个重要指标。为了在恶劣的无线信道环境中能够为达到良好的视频传输质量,本文提出了一种自适应码率控制的方法,通过探测无线信道的反馈的信道参数,判定网络状态及编码端缓冲区满溢程度,利用二次率失真法计算出Lagrangian代价函数,自适应调节编码参数而实现输出码率的控制,利于视频的平滑传输。最后通过实测数据分析优化后的方法对视频主观质量,率失真以及压缩比的影响。更多还原

【Abstract】 With developing rapidly of modem information technology, video monitor system is adopted to various application. Generally, wire transmission is used to monitoring system, because of geographic environment or working conditions restricted, it is not easy to change monitoring spot. Therefore, it is thought that is a better solution of remote monitoring using wireless video monitor.The H.264 adopts the intra-prediction technique in the spatial domain to enhance the coding efficiency. Real-time requirement should be very important for monitoring system. Actually, in existence a situation of bandwidth limited, error rate high in the wireless channel, the original video sequence must be compressed to meet the real-time demand. This paper proposes an algorithm which is basing a new standard named H.264. This algorithm can reduce bit rate by using vary effective approach. Because of wireless channel is instability, we can decide the encoding mode according to the feedback parameter from the wireless channel. We fix the encoding mode by referencing network state to predict target parameter.In order to realize better video quality, it is necessary to change the encoding mode according to the feedback parameter of the varying wireless channel. In this paper, an approach of adaptive rate control to judge the situation of the CDMA network, and the buffer overflow or not, and figure out the cost function. Finally, we analyze the video quality, compression ratio and RD value after optimizing.更多还原